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  • 51.
    Di Marco, Piergiuseppe
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Park, Pan Gun
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    TREnD: A timely, reliable, energy-efficient and dynamic wsn protocol for control applications2010In: IEEE International Conference on Communications, 2010Conference paper (Refereed)
    Abstract [en]

    Control applications over wireless sensor networks (WSNs) require timely, reliable, and energy efficient communications. Cross-layer interaction is an essential design paradigm to exploit the complex interaction among the layers of the protocol stack and reach a maximum efficiency. Such a design approach is challenging because reliability and latency of delivered packets and energy are at odds, and resource constrained nodes support only simple algorithms. In this paper, the TREnD protocol is introduced for control applications over WSNs in industrial environments. It is a cross-layer protocol that embraces efficiently routing algorithm, MAC, data aggregation, duty cycling, and radio power control. The protocol parameters are adapted by an optimization problem, whose objective function is the network energy consumption, and the constraints are the reliability and latency of the packets. TREnD uses a simple algorithm that allows the network to meet the reliability and latency required by the control application while minimizing for energy consumption. TREnD is implemented on a test-bed and compared to some existing protocols. Experimental results show good performance in terms of reliability, latency, low duty cycle, and load balancing for both static and time-varying scenarios.

  • 52.
    Di Marco, Piergiuseppe
    et al.
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Park, Pangun
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Automatic Control.
    Analytical Modelling of IEEE 802.15.4 for Multi-hop Networks with Heterogeneous Traffic and Hidden Terminals2010In: 2010 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE GLOBECOM 2010, 2010Conference paper (Refereed)
    Abstract [en]

    IEEE 802.15.4 multi-hop wireless networks are an important communication infrastructure for many applications, including industrial control, home automation, and smart grids. Existing analysis of the IEEE 802.15.4 medium access control (MAC) protocol are often based on assumptions of homogeneous traffic and ideal carrier sensing, which are far from the reality when predicting performance for multi-hop networks. In this paper, a generalized analysis of the unslotted IEEE 802.15.4 MAC is presented. The model considers heterogeneous traffic and hidden terminals due to limited carrier sensing capabilities, and allows us to investigate jointly IEEE 802.15.4 MAC and routing algorithms. The analysis is validated via Monte Carlo simulations, which show that routing over multi-hop networks is significantly influenced by the IEEE 802.15.4 MAC performance. Routing decisions based on packet loss probability may lead to an unbalanced distribution of the traffic load across paths, thus motivating the need of a joint optimization of routing and MAC.

  • 53. Di Paolo, L.
    et al.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Graziosi, F.
    Santucci, F.
    Tennina, S.
    Performance analysis of distributed source coding and packet aggregation in wireless sensor networks2006In: GLOBECOM - IEEE Global Telecommunications Conference, 2006, p. 1-6Conference paper (Refereed)
    Abstract [en]

    In this paper, we propose a theoretical setup for evaluation of energy efficiency of wireless sensor networks (WSNs) with distributed source coding (DSC) algorithms and packet aggregation (PA). We consider four topologies for DSC and three alternatives for PA, and the system model includes a realistic network architecture with multi-hop communication, automatic repeat request protocol (ARQ), and packet losses. The analysis is carried out in two steps. Firstly we derive the packet loss probability, and then evaluate the average number of packets transmitted throughout the network. This second performance index can then be mapped onto an energy efficiency indicator. The proposed model is specifically adopted for performance comparison of the different coding strategies and aggregation schemes in terms of energy efficiency. Numerical results show that packet overheads have a relevant influence on performance, while the ARQ protocol introduces negligible effects on the energy consumption. Furthermore, DSC topologies with masterslave approach and fragmentation of packets exhibit better performance.

  • 54.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Power Allocation for Channel Estimation and EnergyBeamforming in Wirelessly Powered Sensor Networks2018In: Proceedings of IEEE International Conference on Communications Workshops, 2018Conference paper (Refereed)
    Abstract [en]

    Wirelessly powered sensor networks (WPSNs) are becoming increasingly important to monitor many internet-of-things systems. In these WPSNs, dedicated base stations (BSs) with multiple antennas charge the sensor nodes without the need of replacing their batteries thanks to two essential procedures: i)  getting of the channel state information of the nodes by sending pilots, and based on this, ii) performing energy beamforming to transmit energy to the nodes. However, the BSs have limited power budget and thus these two procedures are not independent, contrarily to what  is assumed in some previous studies. In this paper, we investigate the novel problem of how to optimally allocate the power for channel estimation and energy transmission. Although the problem is non-convex, we provide a new solution approach and a performance analysis in terms of optimality and complexity. We also provide a closed form solution for the case where the channels are estimated based on a least square estimation. The simulations show a gain of approximately 10% in allocating the power optimally, and the importance of improving the channel estimation efficiency.

  • 55.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Xiao, Ming
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Flowing with the water: On optimal monitoring of water distribution networks by mobile sensors2016Conference paper (Refereed)
  • 56.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Xiao, Ming
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Joint node deployment and wireless energy transfer scheduling for immortal sensor networks2017In: 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 7959918Conference paper (Refereed)
    Abstract [en]

    The lifetime of a wireless sensor network (WSN) is limited by the lifetime of the individual sensor nodes. A promising technique to extend the lifetime of the nodes is wireless energy transfer. The WSN lifetime can also be extended by exploiting the redundancy in the nodes' deployment, which allows the implementation of duty-cycling mechanisms. In this paper, the joint problem of optimal sensor node deployment and WET scheduling is investigated. Such a problem is formulated as an integer optimization whose solution is challenging due to the binary decision variables and non-linear constraints. To solve the problem, an approach based on two steps is proposed. First, the necessary condition for which the WSN is immortal is established. Based on this result, an algorithm to solve the node deployment problem is developed. Then, the optimal WET scheduling is given by a scheduling algorithm. The WSN is shown to be immortal from a networking point of view, given the optimal deployment and WET scheduling. Theoretical results show that the proposed algorithm achieves the optimal node deployment in terms of the number of deployed nodes. In the simulation, it is shown that the proposed algorithm reduces significantly the number of nodes to deploy compared to a random-based approach. The results also suggest that, under such deployment, the optimal scheduling and WET can make WSNs immortal.

  • 57.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Xiao, Ming
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Lifetime Maximization for Sensor Networks with Wireless Energy Transfer2016In: 2016 IEEE International Conference on Communications, ICC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 20-25, article id 7510602Conference paper (Refereed)
    Abstract [en]

    In Wireless Sensor Networks (WSNs), to supply energy to the sensor nodes, wireless energy transfer (WET) is a promising technique. One of the most efficient procedures to transfer energy to the sensor nodes consists in using a sharp wireless energy beam from the base station to each node at a time. A natural fundamental question is what is the lifetime ensured by WET and how to maximize the network lifetime by scheduling the transmissions of the energy beams. In this paper, such a question is addressed by posing a new lifetime maximization problem for WET enabled WSNs. The binary nature of the energy transmission process introduces a binary constraint in the optimization problem, which makes challenging the investigation of the fundamental properties of WET and the computation of the optimal solution. The sufficient condition for which the WET makes WSNs immortal is established as function of the WET parameters. When such a condition is not met, a solution algorithm to the maximum lifetime problem is proposed. The numerical results show that the lifetime achieved by the proposed algorithm increases by about 50% compared to the case without WET, for a WSN with a small to medium size number of nodes. This suggests that it is desirable to schedule WET to prolong lifetime of WSNs having small or medium network sizes.

  • 58.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Xiao, Ming
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Poster: On the Immortality of Wireless Sensor Networks by Wireless Energy Transfer - A Node Deployment Perspective2017In: Proceedings of International Conference on Embedded Wireless Systems and Networks, 2017Conference paper (Refereed)
    Abstract [en]

    The lifetime of wireless sensor networks (WSNs) can be substantially extended by transferring energy wirelessly to the sensor nodes. In this poster, a wireless energy transfer (WET) enabled WSN is presented, where a base station transfers energy wirelessly to the sensor nodes that are deployed in several regions of interest, to supply them with energy to sense and to upload data. The WSN lifetime can be extended by deploying redundant sensor nodes, which allows the implementation of duty-cycling mechanisms to reduce nodes' energy consumption. In this context, a problem on sensor node deployment naturally arises, where one needs to determine how many sensor nodes to deploy in each region such that the total number of nodes is minimized, and the WSN is immortal. The problem is formulated as an integer optimization, whose solution is challenging due to the binary decision variables and a non-linear constraint. A greedy-based algorithm is proposed to achieve the optimal solution of such deployment problem. It is argued  that such scheme can be used in monitoring systems in smart cities, such as smart buildings and water lines.

  • 59.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Gkatzikis, Lazaros
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Xiag, Ming
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Energy Efficient Sensor Activation for Water Distribution Networks Based on Compressive Sensing2015In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 33, no 12, p. 2997-3010Article in journal (Refereed)
    Abstract [en]

    The recent development of low cost wireless sensors enables novel internet-of-things (IoT) applications, such as the monitoring of water distribution networks. In such scenarios, the lifetime of the wireless sensor network (WSN) is a major concern, given that sensor node replacement is generally inconvenient and costly. In this paper, a compressive sensing-based scheduling scheme is proposed that conserves energy by activating only a small subset of sensor nodes in each timeslot to sense and transmit. Compressive sensing introduces a cardinality constraint that makes the scheduling optimization problem particularly challenging. Taking advantage of the network topology imposed by the IoT water monitoring scenario, the scheduling problem is decomposed into simpler subproblems, and a dynamic-programming-based solution method is proposed. Based on the proposed method, a solution algorithm is derived, whose complexity and energy-wise performance are investigated. The complexity of the proposed algorithm is characterized and its performance is evaluated numerically via an IoT emulator of water distribution networks. The analytical and numerical results show that the proposed algorithm outperforms state-of-the-art approaches in terms of energy consumption, network lifetime, and robustness to sensor node failures. It is argued that the derived solution approach is general and it can be potentially applied to more IoT scenarios such as WSN scheduling in smart cities and intelligent transport systems.

  • 60.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering (EES).
    Gkatzikis, Lazaros
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Xiao, Ming
    A Sensor  Scheduling  Protocol for  Energy-efficiency and  Robustness to Failures2016In: Multimedia Communications Technical Committee Communications, Vol. 11, no 3, p. 10-14Article in journal (Refereed)
  • 61.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Gkatzikis, Lazaros
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Xiao, Ming
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Energy efficient monitoring of water distribution networks via compressive sensing2015In: 2015 IEEE International Conference on Communications (ICC), IEEE conference proceedings, 2015, Vol. 2015, p. 6681-6686Conference paper (Refereed)
    Abstract [en]

    The recent development of low cost wireless sensors enables water monitoring through dense wireless sensor networks (WSN). Sensor nodes are battery powered devices, and hence their limited energy resources have to be optimally managed. The latest advancements in compressive sensing (CS) provide ample promise to increase WSNs lifetime by limiting the amount of measurements that have to be collected. Additional energy savings can be achieved through CS-based scheduling schemes that activate only a limited number of sensors to sense and transmit their measurements, whereas the rest are turned off. The ultimate objective is to maximize network lifetime without sacrificing network connectivity and monitoring performance. This problem can be approximated by an energy balancing approach that consists of multiple simpler subproblems, each of which corresponds to a specific time period. Then, the sensors that should be activated within a given period can be optimally derived through dynamic programming. The complexity of the proposed CS-based scheduling scheme is characterized and numerical evaluation reveals that it achieves comparable monitoring performance by activating only a fraction of the sensors.

  • 62.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Gkatzikis, Lazaros
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    On Maximizing Sensor Network Lifetime by Energy Balancing2018In: IEEE Transactions on Control of Network Systems, ISSN 2325-5870, Vol. 5, no 3Article in journal (Refereed)
    Abstract [en]

    Many physical systems, such as water/electricity distribution networks, are monitored by battery-powered wireless-sensor networks (WSNs). Since battery replacement of sensor nodes is generally difficult, long-term monitoring can be only achieved if the operation of the WSN nodes contributes to long WSN lifetime. Two prominent techniques to long WSN lifetime are 1) optimal sensor activation and 2) efficient data gathering and forwarding based on compressive sensing. These techniques are feasible only if the activated sensor nodes establish a connected communication network (connectivity constraint), and satisfy a compressive sensing decoding constraint (cardinality constraint). These two constraints make the problem of maximizing network lifetime via sensor node activation and compressive sensing NP-hard. To overcome this difficulty, an alternative approach that iteratively solves energy balancing problems is proposed. However, understanding whether maximizing network lifetime and energy balancing problems are aligned objectives is a fundamental open issue. The analysis reveals that the two optimization problems give different solutions, but the difference between the lifetime achieved by the energy balancing approach and the maximum lifetime is small when the initial energy at sensor nodes is significantly larger than the energy consumed for a single transmission. The lifetime achieved by energy balancing is asymptotically optimal, and that the achievable network lifetime is at least 50% of the optimum. Analysis and numerical simulations quantify the efficiency of the proposed energy balancing approach.

  • 63.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Ozcelikkale, A.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Network and Systems engineering.
    Xiao, Ming
    KTH, School of Electrical Engineering (EES), Information Science and Engineering.
    Optimal energy beamforming and data routing for immortal wireless sensor networks2017In: 2017 IEEE International Conference on Communications, ICC 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, article id 7996326Conference paper (Refereed)
    Abstract [en]

    Wireless sensor networks (WSNs) consist of energy limited sensor nodes, which limits the network lifetime. Such a lifetime can be prolonged by employing the emerging technology of wireless energy transfer (WET). In WET systems, the sensor nodes can harvest wireless energy from wireless charger, which can use energy beamforming to improve the efficiency. In this paper, a scenario where dedicated wireless chargers with multiple antennas use energy beamforming to charge sensor nodes is considered. The energy beamforming is coupled with the energy consumption of sensor nodes in terms of data routing, which is one novelty of the paper. The energy beamforming and the data routing are jointly optimized by a non-convex optimization problem. This problem is transformed into a semidefinite optimization problem, for which strong duality is proved, and thus the optimal solution exists. It is shown that the optimal solution of the semi-definite programming problem allows to derive the optimal solution of the original problem. The analytical and numerical results show that optimal energy beamforming gives two times better monitoring performance than that of WET without using energy beamforming.

  • 64.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Ozcelikkale, Ayca
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Xiao, Ming
    Towards Immortal Wireless Sensor Networks by Optimal Energy Beamforming and Data Routing2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 8, p. 5338-5352Article in journal (Refereed)
    Abstract [en]

    The lifetime of a wireless sensor network (WSN) determines how long the network can be used to monitor the area of interest. Hence, it is one of the most important performance metrics for WSN. The approaches used to prolong the lifetime can be briefly divided into two categories: reducing the energy consumption, such as designing an efficient routing, and providing extra energy, such as using wireless energy transfer (WET) to charge the nodes. Contrary to the previous line of work where only one of those two aspects is considered, we investigate these two together. In particular, we consider a scenario where dedicated wireless chargers transfer energy wirelessly to sensors. The overall goal is to maximize the minimum sampling rate of the nodes while keeping the energy consumption of each node smaller than the energy it receives. This is done by properly designing the routing of the sensors and the WET strategy of the chargers. Although such a joint routing and energy beamforming problem is non-convex, we show that it can be transformed into a semi-definite optimization problem (SDP). We then prove that the strong duality of the SDP problem holds, and hence the optimal solution of the SDP problem is attained. Accordingly, the optimal solution for the original problem is achieved by a simple transformation. We also propose a low-complexity approach based on pre-determined beamforming directions. Moreover, based on the alternating direction method of multipliers (ADMM), the distributed implementations of the proposed approaches are studied. The simulation results illustrate the significant performance improvement achieved by the proposed methods. In particular, the proposed energy beamforming scheme significantly out-performs the schemes where one does not use energy beamforming, or one does not use optimized routing. A thorough investigation of the effect of system parameters, including the number of antennas, the number of nodes, and the number of chargers, on the system performance is provided. The promising convergence behaviour of the proposed distributed approaches is illustrated.

  • 65.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Santi, Paolo
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Vasilakos, Athanasios
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    The sensable city: A survey on the deployment and management for smart city monitoringIn: IEEE Communications Surveys and Tutorials, ISSN 1553-877X, E-ISSN 1553-877XArticle in journal (Refereed)
  • 66.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Shokri-Ghadikolaei, Hossein
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Wirelessly-powered Sensor Networks: Power Allocation for Channel Estimation and Energy beamformingIn: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248Article in journal (Refereed)
    Abstract [en]

    Wirelessly-powered sensor networks (WPSNs) are becoming increasingly important to monitor many internet-of-things systems. We consider a WPSN where a multiple-antenna base station, dedicated for energy transmission, sends pilot signals to estimate the channel state information and consequently shapes the energy beams toward the sensor nodes. Given a fixed energy budget at the base station, in this paper, we investigate the novel problem of optimally allocating the power for the channel estimation and for the energy transmission. We formulate this problem for general channel estimation and beamforming schemes, which turns out to be non-convex. We provide a new solution approach and a performance analysis in terms of optimality and complexity. We also present a closed-form solution for the case where the channels are estimated based on a least square channel estimation and a maximum ratio transmit beamforming scheme. The analysis and simulations indicate a significant gain in terms of the network sensing rate, compared to the fixed power allocation, and the importance of improving the channel estimation efficiency.

  • 67.
    Du, Rong
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Fischione, Carlo
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Optimal Node Deployment and Energy Provision for Wirelessly Powered Sensor Networks2018In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 37, no 2, p. 407-423Article in journal (Refereed)
    Abstract [en]

    In a typical wirelessly powered sensor network (WPSN), wireless chargers provide energy to sensor nodes by using wireless energy transfer (WET). The chargers can greatly improve the lifetime of a WPSN using energy beamforming by a proper charging scheduling of energy beams. However, the supplied energy still may not meet the demand of the energy of the sensor nodes. This issue can be alleviated by deploying redundant sensor nodes, which not only increase the total harvested energy, but also decrease the energy consumption per node provided that an efficient  scheduling of the sleep/awake of the nodes is performed. Such a problem of joint optimal sensor deployment, WET scheduling, and node activation is posed and investigated in this paper. The problem is an integer optimization that is challenging due to the binary decision variables and non-linear constraints. Based on the analysis of the necessary condition such that the WPSN be immortal, we decouple the original problem into a node deployment problem and a charging and activation scheduling problem. Then, we propose an algorithm and prove that it achieves the optimal solution under a mild condition. The simulation results show that the proposed algorithm reduces the needed nodes to deploy by approximately 16%, compared to a random-based approach. The simulation also shows if the battery buffers are large enough, the optimality condition will be easy to meet.

  • 68. El-Sayed, H.
    et al.
    Athanasiou, George
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Evaluation of localization methods in millimeter-wave wireless systems2014In: 2014 IEEE 19th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2014, IEEE conference proceedings, 2014, p. 345-349Conference paper (Refereed)
    Abstract [en]

    Millimeter-wave communications are considered as one of the key technologies for enabling multi-gigabit wireless access and bandwidth demanding applications. An increasing number of these applications, such as smart environments, asset tracking, video surveillance, and specialized location based services, require knowledge related to the location of the wireless devices. Due to the special characteristics of millimeter-wave transmissions, such as high path loss attenuation, oxygen absorption, and antenna directivity, it is challenging to achieve accurate localization. In this overview paper, the performance of localization methods over the millimeter-wave medium is compared under realistic conditions. The prominent localization approaches based on received signal strength, time of arrival, and angle of arrival of millimeter-wave signals, are numerically evaluated by an extensive set of Monte Carlo simulations. It is suggested that localization based on angle of arrival is the most promising for millimeter-wave transmissions.

  • 69. Enyioha, Chinwendu
    et al.
    Magnusson, Sindri
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. KTH - Royal Institute of Technology.
    Heal, Kathryn
    Na, Li
    Carlo, Fischione
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering.
    Tarokh, Vahid
    On Variability of Renewable Energy and Online Power Allocation2018In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 33, no 1, p. 451-462Article in journal (Refereed)
    Abstract [en]

    As electric power system operators shift from conventional energy to renewable energy sources, power distribution systems will experience increasing fluctuations in supply. These fluctuations present the need to not only design online decentralized power allocation algorithms, but also characterize how effective they are given fast-changing consumer demand and generation. In this paper, we present an online decentralized dual descent (OD3) power allocation algorithm and determine (in the worst case) how much of observed social welfare can be explained by fluctuations in generation capacity and consumer demand. Convergence properties and performance guarantees of the OD3 algorithm are analyzed by characterizing the difference between the online decision and the optimal decision. We demonstrate validity and accuracy of the theoretical results in the paper through numerical experiments using real power generation data.

  • 70.
    Enyioha, Chinwendu
    et al.
    Harvard University.
    Sindri, Magnusson
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Heal, Kathryn
    Harvard University.
    Li, Na
    Harvard University.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Tarokh, Vahid
    Robustness Analysis for an Online Decentralized Descent Power allocation algorithm2016In: 2016 IEEE Information Theory and Applications Workshop (ITA), IEEE conference proceedings, 2016Conference paper (Refereed)
    Abstract [en]

    As independent service providers increasingly inject power (from renewable sources like wind) into the power distribution system, the power distribution system will likely experience increasingly significant fluctuations in power supply. Fluctuations in power generation, coupled with time-varying consumption of electricity on the demand side and the massive scale of power distribution networks present the need to not only design decentralized power allocation policies, but also understand how robust they are to dynamic demand and supply. In this paper, via an Online Decentralized Dual Descent (OD3) Algorithm, with communication for decentralized coordination, we design power allocation policies in a power distribution system. Based on the OD3 algorithm, we determine and characterize (in the worst case) how much of observed social welfare andprice volatility can be explained by fluctuations in consumption utilities of users and capacities of suppliers. In coordinating the power allocation, the OD3 algoritihm uses a protocol in which the users’ consumption at each time-step depends on the coordinating (price) signal, which is iteratively updated based on aggregate power consumption. Convergence properties and performance guarantees of the OD3 algorithm is analyzed by characterizing the difference between the online decision and the optimal decision. As more renewable energy sources are integrated into the power grid, the results in this paper providea framework to understand how volatility in the power systems propagate to markets. The theoretical results in the paper are validated and illustrated by numerical experiments.

  • 71. Ergen, S. C.
    et al.
    Di Marco, Piergiuseppe
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    MAC protocol engine for sensor networks2009In: GLOBECOM - IEEE Global Telecommunications Conference, 2009Conference paper (Refereed)
    Abstract [en]

    We present a novel approach for Medium Access Control (MAC) protocol design based on protocol engine. Current way of designing MAC protocols for a specific application is based on two steps: First the application specifications (such as network topology and packet generation rate), the requirements for energy consumption, delay and reliability, and the resource constraints from the underlying physical layer (such as energy consumption and data rate) are specified, and then the protocol that satisfies all these constraints is designed. Main drawback of this procedure is that we have to restart the design process for each possible application, which may be a waste of time and efforts. The goal of a MAC protocol engine is to provide a library of protocols together with their analysis such that for each new application the optimal protocol is chosen automatically among its library with optimal parameters. We illustrate the MAC engine idea by including an original analysis of IEEE 802.15.4 unslotted random access and Time Division Multiple Access (TDMA) protocols, and implementing these protocols in the software framework called SPINE, which runs on top of TinyOS and is designed for health care applications. Then we validate the analysis and demonstrate how the protocol engine chooses the optimal protocol under different application scenarios via an experimental implementation.

  • 72.
    Farhadi, Hamed
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Zaidi, Ali
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Wang, Chao
    School of Electronics and Information Engineering, Tongji University, Shanghai, China.
    Skoglund, Mikael
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Distributed Interference Alignment and Power Control for Wireless MIMO Interference Networks with Noisy Channel State Information2013In: 2013 First International Black Sea Conference on Communications and Networking (BlackSeaCom), IEEE conference proceedings, 2013, p. 23-27Conference paper (Refereed)
    Abstract [en]

    This paper considers a multi-input multi-output(MIMO) interference network in which each transmitter intendsto communicate with its dedicated receiver at a certain fixed rate. It is known that when perfect CSI is available at each terminal, the interference alignment technique can be applied to align theinterference signals at each receivers in a subspace independent of the desired signal subspace. The impact of interference canhence be eliminated. In practice, however, terminals in general can acquire only noisy CSI. Interference alignment cannot be perfectly performed to avoid interference leakage in the signal subspace. Thus, the quality of each communication link dependson the transmission power of the unintended transmitters. Tosolve this problem, we propose an iterative algorithm to performstochastic power control and transceiver design based on onlynoisy local CSI. The transceiver design is conducted based on the interference alignment concept, and the power control seeks solutions of efficiently assigning transmit powers to provide successful communications for all transmitter-receiver pairs.

  • 73.
    Fiorenzi, Marco
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Girella, Daniele
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Möller, Niels
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Arvidsson, A.
    Skog, R.
    Petersson, J.
    Karlsson, P.
    Fischione, Carlo
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Enhancing TCP over HSDPA by cross-layer signalling2007In: GLOBECOM 2007: 2007 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE, 2007, p. 5362-5366Conference paper (Refereed)
    Abstract [en]

    A comprehensive performance evaluation of a cross-layer solution to increase users' downlink data rates over HSDPA is provided. The solution consists of a proxy entity between a server and the Radio Network Controller, and cross-layer signalling from the base station to the proxy. The performance of the solution is evaluated though a detailed ns-2 simulator environment, which includes all HSDPA features, as well as some existing TCP enhancing protocols widely adopted for internet traffic over wireless links. Numerical results show that the proxy significantly increases the users' throughput, while also improving the utilization of the radio resources.

  • 74.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fast-Lipschitz Optimization With Wireless Sensor Networks Applications2011In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 56, no 10, p. 2319-2331Article in journal (Refereed)
    Abstract [en]

    Motivated by the need for fast computations in wireless sensor networks, the new F-Lipschitz optimization theory is introduced for a novel class of optimization problems. These problems are defined by simple qualifying properties specified in terms of increasing objective function and contractive constraints. It is shown that feasible F-Lipschitz problems have always a unique optimal solution that satisfies the constraints at equality. The solution is obtained quickly by asynchronous algorithms of certified convergence. F-Lipschitz optimization can be applied to both centralized and distributed optimization. Compared to traditional Lagrangian methods, which often converge linearly, the convergence time of centralized F-Lipschitz problems is at least superlinear. Distributed F-Lipschitz algorithms converge fast, as opposed to traditional Lagrangian decomposition and parallelization methods, which generally converge slowly and at the price of many message passings. In both cases, the computational complexity is much lower than traditional Lagrangian methods. Examples of application of the new optimization method are given for distributed estimation and radio power control in wireless sensor networks. The drawback of the F-Lipschitz optimization is that it might be difficult to check the qualifying properties. For more general optimization problems, it is suggested that it is convenient to have conditions ensuring that the solution satisfies the constraints at equality.

  • 75.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    F-Lipschitz Optimization2010Report (Other academic)
    Abstract [en]

    In wireless sensors networks it is common that decision variables must be optimized by algorithms that need tobe fast, simple, and robust to errors and noises, both in a centralized and in a distributed set-up. A new simple vectoroptimization theory, named the fast Lipschitz (F-Lipschitz) optimization, is introduced for a novel class of nonlinearmulti-objective optimization problems that are pervasive in wireless sensor networks. These problems are definedby qualifying properties specified in terms of increasing objective function and partially monotonic constraints. It isshown that feasible F-Lipschitz problems have always a unique Pareto optimal solution that satisfies all the constraintsat the equality, including the inequality constraints. The solution is obtained quickly by asynchronous algorithmsof certified convergence. F-Lipschitz optimization can be applied to both centralized and distributed optimization.Compared to traditional Lagrangian methods, which often converge linearly, the convergence time of centralizedF-Lipschitz algorithms is superlinear. Distributed F-Lipschitz algorithms converge fast, as opposed to traditionalLagrangian decomposition and parallelization methods, which generally converge slowly and at the price of manymessage passings. In both cases, the computational complexity is much lower than traditional Lagrangian methods.It is shown that the interference function theory, which plays a central role in distributed resource allocation ofwireless communication systems, is a particular case of F-Lipschitz optimization. It is proved that a class of convexproblems, including geometric programming problems, can be cast as F-Lipschitz problems, and thus they can besolved much more efficiently than interior point methods. Some typical optimization problems that occur on wirelesssensor networks are shown to be F-Lipschitz. For more general optimization problems, it is suggested that beforesolving them by Lagrangian methods, it is convenient having conditions ensuring that the solution satisfies part or allof the constraints at the equality. The drawback of the F-Lipschitz optimization is that it might be difficult to checkthe qualifying properties.

  • 76.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Athanasiou, George
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Santucci, F.
    Dynamic optimization of generalized least squares handover algorithms2017In: 2014 7th International Conference on Network Games, Control and Optimization, NetGCoop 2014, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 247-254, article id 7943424Conference paper (Refereed)
    Abstract [en]

    Efficient handover algorithms are essential for highly performing cellular networks. These algorithms depend on numerous parameters, whose settings must be appropriately optimized to offer a seamless connectivity. Nevertheless, such an optimization is difficult in a time varying context, unless adaptive strategies are used. In this paper, a new approach for the handover optimization is proposed. Three dynamical optimization approaches are presented, where the probability of outage and the probability of handover are considered. Since it is shown that these probabilities are difficult to compute, simple approximations of adequate accuracy are developed. A distributed optimization algorithm is then developed to maximize handover performance. Numerical results show that the proposed algorithm improves the performance of the handover considerably when compared to more traditional approaches.

  • 77.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Athanasiou, George
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Santucci, Fortunato
    Dynamic Optimization of Generalized Least Squares Handover Algorithms2014In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 13, no 3, p. 1235-1249Article in journal (Refereed)
    Abstract [en]

    Efficient handover algorithms are essential for highly performing mobile wireless communications. These algorithms depend on numerous parameters, whose settings must be appropriately optimized to offer a seamless connectivity. Nevertheless, such an optimization is difficult in a time varying context, unless adaptive strategies are used. In this paper, a new approach for the handover optimization is proposed. First, a new modeling of the handover process by a hybrid system that takes as input the handover parameters is established. Then, this hybrid system is used to pose some dynamical optimization approaches where the probability of outage and the probability of handover are considered. Since it is shown that these probabilities are difficult to compute, simple approximations of adequate accuracy are developed. Based on these approximations, a new approach to the solution of the handover optimizations is proposed. A distributed optimization algorithm is then developed to maximize handover performance. From an extensive set of results obtained by numerical computations and simulations, it is shown that the proposed algorithm improves performance of the handover considerably when compared to more traditional approaches.

  • 78.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Bonivento, A.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Sangiovanni-Vincentelli, A.
    Cooperative Diversity with Disconnection Constraints and Sleep Discipline for Power Control in Wireless Sensor Networks2006In: 2006 IEEE 63RD VEHICULAR TECHNOLOGY CONFERENCE, IEEE , 2006, p. 578-582Conference paper (Refereed)
    Abstract [en]

    We derive a power control policy for a group of sensor nodes that are monitoring a real-time application sensitive to disconnections (outages) of the communication. Specifically, we suggest that the sensor nodes perform cooperative diversity while running a sleep discipline. After the description of a detailed model of the wireless links, we propose a power minimization algorithm with a constraint expressed in terms of outage probability. Suboptimal solutions are also discussed. Numerical examples are provided for various number of nodes; wireless scenarios and nodes activities. It is argued that nodes with reduced activity show better performance.

  • 79.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Bonivento, A.
    Sangiovanni-Vincentelli, A.
    Santucci, F.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Performance Analysis of Collaborative Spatio-Temporal Processing for Wireless Sensor Networks2006In: 2006 3RD IEEE CONSUMER COMMUNICATIONS AND NETWORKING CONFERENCE, 2006, p. 325-329Conference paper (Refereed)
    Abstract [en]

    Spatio-temporal processing (STP) is a control technique to increase the quality of the received signals in wireless networks. Outage events have a strong influence not only on the performance of the physical layer, but also on routing, MAC, and application layers. In this paper, we propose an outage-based performance analysis of collaborative STP for wireless sensor networks (WSNs). After an accurate characterization of the wireless channel, we derive the outage statistics as a function of the STP coefficients, and investigate the effects of STP on the probability, average duration and rate of the outage events. Furthermore, we show that a proper control policy for the STP coefficients can be derived according to the requirements from the application and communication layers.

  • 80.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Buttissi, M.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    D'Angelo, M.
    Power and Rate Control with Outage Constraints in CDMA Wireless Networks2009In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 57, no 8, p. 2225-2229Article in journal (Refereed)
    Abstract [en]

    A radio power control strategy to achieve maximum throughput for the up-link of CDMA wireless systems with variable spreading factor is investigated. The system model includes slow and fast fading, rake receiver, and multi-access interference caused by users with heterogeneous data sources. The quality of the communication is expressed in terms of outage probability, while the throughput is defined as the sum of the users' transmit rates. The outage probability is accounted for by resorting to a lognormal approximation. A mixed integer-real optimization problem P-1, where the objective function is the throughput under outage probability constraints, is investigated. Problem P-1 is solved in two steps: firstly, we propose a modified problem P-2 to provide feasible solutions, and then the optimal solution is obtained with an efficient branch-and-bound search. Numerical results are presented and discussed to assess the validity of our approach.

  • 81.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Butussi, Matteo
    Power and rate control outage based in CDMA wireless networks under MAI and heterogeneous traffic sources2007In: 2007 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2007, p. 5856-5861Conference paper (Refereed)
    Abstract [en]

    We characterize the maximum throughput achievable for the up-link of a power-controlled WCDMA wireless system with variable spreading factor. Our system model includes multi access interference caused by users with heterogeneous data sources, and quality of service expressed in terms of outage probability. Inner loop and outer loop power control mechanisms are also explicitly taken into account. We express the system throughput as the sum of the users transmission rates, and propose a mixed integer optimization program where the objective function is the sum of the rates under outage probability constraints. Then, we solve the optimization problem proposing an efficient optimal approach based on two steps: firstly, a modified problem provides feasible solutions, and then the optimal solution is obtained with branch and bound criteria. Numerical results confirm the validity of our approach, and show how the throughput depends on the power control fluctuation, activity of the sources, and quality of service.

  • 82.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    D'Angelo, M.
    A generalized utility maximization problem with outage constraints in CDMA networks2010In: 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems, IFAC Papers Online, 2010, p. 133-138Conference paper (Refereed)
    Abstract [en]

    The problem of maximizing a utility function while limiting the outage probability below an appropriate threshold is investigated. A coded-division multi access wireless network under mixed Nakagami-lognormal fading is considered. Solving such a utility maximization problem is difficult because the problem is non-convex and non-geometric with mixed integer and real decision variables and no explicit functions of the constraints are available. In this paper, two methods to the solution of the utility maximization problem are proposed. By the first method, a simple explicit outage approximation is used and the constraint that rates are integers is relaxed yielding a standard convex programming optimization that can be solved quickly but at the price of a reduced accuracy. The second method uses a more accurate outage approximation, which allows one solving the utility maximization problem by the Lagrange duality for non-convex problems and contraction mapping theory. Numerical results show that the first method performs well for average values of the outage requirements, whereas the second one is always more accurate, but is also more computationally expensive.

  • 83.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    D'Angelo, M.
    Butussi, M.
    Utility Maximization via Power and Rate Allocation with Outage Constraints in Nakagami-Lognormal Channels2011In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 10, no 4, p. 1108-1120Article in journal (Refereed)
    Abstract [en]

    The problem of maximizing a utility function while limiting the outage probability below an appropriate threshold is investigated. A coded-division multi access wireless network under mixed Nakagami-lognormal fading is considered. Solving such a utility maximization problem is difficult because the problem is non-convex and non-geometric with mixed integer and real decision variables and no explicit functions of the constraints are available. In this paper, three methods for the solution of the utility maximization problem are proposed. By the first method, a simple explicit outage approximation is used and the constraint that rates are integers is relaxed yielding a standard convex programming optimization that can be solved quickly but at the price of a reduced accuracy. The second method uses a more accurate outage approximation, which allows one solving the utility maximization problem by the Lagrange duality for non-convex problems and contraction mapping theory. The third method is a combination of the first and the second one. Numerical results show that the first method performs well for average values of the outage requirements, whereas the second one is always more accurate, but is also more computationally expensive. Finally, the third method gives same accuracy as the second one, but has a lower computational complexity only for a small number of transmitters.

  • 84.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    De Angelis, A.
    Performance limitations of localization based on ranging, speed, and orientation2015In: IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, IEEE conference proceedings, 2015, p. 490-494Conference paper (Refereed)
    Abstract [en]

    Estimating the position of a mobile node by linear sensor fusion of ranging, speed, and orientation measurements has the potentiality to achieve high localization accuracy. Nevertheless, the design of these sensor fusion algorithms is uncertain if their fundamental limitations are unknown. Despite the substantial research focus on these sensor fusion methods, the characterization of the Cramér Rao Lower Bound (CRLB) has not yet been satisfactorily addressed. In this paper, the existence and derivation of the posterior CRLB for the linear sensor fusion of ranging, speed, and orientation measurements is investigated. The major difficulty in the analysis is that ranging and orientation are not linearly related to the position, which makes it hard to derive the posterior CRLB. This difficulty is overcome by introducing the concept of posterior CRLB in the Cauchy principal value sense and deriving explicit upper and lower bounds to the posteriori Fisher information matrix. Numerical simulation results are provided for both the parametric CRLB and the posterior CRLB, comparing some widely-used methods from the literature to the derived bound. It is shown that many existing methods based on Kalman filtering may be far from the the fundamental limitations given by the CRLB.

  • 85.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ergen, S. Coleri
    Park, Pan Gun
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sangiovanni-Vincentelli, A.
    Medium Access Control Analytical Modeling and Optimization in Unslotted IEEE 802.15.4 Wireless Sensor Networks2009In: 2009 6TH ANNUAL IEEE COMMUNICATIONS SOCIETY CONFERENCE ON SENSOR, MESH AND AD HOC COMMUNICATIONS AND NETWORKS (SECON 2009), NEW YORK: IEEE , 2009, p. 440-448Conference paper (Refereed)
    Abstract [en]

    Accurate analytical expressions of delay and packet reception probabilities, and energy consumption of duty-cycled wireless sensor networks with random medium access control (MAC) are instrumental for the efficient design and optimization of these resource-constrained networks. Given a clustered network topology with unslotted IEEE 802.15.4 and preamble sampling MAC, a novel approach to the modeling of the delay, reliability, and energy consumption is proposed. The challenging part in such a modeling is the random MAC and sleep policy of the receivers, which prevents to establish the exact time of data packet transmission. The analysis gives expressions as function of sleep time, listening time, traffic rate and MAC parameters. The analytical results are then used to optimize the duty cycle of the nodes and MAC protocol parameters. The approach provides a significant reduction of the energy consumption compared to existing solutions in the literature. Monte Carlo simulations by ns2 assess the validity of the analysis.

  • 86.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Graziosi, Fabio
    Santucci, Fortunato
    Approximation for a SUM of ON-OFF lognormal processes with wireless applications2007In: IEEE TRANSACTIONS ON COMMUNICATIONS, 2007, Vol. 55, no 10, p. 1984-1993Conference paper (Refereed)
    Abstract [en]

    In this paper, a lognormal approximation is proposed for the sum of lognormal processes weighted by binary processes. The analytical approach moves from the method early proposed by Wilkinson for approximating first-order statistics of a sum of lognormal components, and extends to incorporate second-order statistics and the presence of both time-correlated random binary weights and cross-correlated lognormal components in moments' matching. Since the sum of weighted lognormal processes models the signal-to-interference-plus-noise ratio (SINR) of wireless systems, the method can be applied to evaluate in an effective and accurate way the outage occurrence rate and outage duration for different wireless systems of practical interest. In a frequency-reuse-based cellular system, the method is applied for various propagation scenarios, characterized by different shadowing correlation decay distances and correlations among shadowing components. A further case of relevant interest is related to power-controlled wideband wireless systems, where the random weights are binary random variables denoting the activity status of each interfering source. Finally, simulation results are used to confirm the validity of the analysis.

  • 87.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Jakobsson, Martin
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Optimality of Radio Power Control Via Fast-Lipschitz Optimization2016In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 64, no 6, p. 2589-2601Article in journal (Refereed)
    Abstract [en]

    In wireless network resource allocation, the radio power control problems are often solved by fixed point algorithms. Although these algorithms give feasible problem solutions, such solutions often lack notion of problem optimality. This paper reconsiders well-known fixed-point algorithms, such as those with standard and type-II standard interference functions, and investigates the conditions under which they give optimal solutions. The optimality is established by the recently proposed fast-Lipschitz optimization framework. To apply such a framework, the analysis is performed by a logarithmic transformation of variables that gives tractable fast-Lipschitz problems. It is shown how the logarithmic problem constraints are contractive by the standard or type-II standard assumptions on the power control problem, and how sets of cost functions fulfill the fast-Lipschitz qualifying conditions. The analysis on nonmonotonic interference function allows establishing a new qualifying condition for fast-Lipschitz optimization. The results are illustrated by considering power control problems with standard interference function, problems with type-II standard interference functions, and a case of subhomogeneous power control problems. Given the generality of fast-Lipschitz optimization compared to traditional methods for resource allocation, it is concluded that such an optimization may help to determine the optimality of many resource allocation problems in wireless networks.

  • 88.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Graziosi, F.
    Santucci, F.
    Distributed cooperative processing and control over wireless sensor networks2006In: IWCMC 2006 - Proceedings of the 2006 International Wireless Communications and Mobile Computing Conference, 2006, Vol. 2006, p. 1311-1316Conference paper (Other academic)
    Abstract [en]

    An overview of some recent advances in distributed information processing for control over wireless sensor networks is presented in this paper. Firstly, a taxonomy of fundamental control and communication schemes for these systems is introduced. Next, specific research issues are proposed and discussed with three prominent examples on distributed source coding with packet aggregation, distributed cooperative diversity and distributed cooperative localization. In regard to these examples, it is argued about some open research problems and suggestions for further investigations on joint control and communication design for distributed processing and control over wireless sensor networks.

  • 89.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Jönsson, Ulf
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
    Fast-Lipschitz optimization with wireless sensor networks applications2011In: Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN'11, 2011, p. 378-389Conference paper (Refereed)
    Abstract [en]

    Motivated by the need for fast computations demanded by wireless sensor networks, the new F-Lipschitz optimization theory is introduced for a novel class of optimization problems. These problems are defined by simple qualifying properties specified in terms of increasing objective function and contractive constraints. It is shown that feasible F-Lipschitz problems have always a unique optimal solution that satisfies the constraints at equality. The solution is obtained quickly by asynchronous algorithms of certified convergence. F-Lipschitz optimization can be applied to both centralized and distributed optimization. Compared to traditional Lagrangian methods, which often converge linearly, the convergence time of centralized F-Lipschitz problems is at least superlinear. Distributed F-Lipschitz algorithms converge fast, as opposed to traditional La-grangian decomposition and parallelization methods, which generally converge slowly and at the price of many message passings. In both cases, the computational complexity is much lower than traditional Lagrangian methods. Examples of application of the new optimization method are given for distributed detection and radio power control in wireless sensor networks. The drawback of the F-Lipschitz optimization is that it might be difficult to check the qualifying properties. For more general optimization problems, it is suggested that it is convenient to have conditions ensuring that the solution satisfies the constraints at equality.

  • 90.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Möller, Niels
    Graziosi, F.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Santucci, F.
    Analysis of TCP/IP over WCDMA Wireless Systems under Power Control, MAI and Link Level Error Recovery2005In: Proceedings International Workshop on Convergent Technologies (IWCT), 2005Conference paper (Refereed)
  • 91.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Park, P.
    Ergen, S. Coleri
    Analysis and optimization of duty-cycle in preamble-based random access networks2013In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 19, no 7, p. 1691-1707Article in journal (Refereed)
    Abstract [en]

    Duty-cycling has been proposed as an effective mechanism for reducing the energy consumption in wireless sensor networks (WSNs). Asynchronous duty-cycle protocols where the receiver wakes up periodically to check whether there is a transmission and the sender transmits preambles to check if the receiver is awake are widely used in WSNs due to the elimination of complex control mechanisms for topology discovery and synchronization. However, the intrinsic simplicity of the asynchronous mechanism has the drawback of smaller energy saving potential that requires the optimization of the duty cycle parameters. In this paper, we propose a novel method for the optimization of the duty-cycle parameters in preamble-based random access networks based on the accurate modeling of delay, reliability and energy consumption as a function of listen time, sleep time, traffic rate and medium access control (MAC) protocol parameters. The challenges for modeling are the random access MAC and the sleep policy of the receivers, which make it impossible to determine the exact time of data packet transmissions, and thus difficult to investigate the performance indicators given by the delay, reliability and energy consumption to successfully receive packets. An analysis of these indicators is developed as a function of the relevant parameters of the network and it is used in the minimization of the energy consumption subject to delay and reliability requirements. The optimization provides significant reduction of the energy consumption compared to the previously proposed protocols in the literature.

  • 92.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Park, Pan Gun
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Di Marco, Piergiuseppe
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Design principles of wireless sensor networks protocols for control applications2011In: Wireless Networking Based Control / [ed] Sudip K. Mazumder, Springer-Verlag New York, 2011, p. 203-238Chapter in book (Refereed)
    Abstract [en]

    Control applications over wireless sensor networks (WSNs) require timely, reliable, and energy efficient communications. This is challenging because reliability and latency of delivered packets and energy are at odds, and resource constrained nodes support only simple algorithms. In this chapter, a new system-level design approach for protocols supporting control applications over WSNs is proposed. The approach suggests a joint optimization, or co-design, of the control specifications, networking layer, the medium access control layer, and physical layer. The protocol parameters are adapted by an optimization problem whose objective function is the network energy consumption, and the constraints are the reliability and latency of the packets as requested by the control application. The design method aims at the definition of simple algorithms that are easily implemented on resource constrained sensor nodes. These algorithms allow the network to meet the reliability and latency required by the control application while minimizing for energy consumption. The design method is illustrated by two protocols: Breath and TREnD, which are implemented on a test-bed and compared to some existing solutions. Experimental results show good performance of the protocols based on this design methodology in terms of reliability, latency, low duty cycle, and load balancing for both static and time-varying scenarios. It is concluded that a system-level design is the essential paradigm to exploit the complex interaction among the layers of the protocol stack and reach a maximum WSN efficiency.

  • 93.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Park, Pangun
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Ergen, S.C.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sangiovanni-Vincentelli, A.
    Analytical modeling and optimization of duty-cycles in preamble-based IEEE 802.15.4 wireless sensor networks2009In: IEEE/ACM Transactions on Networking, ISSN 1063-6692, E-ISSN 1558-2566Article in journal (Refereed)
  • 94.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Speranzon, Alberto
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sangiovanni-Vincentelli, Alberto
    Peer-to-peer Estimation over Wireless Sensor Networks via Lipschitz Optimization2009In: 2009 INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN 2009), NEW YORK: IEEE , 2009, p. 241-252Conference paper (Refereed)
    Abstract [en]

    Motivated by a peer-to-peer estimation algorithm in which adaptive weights are optimized to minimize the estimation error variance, we formulate and solve a novel non-convex Lipschitz optimization problem that guarantees global stability of a large class of peer-to-peer consensus-based algorithms for wireless sensor network. Because of packet. losses, the solution of this optimization problem cannot be achieved efficiently with either traditional centralized methods or distributed Lagrangian message passing. The prove that the optimal solution can be obtained by solving a set of nonlinear equations. A fast distributed algorithm, which requires only local computations, is presented for solving these equations. Analysis and computer simulations illustrate the algorithm and its application to various network topologies.

  • 95.
    Fischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Tennina, S.
    Santucci, F.
    Graziosi, F.
    Reliability and Efficiency Analysis of Distributed Source Coding in Wireless Sensor Networks2009In: 2009 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2009, p. 324-329Conference paper (Refereed)
    Abstract [en]

    We propose a comprehensive theoretical framework to evaluate reliability and energy consumption of distributed source coding (DSC) in wireless sensor networks (WSNs) applications. Energy efficiency and the amount of measurements that can be successfully decoded in tree-based WSNs employing DSC in the presence of different coding topologies and packet aggregation schemes (PA) are accurately characterized. The system model includes a realistic network architecture with multi-hop communication, automatic repeat request protocol (ARQ), packet losses due to channel impairments and collisions, and correlation properties of the sensed phenomena. Four DSC topologies and three alternatives of PA are considered. The analysis is carried out by evaluating the expressions of reliability of DSC in terms of probability of measurements that cannot be decoded (loss factor), and the efficiency in terms of average energy consumption of the network. Numerical results show that the best choice of DSC topology and packet aggregation depends highly on the network parameters and source characteristics. Therefore, the analysis developed in this paper can be used as an effective mean to optimize network operations.

  • 96.
    Flischione, Carlo
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Sangiovanni-Vincentelli, A.
    Ares, Benigno Zurita
    KTH.
    Minimum Energy Coding in CDMA Wireless Sensor Networks2009In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 8, no 2, p. 985-994Article in journal (Refereed)
    Abstract [en]

    A theoretical framework is proposed for accurate comparison of minimum energy coding in Coded Division Multiple Access (CDMA) Wireless Sensor Networks (WSNs). Energy consumption and reliability are analyzed for two coding schemes: Minimum Energy coding (ME), and Modified Minimum Energy coding (MME). A detailed model of consumed energy is described as function of the coding, radio transmit power, the characteristics of the transceivers, and the dynamics of the wireless channel. Since CDMA is strongly limited by multi-access interference, the system model includes all the relevant characteristics of wireless propagation. A distributed and asynchronous algorithm, which minimizes the total energy consumption by controlling the radio power, is developed. Numerical results are presented to validate the theoretical analysis and show under which conditions MME outperforms ME with respect to energy consumption and bit error rate. It is concluded that MME is more energy efficient than ME only for short codewords.

  • 97.
    Flärdh, Oscar
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Karl H.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Johansson, Mikael
    KTH, School of Electrical Engineering (EES), Automatic Control.
    A Control Framework for Online Error Control Adaptation in Networked Applications2006In: Proceedings of IEEE Second International Symposium on Control, Communications, and Signal Processing, 2006Conference paper (Refereed)
    Abstract [en]

    For many real-time applications running over packet-switched networks, it is important to maintain delivered data quality using a limited amount of network resources. It is therefore natural to employ cost functions that allow online trade-off between the experienced application quality and the resource usage. However, minimizing such cost functions requires perfect knowledge of the network state at the transmission side, while, in general, such information is only partially available. In this paper, we introduce a new adaptive error correction algorithm that optimizes the amount of redundancy based on the available information from the application and the network. An extremum-seeking control algorithm is employed to deal with the high level of uncertainty in the network models. The validity of our approach is illustrated in simulations with varying network loads and loss correlation.

  • 98.
    Flärdh, Oscar
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Johansson, Mikael
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Analysis of a simple feedback scheme for error correction over a lossy network2007In: 2007 IEEE INTERNATIONAL CONFERENCE ON NETWORKING, SENSING, AND CONTROL, IEEE , 2007, p. 261-266Conference paper (Refereed)
    Abstract [en]

    A control theoretic analysis of a simple error correction scheme for lossy packet-switched networks is presented. Based on feedback information from the error correction process in the receiver, the sender adjusts the amount of redundancy using a so called extremum-seeking controller, which do not rely on any accurate model of the network loss process. The closed-loop system is shown to converge to a limit cycle in a neighborhood of the optimal redundancy. The result are validated using packet-based simulations with data from wireless sensor network experiments.

  • 99.
    Gerami, Majid
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Xiao, Ming
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Decentralized minimum-cost repair for distributed storage systems2013In: Communications (ICC), 2013 IEEE International Conference on, IEEE conference proceedings, 2013, p. 1910-1914Conference paper (Refereed)
    Abstract [en]

    There have been emerging lots of applications for distributed storage systems e.g., those in wireless sensor networks or cloud storage. Since storage nodes in wireless sensor networks have limited battery, it is valuable to find a repair scheme with optimal transmission costs (e.g., energy). The optimal-cost repair has been recently investigated in a centralized way. However a centralized control mechanism may not be available or is very expensive. For the scenarios, it is interesting to study optimal-cost repair in a decentralized setup. We formulate the optimal-cost repair as convex optimization problems for the network with convex transmission costs. Then we use primal and dual decomposition approaches to decouple the problem into subproblems to be solved locally. Thus, each surviving node, collaborating with other nodes, can minimize its transmission cost such that the global cost is minimized. We further study the optimality and convergence of the algorithms. Finally, we discuss the code construction and determine the field size for finding feasible network codes in our approaches.

  • 100.
    Gerami, Majid
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Xiao, Ming
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Li, Jun
    KTH, School of Electrical Engineering (EES).
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Lin, Z.
    Repair for distributed storage systems with packet erasure channels and dedicated nodes for repair2016In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 64, no 4, p. 1367-1383, article id 7422022Article in journal (Refereed)
    Abstract [en]

    We study the repair problem in distributed storage systems where storage nodes are connected through packet erasure channels and some nodes are dedicated to repair [termed as dedicated-for-repair (DR) storage nodes]. We first investigate the minimum required repair-bandwidth in an asymptotic setup, in which the stored file is assumed to have an infinite size. The result shows that the asymptotic repair-bandwidth over packet erasure channels with a fixed erasure probability has a closed-form relation to the repair-bandwidth in lossless networks. Next, we show the benefits of DR storage nodes in reducing the repair bandwidth, and then we derive the necessary minimal storage space of DR storage nodes. Finally, we study the repair in a nonasymptotic setup, where the stored file size is finite. We study the minimum practical-repair-bandwidth, i.e., the repair-bandwidth for achieving a given probability of successful repair. A combinatorial optimization problem is formulated to provide the optimal practical-repair-bandwidth for a given packet erasure probability. We show the gain of our proposed approaches in reducing the repair-bandwidth.

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