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  • Presentation: 2020-03-06 10:00 Sal B, Kista
    Masoudi, Meysam
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Energy and Delay-aware Communication and Computation in Wireless Networks2020Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Power conservation has become a severe issue in devices since battery capability advancement is not keeping pace with the swift development of other technologies such as processing technologies. This issue becomes critical when both the number of resource-intensive applications and the number of connected devices are rapidly growing. The former results in an increase in power consumption per device, and the latter causes an increase in the total power consumption of devices. Mobile edge computing (MEC) and low power wide area networks (LPWANs) are raised as two important research areas in wireless networks, which can assist devices to save power. On the one hand, devices are being considered as a platform to run resource-intensive applications while they have limited resources such as battery and processing capabilities. On the other hand, LPWANs raised as an important enabler for massive IoT (Internet of Things) to provide long-range and reliable connectivity for low power devices. The scope of this thesis spans over these two main research areas: (1) MEC, where devices can use radio resources to offload their processing tasks to the cloud to save energy. (2) LPWAN, with grant-free radio access where devices from different technology transmit their packets without any handshaking process.

    In particular, we consider a MEC network, where the processing resources are distributed in the proximity of the users. Hence, devices can save energy by transmitting the data to be processed to the edge cloud provided that the delay requirement is met and transmission power consumption is less than the local processing power consumption. This thesis addresses the question of whether to offload or not to minimize the uplink power consumption in a multi-cell multi-user MEC network. We consider the maximum acceptable delay as the QoS metric to be satisfied in our system. We formulate the problem as a mixed-integer nonlinear problem, which is converted into a convex form using D.C. approximation. To solve the converted optimization problem, we have proposed centralized and distributed algorithms for joint power allocation and channel assignment together with decision-making on job offloading. Our results show that there exists a region in which offloading can save power at mobile devices and increases the battery lifetime.

    Another focus of this thesis is on LPWANs, which are becoming more and more popular, due to the limited battery capacity and the ever-increasing need for durable battery lifetime for IoT networks. Most studies evaluate the system performance assuming single radio access technology deployment. In this thesis, we study the impact of coexisting competing radio access technologies on the system performance. We consider K technologies, defined by time and frequency activity factors, bandwidth, and power, which share a set of radio resources. Leveraging tools from stochastic geometry, we derive closed-form expressions for the successful transmission probability, expected battery lifetime, experienced delay, and expected number of retransmissions. Our analytical model, which is validated by simulation results, provides a tool to evaluate the coexistence scenarios and analyze how the introduction of a new coexisting technology may degrade the system performance in terms of success probability, delay, and battery lifetime. We further investigate the interplay between traffic load, the density of access points, and reliability/delay of communications, and examine the bounds beyond which, mean delay becomes infinite.

  • Presentation: 2020-03-13 10:00 F3, Stockholm
    Gouveia Fonseca, Joana Filipa
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Cooperative Multi-Vehicle Circumnavigation and Tracking of a Mobile Target2020Licentiate thesis, monograph (Other academic)
    Abstract [en]

    A multi-vehicle system is composed of interconnected vehicles coordinated to complete a certain task. When controlling such systems, the aim is to obtain a coordinated behaviour through local interactions among vehicles and the surrounding environment.One motivating application is the monitoring of algal blooms; this phenomenon occurs frequently and has a substantial negative effect on the environment such as large-scale mortality of fish. In this thesis, we investigate control of multiple unmanned surface vehicles (USVs) for mobile target circumnavigation and tracking, where the target can be an algal bloom area.A protocol based on local measurements provided by the vehicles is developed to estimate the target's location and shape.Then a control strategy is derived that brings the vehicle system to the target while forming a regular polygon.

    More precisely, we first consider the problem of tracking a mobile target while circumnavigating it with multiple USVs. A satellite image indicates the initial location of the target, which is supposed to have an irregular dynamic shape well approximated by a circle with moving center and varying radius. Each USV is capable of measuring its distance to the boundary of the target and to its center. We design an adaptive protocol to estimate the circle's parameters based on the local measurements. A control protocol then brings the vehicles towards the target boundary as well as spreads them equidistantly along the boundary. The protocols are proved to converge to the desired state. Simulated examples illustrate the performance of the closed-loop system.

    Secondly, we assume that the vehicles can only measure the distance to the boundary of the target and not to its center. We propose a decentralised least-squares method for target estimation suitable for circular targets. Convergence proofs are given for also this case. An example using simulated algal bloom data shows that the method works well under realistic settings.

    Finally, we investigate how to extend our protocols to a quite general irregular mobile target. In this case, each vehicle communicates only with its two nearest neighbors and estimates the curvature of the target boundary using their collective measurements. We validate the performance of the protocol under various settings and target shapes through a numerical study.