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Base station (BS) positioning is considered an effective method to improve the performance of a Wireless Sensor Network (WSN). The goal of this dissertation is to minimize total energy consumption and to prolong lifetime of a WSN. First, the idea of the BS positioning in WSNs through our exhaustive search algorithm is evaluated; where it is shown that the BS position has an undeniable effect on the energy efficiency and lifespan of a WSN. Then, a metric-aware optimal BS positioning and relocation mechanism for WSNs is proposed. This technique locates the BS with respect to the available energy resources and the amount of traffic travelling through the sensor nodes at the time. Moreover, a BS relocation technique is presented in response to the dynamic environment that the sensor nodes operate in. Specifically, two optimization strategies based on the value of the path loss exponent are analyzed as weighted linear or nonlinear least squares minimization problems. Lastly, a distributed algorithm is proposed that can effectively handle the required computation by exploiting the nodes cooperation. The simulation results demonstrate that the proposed BS positioning and relocation method can significantly improve the lifespan and energy efficiency in WSNs. / Communications

A Mobile Ad Hoc Network (MANET) adopts a decentralized communication architecture which relies on cooperation among nodes at each layer of the protocol stack. Its reliance on cooperation for success and survival makes the ad hoc network particularly sensitive to variations in node behavior. Specifically, for functions such as routing, nodes which are limited in their resources may be unwilling to cooperate in forwarding for other nodes. Such selfish behavior leads to degradation in the performance of the network and possibly, in the extreme case, a complete cessation of operations. Consequently it is important to devise solutions to encourage resource-constrained nodes to cooperate. Incentive schemes have been proposed to induce selfish nodes to cooperate. Though many of the proposed schemes in the literature are payment-based, nodes can be incentivized to cooperate by adopting policies which are non-monetary in nature, but rather are based on the threat of retaliation for non-cooperating nodes. These policies, for which there is little formal analysis in the existing literature on node cooperation, are based on observed node behavior. We refer to them as behavior-based incentives. In this work, we analyze the effectiveness of behavior-based incentives in inducing nodes to cooperate. To determine whether an incentive scheme is effective in fostering cooperation we develop a game-theoretic model. Adopting a repeated game model, we show that nodes may agree to cooperate in sharing their resources and forward packets, even if they perceive a cost in doing so. This happens as the nodes recognize that refusing to cooperate will result in similar behavior by others, which ultimately would compromise the viability of the network as a whole. A major shortcoming in the analysis done in past works is the lack of consideration of practical constraints imposed by an ad hoc environment. One such example is the assumption that a node, when making decisions about whether to cooperate, has perfect knowledge of every other node's actions. In a distributed setting this is impractical. In our work, we analyze behavior-based incentives by incorporating such practical considerations as imperfect monitoring into our game-theoretic models. In modeling the problem as a game of imperfect public monitoring (nodes observe a common public signal that reflects the actions of other nodes in the network) we show that, under the assumption of first order stochastic dominance of the public signal, the grim trigger strategy leads to an equilibrium for nodes to cooperate. Even though a trigger-based strategy like grim-trigger is effective in deterring selfish behavior it is too harsh in its implementation. In addition, the availability of a common public signal in a distributed setting is rather limited. We, therefore, consider nodes that individually monitor the behavior of other nodes in the network and keep this information private. Note that this independent monitoring of behavior is error prone as a result of slow switching between transmit and promiscuous modes of operation, collisions and congestion due to the wireless medium, or incorrect feedback from peers. We propose a probability-based strategy that induces nodes to cooperate under such a setting. We analyze the strategy using repeated games with imperfect private monitoring and show it to be robust to errors in monitoring others" actions. Nodes achieve a near-optimal payoff at equilibrium when adopting this strategy. This work also characterizes the effects of a behavior-based incentive, applied to induce cooperation, on topology control in ad hoc networks. Our work is among the first to consider selfish behavior in the context of topology control. We create topologies based on a holistic view of energy consumption " energy consumed in forwarding packets as well as in maintaining links. Our main results from this work are to show that: (a) a simple forwarding policy induces nodes to cooperate and leads to reliable paths in the generated topology, (b) the resulting topologies are well-connected, energy-efficient and exhibit characteristics similar to those in small-world networks. / Ph. D.

Given a set P of n points in R^d, we consider the k-connected interference minimization problem, in which the objective is to assign a transmission radius to each node in P such that the resulting network is k-connected and the maximum interference is minimized. We show for any n and any 1 <= k < n, Omega(sqrt(kn)) and Omega(k log n) are lower bounds on the worst-case minimum maximum interference in the symmetric and asymmetric models, respectively. In the symmetric case, we present polynomial-time algorithms that build a k-connected network on any given set of n nodes with interference O(sqrt(kn)) in one dimension and O(min{k sqrt(n), k log lambda}) in two dimensions, where lambda denotes the ratio of the longest to shortest distances between any pair of nodes. In the asymmetric case, we present a polynomial-time algorithm that builds a strongly k-connected network with maximum interference O(k log lambda) in two dimensions. / October 2016

Underwater wireless sensor networks (UWSNs) are the enabling technology for a new era of underwater monitoring and actuation applications. However, there still is a long road ahead until we reach a technological maturity capable of empowering high-density large deployment of UWSNs. To the date hereof, the scientific community is yet investigating the principles that will guide the design of networking protocols for UWSNs. This is because the principles that guide the design of protocols for terrestrial wireless sensor networks cannot be applied for an UWSN since it uses the acoustic channel instead of radio-frequency-based channel. This thesis provides a general discussion for high-fidelity and energy-efficient data collection in UWSNs. In the first part of this thesis, we propose and study the symbiotic design of topology control and opportunistic routing protocols for UWSNs. We propose the CTC and DTC topology control algorithms that rely on the depth adjustment of the underwater nodes to cope with the communication void region problem. In addition, we propose an analytical framework to study and evaluate our mobility-assisted approach in comparison to the classical bypassing and power control-based approaches. Moreover, we develop the GEDAR routing protocol for mobile UWSNs. GEDAR is the first OR protocol employing our innovative depth adjustment-based topology control methodology to re-actively cope with communication void regions. In the second part of this thesis, we study opportunistic routing (OR) underneath duty-cycling in UWSNs. We propose an analytical framework to investigate the joint design of opportunistic routing and duty cycle protocols for UWSNs. While duty-cycling conserves energy, it changes the effective UWSN density. Therefore, OR is proposed to guarantee a suitable one-hop density of awake neighbors to cope with the poor and time-varying link quality of the acoustic channel. In addition, we propose an analytical framework to study the impact of heterogeneous and on-the-fly sleep interval adjustment in OR underneath duty-cycling in UWSNs. The proposed model is aimed to provide insights for the future design of protocols towards a prolonged UWSN lifetime. The developed solutions have been extensively compared to related work either analytically or through simulations. The obtained results show the potentials of them in several scenarios of UWSNs. In turn, the devised analytical frameworks have been providing significant insights that will guide future developments of routing and duty-cycling protocols for several scenarios and setting of UWSNs.

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Multi-robot systems have recently witnessed a swell in interest in the past few years because of their various applications such as agricultural autonomy, medical robotics, industrial and commercial automation and, search and rescue. In this thesis, we particularly investigate the behavior of multi-robot systems with respect to stable topology control in asymmetric interaction settings. From theoretical perspective, we first classify stable topologies, and identify the conditions under which we can determine whether a topology is stable or not. Then, we design a limited fields-of-view (FOV) controller for robots that use sensors like cameras for coordination which induce asymmetric robot to robot interactions. Finally, we conduct a rigorous theoretical analysis to qualitatively determine which interactions are suitable for stable directed topology control of multi-robot systems with asymmetric interactions. In this regard, we solve an optimal topology selection problem to determine the topology with the best interactions based on a suitable metric that represents the quality of interaction. Further, we solve this optimal problem distributively and validate the distributed optimization formulation with extensive simulations.  For experimental purposes, we developed a portable multi-robot testbed which enables us to conduct multi-robot topology control experiments in both indoor and outdoor settings and validate our theoretical findings. Therefore, the contribution of this thesis is two fold: i) We provide rigorous theoretical analysis of  stable coordination of multi-robot systems with directed graphs, demonstrating the graph structures that induce stability for a broad class of coordination objectives; ii) We develop a testbed that enables validating multi-robot topology control in both indoor and outdoor settings. / Doctor of Philosophy / In this thesis, we address the problem of collaborative tasks in a multi-robot system where we investigate how interactions within members of the multi-robot system can induce instability. We conduct rigorous theoretical analysis and identify when the system will be unstable and hence classify interactions that will lead to stable multi-robot coordination. Our theoretical analysis tries to emulate realistic interactions in a multi-robot system such as limited interactions (blind spots) that exist when on-board cameras are used to detect and track other robots in the vicinity. So we study how these limited interactions induce instability in the multi-robot system. To verify our theoretical analysis experimentally,  we developed a portable multi-robot testbed that enables us to test our theory on stable coordination of multi-robot system with a team of Unmanned Aerial Vehicles (UAVs) in both indoor and outdoor settings. With this feature of the testbed we are able to investigate the difference in the multi-robot system behavior when tested in controlled indoor environments versus an uncontrolled outdoor environment. Ultimately, the motivation behind this thesis is to emulate realistic conditions for multi-robot cooperation and investigate suitable conditions for them to work in a stable and safe manner. Therefore, our contribution is twofold ; i) We provide rigorous theoretical analysis that enables stable coordination of multi-robot systems with limited interactions induced by sensor capabilities such as cameras; ii) We developed a testbed that enables testing of our theoretical contribution with a team of real robots in realistic environmental conditions.

Wireless Sensor Networks (WSNs) are now widely used for monitoring and controlling of systems where human intervention is not desirable or possible. Connected Dominating Sets (CDSs) based topology control in WSNs is one kind of hierarchical method to ensure sufficient coverage while reducing redundant connections in a relatively crowded network. Moreover, Minimum-sized Connected Dominating Set (MCDS) has become a well-known approach for constructing a Virtual Backbone (VB) to alleviate the broadcasting storm for efficient routing in WSNs extensively. However, no work considers the load-balance factor of CDSsin WSNs. In this dissertation, we first propose a new concept — the Load-Balanced CDS (LBCDS) and a new problem — the Load-Balanced Allocate Dominatee (LBAD) problem. Consequently, we propose a two-phase method to solve LBCDS and LBAD one by one and a one-phase Genetic Algorithm (GA) to solve the problems simultaneously. Secondly, since there is no performance ratio analysis in previously mentioned work, three problems are investigated and analyzed later. To be specific, the MinMax Degree Maximal Independent Set (MDMIS) problem, the Load-Balanced Virtual Backbone (LBVB) problem, and the MinMax Valid-Degree non Backbone node Allocation (MVBA) problem. Approximation algorithms and comprehensive theoretical analysis of the approximation factors are presented in the dissertation. On the other hand, in the current related literature, networks are deterministic where two nodes are assumed either connected or disconnected. In most real applications, however, there are many intermittently connected wireless links called lossy links, which only provide probabilistic connectivity. For WSNs with lossy links, we propose a Stochastic Network Model (SNM). Under this model, we measure the quality of CDSs using CDS reliability. In this dissertation, we construct an MCDS while its reliability is above a preset applicationspecified threshold, called Reliable MCDS (RMCDS). We propose a novel Genetic Algorithm (GA) with immigrant schemes called RMCDS-GA to solve the RMCDS problem. Finally, we apply the constructed LBCDS to a practical application under the realistic SNM model, namely data aggregation. To be specific, a new problem, Load-Balanced Data Aggregation Tree (LBDAT), is introduced finally. Our simulation results show that the proposed algorithms outperform the existing state-of-the-art approaches significantly.

The objective of this thesis is to address the problem of energy conservation in wireless sensor networks by tackling two fundamental problems: topology control and data delivery. We first address energy-aware topology control taking into account throughput per unit energy as the primary metric of interest. Through both experimental observations and analysis, we show that the optimal topology is a function of traffic load in the network. We then propose a new topology control scheme, Adaptive Topology Control (ATC), which increases throughput per unit energy. Based on different coordinations among nodes, we proposed three ATC schemes: ATC-CP, ATC-IP, and ATC-MS. Through simulations, we show that three ATC schemes outperform static topology control schemes, and particularly the ATC-MS has the best performance under all environments. Secondly, we explore an energy-aware data delivery problem consisting of two sub-problems: downstream (from a sink to sensors) and upstream (from sensors to a sink) data delivery. Although we address the problems as two independent ones, we eventually solve those problems with two approaches: GARUDA-DN and GARUDA-UP which share a common structure, the minimum dominating set. For the downstream data delivery, we consider reliability as well as energy conservation since unreliable data delivery can increase energy consumption under high data loss rates. To reduce energy consumption and achieve robustness, we propose GARUDA-DN which is scalable to the network size, message characteristics, loss rate and the reliable delivery semantics. From ns2-based simulations, we show that GARUDA-DN performs significantly better than the basic schemes proposed thus far in terms of latency and energy consumption. For the upstream data delivery, we address an energy efficient aggregation scheme to gather correlated data with theoretical solutions: the shortest path tree (SPT), the minimum spanning tree (MST) and the Steiner minimum tree (SMT). To approximate the optimal solution in case of perfect correlation among data, we propose GARUDA-UP which combines the minimum dominating set (MDS) with SPT in order to aggregate correlated data. From discrete event simulations, we show that GARUDA-UP outperforms the SPT and closely approximates the centralized optimal solution, SMT, with less amount of overhead and in a decentralized fashion.

Wireless sensor networks (WSNs) have emerged in strategic applications such as target detection, localization, and tracking in battlefields, where the large-scale na- ture renders centralized control prohibitive. In addition, the finite batteries in sensor nodes demand energy-aware network control. In this thesis, we propose an energy- efficient topology management model inspired by biological inter-cellular signaling schemes. The model allows sensor nodes to cluster around imminent targets in a purely distributed and autonomous fashion. In particular, nodes in the target vicinity collaborate to form clusters based on their relative observation quality values. Sub- sequently, the clustered sensor nodes compete based on their energy levels until some of them gain active status while the rest remain idle, again according to a distributed algorithm based on biological processes. A final phase of the model has the active cluster members compete until one of them becomes the clusterhead. We examine the behavior of such a model in both finite-size and infinite-size networks. Specifically, we show that the proposed model is inherently stable and achieves superior energy efficiency against reference protocols for networks of finite size. Furthermore, we dis- cuss the behavior of the model in the asymptotic case when the number of nodes goes to infinity. In this setting, we study the average number of cluster members.