Efficient Information Aggregation Strategies for Distributed Control and Signal Processing

This thesis is concerned with distributed control and coordination of networks consisting of multiple, potentially mobile, agents. This is motivated mainly by the emergence of large scale networks characterized by the lack of centralized access to information and time-varying connectivity. Control and optimization algorithms deployed in such networks should be completely distributed, relying only on local observations and information, and robust against unexpected changes in topology such as link failures. We will describe protocols to solve certain control and signal processing problems in this setting. We will demonstrate that a key challenge for such systems is the problem of computing averages in a decentralized way. Namely, we will show that a number of distributed control and signal processing problems can be solved straightforwardly if solutions to the averaging problem are available. The rest of the thesis will be concerned with algorithms for the averaging problem and its generalizations. We will (i) derive the fastest known averaging algorithms in a variety of settings and subject to a variety of communication and storage constraints (ii) prove a lower bound identifying a fundamental barrier for averaging algorithms (iii) propose a new model for distributed function computation which reflects the constraints facing many large-scale networks, and nearly characterize the general class of functions which can be computed in this model.Comment: Ph.D. thesis, Department of Electrical Engineering and Computer Science, MIT, September 201

Distributed Connectivity Control of Mobile Networks

Control of mobile networks raises fundamental and novel problems in controlling the structure of the resulting dynamic graphs. In particular, in applications involving mobile sensor networks and multiagent systems, a great new challenge is the development of distributed motion algorithms that guarantee connectivity of the overall network. Motivated by the inherently discrete nature of graphs as combinatorial objects, we address this challenge using a key control decomposition. First, connectivity control of the network structure is performed in the discrete space of graphs and relies on local estimates of the network topology used, along with algebraic graph theory, to verify link deletions with respect to connectivity. Tie breaking, when multiple such link deletions can violate connectivity, is achieved by means of gossip algorithms and distributed market-based control. Second, motion control is performed in the continuous configuration space, where nearest-neighbor potential fields are used to maintain existing links in the network. Integration of the earlier controllers results in a distributed, multiagent, hybrid system, for which we show that the resulting motion always ensures connectivity of the network, while it reconfigures toward certain secondary objectives. Our approach can also account for communication time delays as well as collision avoidance and is illustrated in nontrivial computer simulations

TCP in 5G mmWave Networks: Link Level Retransmissions and MP-TCP

MmWave communications, one of the cornerstones of future 5G mobile networks, are characterized at the same time by a potential multi-gigabit capacity and by a very dynamic channel, sensitive to blockage, wide fluctuations in the received signal quality, and possibly also sudden link disruption. While the performance of physical and MAC layer schemes that address these issues has been thoroughly investigated in the literature, the complex interactions between mmWave links and transport layer protocols such as TCP are still relatively unexplored. This paper uses the ns-3 mmWave module, with its channel model based on real measurements in New York City, to analyze the performance of the Linux TCP/IP stack (i) with and without link-layer retransmissions, showing that they are fundamental to reach a high TCP throughput on mmWave links and (ii) with Multipath TCP (MP-TCP) over multiple LTE and mmWave links, illustrating which are the throughput-optimal combinations of secondary paths and congestion control algorithms in different conditions.Comment: 6 pages, 11 figures, accepted for presentation at the 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS

Past, present and future of path-planning algorithms for mobile robot navigation in dynamic environments

Mobile robots have been making a significant contribution to the advancement of many sectors including automation of mining, space, surveillance, military, health, agriculture and many more. Safe and efficient navigation is a fundamental requirement of mobile robots, thus, the demand for advanced algorithms rapidly increased. Mobile robot navigation encompasses the following four requirements: perception, localization, path-planning and motion control. Among those, path-planning is a vital part of a fast, secure operation. During the last couple of decades, many path-planning algorithms were developed. Despite most of the mobile robot applications being in dynamic environments, the number of algorithms capable of navigating robots in dynamic environments is limited. This paper presents a qualitative comparative study of the up-to-date mobile robot path-planning methods capable of navigating robots in dynamic environments. The paper discusses both classical and heuristic methods including artificial potential field, genetic algorithm, fuzzy logic, neural networks, artificial bee colony, particle swarm optimization, bacterial foraging optimization, ant-colony and Agoraphilic algorithm. The general advantages and disadvantages of each method are discussed. Furthermore, the commonly used state-of-the-art methods are critically analyzed based on six performance criteria: algorithm's ability to navigate in dynamically cluttered areas, moving goal hunting ability, object tracking ability, object path prediction ability, incorporating the obstacle velocity in the decision, validation by simulation and experimentation. This investigation benefits researchers in choosing suitable path-planning methods for different applications as well as identifying gaps in this field. © 2020 IEEE

A survey of self organisation in future cellular networks

This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks