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Zeng, M., Du, R., Fodor, V. & Fischione, C. (2019). Computation Rate Maximization for Wireless Powered Mobile Edge Computing with NOMA. In: Proceedings 20th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM 2019): . Paper presented at 20th IEEE International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM), Washington, DC, JUN 10-12, 2019. IEEE
Open this publication in new window or tab >>Computation Rate Maximization for Wireless Powered Mobile Edge Computing with NOMA
2019 (English)In: Proceedings 20th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (IEEE WoWMoM 2019), IEEE , 2019Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we consider a mobile edge computing (MEC) network, that is wirelessly powered. Each user harvests wireless energy and follows a binary computation offloading policy, i.e., it either executes the task locally or offloads it to the MEC as a whole. For the offloading users, non-orthogonal multiple access (NOMA) is adopted for information transmission. We consider rate-adaptive computational tasks and aim at maximizing the sum computation rate of all users by jointly optimizing the individual computing mode selection (local computing or offloading), the time allocations for energy transfer and for information transmission, together with the local computing speed or the transmission power level. The major difficulty of the rate maximization problem lies in the combinatorial nature of the multiuser computing mode selection and its involved coupling with the time allocation. We also study the case where the offloading users adopt time division multiple access (TDMA) as a benchmark, and derive the optimal time sharing among the users. We show that the maximum achievable rate is the same for the TDMA and the NOMA system, and in the case of NOMA it is independent from the decoding order, which can be exploited to improve system fairness. To maximize the sum computation rate, for the mode selection we propose a greedy solution based on the wireless channel gains, combined with the optimal allocation of energy transfer time. Numerical results show that the proposed solution maximizes the computation rate in homogeneous networks, and binary offloading leads to significant gains. Moreover, NOMA increases the fairness of rate distribution among the users significantly, when compared with TDMA.

Place, publisher, year, edition, pages
IEEE, 2019
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-264864 (URN)10.1109/WoWMoM.2019.8792997 (DOI)000494803500029 ()2-s2.0-85071470115 (Scopus ID)978-1-7281-0270-2 (ISBN)978-1-7281-0271-9 (ISBN)
Conference
20th IEEE International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM), Washington, DC, JUN 10-12, 2019
Note

QC 20191217

Available from: 2019-12-17 Created: 2019-12-17 Last updated: 2020-01-03Bibliographically approved
Du, R., Gkatzikis, L., Fischione, C. & Xiao, M. (2018). On Maximizing Sensor Network Lifetime by Energy Balancing. IEEE Transactions on Control of Network Systems, 5(3)
Open this publication in new window or tab >>On Maximizing Sensor Network Lifetime by Energy Balancing
2018 (English)In: IEEE Transactions on Control of Network Systems, ISSN 2325-5870, Vol. 5, no 3Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-185313 (URN)10.1109/TCNS.2017.2696363 (DOI)000445357100035 ()2-s2.0-85053762086 (Scopus ID)
Note

QC 20160420

Available from: 2016-04-15 Created: 2016-04-15 Last updated: 2018-10-08Bibliographically approved
Du, R., Xiao, M. & Fischione, C. (2018). Optimal Node Deployment and Energy Provision for Wirelessly Powered Sensor Networks. IEEE Journal on Selected Areas in Communications, 37(2), 407-423
Open this publication in new window or tab >>Optimal Node Deployment and Energy Provision for Wirelessly Powered Sensor Networks
2018 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 37, no 2, p. 407-423Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
IEEE Press, 2018
National Category
Communication Systems
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-235224 (URN)10.1109/JSAC.2018.2872380 (DOI)2-s2.0-85054262790 (Scopus ID)
Note

QC 20180919

Available from: 2018-09-18 Created: 2018-09-18 Last updated: 2019-02-22Bibliographically approved
Du, R., Ozcelikkale, A., Fischione, C. & Xiao, M. (2018). Towards Immortal Wireless Sensor Networks by Optimal Energy Beamforming and Data Routing. IEEE Transactions on Wireless Communications, 17(8), 5338-5352
Open this publication in new window or tab >>Towards Immortal Wireless Sensor Networks by Optimal Energy Beamforming and Data Routing
2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 8, p. 5338-5352Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
IEEE Communications Society, 2018
National Category
Communication Systems Embedded Systems
Identifiers
urn:nbn:se:kth:diva-233453 (URN)10.1109/TWC.2018.2842192 (DOI)000441933900028 ()2-s2.0-85048499146 (Scopus ID)
Note

QC 20180820

Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2018-09-21Bibliographically approved
Du, R., Fischione, C. & Xiao, M. (2016). Flowing with the water: On optimal monitoring of water distribution networks by mobile sensors. In: : . Paper presented at International Conference on Computer Communications, 10-15 April 2016,San Fransisco, USA.
Open this publication in new window or tab >>Flowing with the water: On optimal monitoring of water distribution networks by mobile sensors
2016 (English)Conference paper, Published paper (Refereed)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-185312 (URN)000390154400151 ()2-s2.0-84983247016 (Scopus ID)
Conference
International Conference on Computer Communications, 10-15 April 2016,San Fransisco, USA
Note

QC 20160420

Available from: 2016-04-15 Created: 2016-04-15 Last updated: 2017-01-16Bibliographically approved
Du, R., Fischione, C. & Xiao, M. (2016). Lifetime Maximization for Sensor Networks with Wireless Energy Transfer. In: 2016 IEEE International Conference on Communications, ICC 2016: . Paper presented at 2016 IEEE International Conference on Communications, ICC 2016, Kuala Lumpur, Malaysia, 22 May 2016 through 27 May 2016 (pp. 20-25). Institute of Electrical and Electronics Engineers (IEEE), Article ID 7510602.
Open this publication in new window or tab >>Lifetime Maximization for Sensor Networks with Wireless Energy Transfer
2016 (English)In: 2016 IEEE International Conference on Communications, ICC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 20-25, article id 7510602Conference paper, Published 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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Keywords
Bins, Biographies, Energy transfer, Inductive power transmission, Optimization, Sensor nodes: Binary constraints, Energy transmission, Fundamental properties, Lifetime maximization, Optimization problems, Solution algorithms, Wireless energy transfers, Wireless sensor network (WSNs)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-188866 (URN)10.1109/ICC.2016.7510602 (DOI)000390993200004 ()2-s2.0-84981299186 (Scopus ID)978-1-4799-6664-6 (ISBN)
Conference
2016 IEEE International Conference on Communications, ICC 2016, Kuala Lumpur, Malaysia, 22 May 2016 through 27 May 2016
Note

QC 20170131

Available from: 2016-06-20 Created: 2016-06-20 Last updated: 2017-01-31Bibliographically approved
Rong, D. (2016). Wireless Sensor Networks in Smart Cities: The Monitoring of Water Distribution Networks Case. (Licentiate dissertation). KTH Royal Institute of Technology
Open this publication in new window or tab >>Wireless Sensor Networks in Smart Cities: The Monitoring of Water Distribution Networks Case
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The development of wireless sensor networks (WSNs) is making it possible to monitor our cities. Due to the small size of the sensor nodes, and their capabilities of transmitting data remotely, they can be deployed at locations that are not easy or impossible to access, such as the pipelines of water distribution networks (WDNs), which plays an important role in protecting environment and securing public health.

  The design of WSNs for WDNs faces major challenges. Generally, WSNs are resource-limited because most of the sensor nodes are battery powered. Thus, their resource allocation has to be carefully controlled. The thesis considers two prominent problems that occur when designing WSNs for WDNs: scheduling the sensing of the nodes of static WSNs, and sensor placement for mobile WSNs. These studies are reported in the thesis from three published or submitted papers. In the first paper, the scheduling of sleep/sensing for each sensor node is considered to maximize the whole WSNs lifetime while guaranteeing a monitoring performance constraint. The problem is transformed into an energy balancing problem, and solved by a dynamic programming based algorithm. It is proved that this algorithm finds one of the optimal solutions for the energy balancing problem. In the second paper, the question of how the energy balancing problem approximates the original scheduling problem is addressed. It is shown that even though these two problems are not equivalent, the gap of them is small enough. Thus, the proposed algorithm for the energy balancing problem can find a good approximation solution for the original scheduling problem. The second part of the thesis considers the use of mobile sensor nodes. Here, the limited resource is the number of available such mobile nodes. To maximize the monitoring coverage in terms of population, an optimization problem for determining the releasing locations for the mobile sensor nodes is formulated. An approximate solution algorithm based on submodular maximization is proposed and its performance is investigated. Beside WDNs, WSN applications for smart cities share a common characteristic: the area to monitor usually has a network structure. Therefore, the studies of this thesis can be potentially generalized for several IoT scenarios.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2016. p. 21
Series
TRITA-EE, ISSN 1653-5146 ; 2016:60
Keywords
Integer Programming, Nonconvex Optimization, Network Lifetime, Dynamic
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-185453 (URN)978-91-7595-964-1 (ISBN)
Presentation
2016-05-10, Q2, OSQULDAS VÄG 10, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20160419

Available from: 2016-04-20 Created: 2016-04-19 Last updated: 2020-01-07Bibliographically approved
Du, R., Chen, C., Yang, B., Lu, N., Guan, X. & Xuemin, S. (2015). Effective Urban Traffic Monitoring by Vehicular Sensor Networks. IEEE Transactions on Vehicular Technology, 64(1), 273-286
Open this publication in new window or tab >>Effective Urban Traffic Monitoring by Vehicular Sensor Networks
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2015 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 64, no 1, p. 273-286Article in journal (Refereed) Published
Abstract [en]

Traffic monitoring in urban transportation systems can be carried out based on vehicular sensor networks. Probe vehicles (PVs), such as taxis and buses, and floating cars (FCs), such as patrol cars for surveillance, can act as mobile sensors for sensing the urban traffic and send the reports to a traffic-monitoring center (TMC) for traffic estimation. In the TMC, sensing reports are aggregated to form a traffic matrix, which is used to extract traffic information. Since the sensing vehicles cannot cover all the roads all the time, the TMC needs to estimate the unsampled data in the traffic matrix. As this matrix can be approximated to be of low rank, matrix completion (MC) is an effective method to estimate the unsampled data. However, our previous analysis on the real traces of taxis in Shanghai reveals that MC methods do not work well due to the uneven samples of PVs, which is common in urban traffic. To exploit the intrinsic relationship between the unevenness of samples and traffic estimation error, we study the temporal and spatial entropies of samples and successfully define the important criterion, i.e., average entropy of the sampling process. A new sampling rule based on this relationship is proposed to improve the performance of estimation and monitoring.With the sampling rule, two new patrol algorithms are introduced to plan the paths of controllable FCs to proactively participate in trafficmonitoring. By utilizing the patrol algorithms for real-data-set analysis, the estimation error reduces from 35% to about 10%, compared with the random patrol or interpolation method in traffic estimation. Both the validity of the exploited relationship and the effectiveness of the proposed patrol control algorithms are demonstrated.

Place, publisher, year, edition, pages
IEEE Press, 2015
Keywords
Matrix completion (MC), patrol control, traffic sensing, vehicular sensor network (VSN)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-165843 (URN)10.1109/TVT.2014.2321010 (DOI)000348054000024 ()2-s2.0-84921409677 (Scopus ID)
Note

QC 20150430

Available from: 2015-04-29 Created: 2015-04-29 Last updated: 2019-10-02Bibliographically approved
Du, R., Gkatzikis, L., Fischione, C. & Xiao, M. (2015). Energy efficient monitoring of water distribution networks via compressive sensing. In: 2015 IEEE International Conference on Communications (ICC): . Paper presented at IEEE International Conference on Communications, ICC 2015, London, United Kingdom, 8 June 2015 through 12 June 2015 (pp. 6681-6686). IEEE conference proceedings, 2015
Open this publication in new window or tab >>Energy efficient monitoring of water distribution networks via compressive sensing
2015 (English)In: 2015 IEEE International Conference on Communications (ICC), IEEE conference proceedings, 2015, Vol. 2015, p. 6681-6686Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015
Series
IEEE International Conference on Communications, ISSN 1550-3607
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-165840 (URN)10.1109/ICC.2015.7249390 (DOI)000371708106148 ()2-s2.0-84953790048 (Scopus ID)978-1-4673-6432-4 (ISBN)
Conference
IEEE International Conference on Communications, ICC 2015, London, United Kingdom, 8 June 2015 through 12 June 2015
Note

QC 20151104

Available from: 2015-04-29 Created: 2015-04-29 Last updated: 2016-04-21Bibliographically approved
Du, R., Gkatzikis, L., Fischione, C. & Xiag, M. (2015). Energy Efficient Sensor Activation for Water Distribution Networks Based on Compressive Sensing. IEEE Journal on Selected Areas in Communications, 33(12), 2997-3010
Open this publication in new window or tab >>Energy Efficient Sensor Activation for Water Distribution Networks Based on Compressive Sensing
2015 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 33, no 12, p. 2997-3010Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
IEEE, 2015
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-178154 (URN)10.1109/JSAC.2015.2481199 (DOI)000365223600040 ()2-s2.0-84960131576 (Scopus ID)
Funder
Wireless@kth
Note

QC 20151215

Available from: 2015-12-07 Created: 2015-12-07 Last updated: 2017-12-01Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-1934-9208

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