Actuation ability introduces a fundamentally new design dimension in wireless ad-hoc sensor networks, allowing the network to adaptively reconfigure and repair itself in response to unpredictable run-time dynamics. One of the key network resources in these systems is energy and several uncontrollable factors lead to situations where a certain segment of the network becomes energy constrained before the remaining network. The performance gets limited due to the constrained sections. We argue that in this scenario, instead of rendering the complete network useless, the remaining energy resources should be reorganized to form a new functional topology in the network. We present methods for the network to be aware of its own integrity and use actuation to improve performance when needed. This capability of the system is referred to as “self aware actuation”. In this paper, we consider a network where nodes (or a subset of the nodes) have traction ability. The network uses mobility to repair the coverage loss in the area being monitored by it. We present a completely distributed energy aware algorithm (referred to as Co-Fi) for coordinated coverage fidelity maintenance in sensor networks. The energy overheads of mobility are incorporated in the algorithm, thus leaving no hidden costs. Our preliminary analysis shows that Co-Fi can significantly help improve the usable lifetime of these networks.

Self Aware Actuation for Fault Repair in Sensor Networks

In this paper, we investigate the optimal spectrum management problem in multiuser frequency selective interference channels. First, a simple pairwise condition for FDMA to be optimal is discovered: for any two among all the users, as long as the normalized cross couplings between them two are both larger than or equal to 1/2, orthogonalization between these two users is optimal for every existing user. Therefore, this single condition applies to achieving all Pareto optimal points of the rate region. Furthermore, not only is this condition sufficient, but in symmetric channels, it is also necessary for FDMA to be always optimal. When the normalized cross couplings are less than 1/2, the optimal spectrum management strategy can be a mixture of frequency sharing and FDMA, depending on users’ power constraints. We first explicitly solve the sum-rate maximization problem in two user symmetric flat channels by solving a closed form equation, providing the optimal spectrum management with a clear intuition as the optimal combination of flat FDMA and flat frequency sharing. Next, we show that this result leads to a primal domain convex optimization formulation for generalizations to frequency selective channels. Finally, we show that all the general optimization problems with n>=2 users and an arbitrary weighted sum-rate objective function in non-symmetric frequency selective channels can be solved by primal domain convex optimization with the same methodology.

Optimal Spectrum Management in Multiuser Interference Channels

Monitoring of environmental phenomena with embedded networked sensing confronts the challenges of both unpredictable variability in the spatial distribution of phenomena, coupled with demands for a high spatial sampling rate in three dimensions. For example, low distortion mapping of critical solar radiation properties in forest environments may require two-dimensional spatial sampling rates of greater than 10 samples/m² over transects exceeding 1000 m². Clearly, adequate sampling coverage of such a transect requires an impractically large number of sensing nodes. This paper describes a new approach where the deployment of a combination of autonomous-articulated and static sensor nodes enables sufficient spatiotemporal sampling density over large transects to meet a general set of environmental mapping demands. To achieve this we have developed an embedded networked sensor architecture that merges sensing and articulation with adaptive algorithms that are responsive to both variability in environmental phenomena discovered by the mobile sensors and to discrete events discovered by static sensors. We begin by describing the class of important driving applications, the statistical foundations for this new approach, and task allocation. We then describe our experimental implementation of adaptive, event aware, exploration algorithms, which exploit our wireless, articulated sensors operating with deterministic motion over large areas. Results of experimental measurements and the relationship among sampling methods, event arrival rate, and sampling performance are presented.

Call and Response: Experiments in Sampling the Environment

xi Dedication xiii Acknowledgments xiv 1 Introduction 1 1.

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A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical Engineering

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A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical Engineering