Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 175-177).

Thesis (Ph.D. (Computer Science)) - Rhodes University, 2008.

Thesis (M.S.)--University of Delaware, 2009. / Principal faculty advisor: Charles G. Boncelet, Dept. of Computer & Information Sciences. Includes bibliographical references.

Thesis (M.S.)--Rutgers University, 2009. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 41-42).

Thesis (Ph. D.)--OGI School of Science & Engineering at OHSU, 2002. / Includes bibliographical references.

M. Tech. Electrical Engineering. / Discusses the question of how to prolong the life of an entire sensor network by reducing the power consumption is the most important issue in wireless sensor networks. Traditional routing schemes have not fulfilled the expectations of an optimised WSN, and as a result, new algorithms are being designed globally. One of these protocols which serve as a basis for this study is the RCRR. In this project, we present a new approach of the Relative Coordinates Rumor Routing algorithm based on a link quality awareness scheme and a modified version of the protocol with better scaling.The benefits of this study are: Proposal of a tuneable algorithm that will not only consume less power compared to the classic RR but also addresses the scalability problem encountered with the original RCRR. Proposal a better trade-off between throughput and average end-to-end delay with the use of the SMAC (compared with Rumor protocol). Avoidance of long delays in queues and saving power on retransmission of packets. Reduction of the wandering of agents during communication. Prolonging the lifetime of the network and thus offering economic, operational, and environmental benefits. Balancing link quality awareness with a topological localisation scheme to achieve better throughput.

The focus of this thesis is on the resource allocation problems in wireless sensor and cooperative networks. Typically, wireless sensor networks operate with limited energy and bandwidth are often required to meet some specified Quality-of-Service (QoS) constraints. The ultimate objective for the majority of the problems considered in this thesis is to save battery energy and maximize the network lifetime. / In the first part of this thesis, we employ complex mathematical models to emulate a variety of power drains in wireless sensor nodes. In the first instance, we address a lifetime optimization problem of a wireless TDMA/CDMA sensor network for joint transmit power and rate allocations. The effect of fast fading is captured by including rate outage and link outage constraints on each link. After that, a single-hop wireless sensor network is deployed for a certain application - to estimate a Gaussian source within a pre-specified distortion threshold. In this part, we consider lifetime maximization, in different multiple access protocols such as TDMA, an interference limited non-orthogonal multiple access (NOMA) and an idealized Gaussian multiple access channel. This problem is further studied in a multi-hop scenario where sensing and receiving powers are also included in addition to transmission power. Finally, we investigate a balancing problem between the source coding and transmission power for video wireless sensor systems where the sensor node is required to send the collected video clips, through wireless media, to a base station within a corresponding distortion threshold. All these energy saving and lifetime optimization problems in sensor networks can be formulated via nonlinear nonconvex optimization problems, which are generally hard to solve. However, with favourable variable substitution and reasonable approximation, most of these problems are shown to be convex. The only exception is the Gaussian source esitmation problem in NOMA scenario for which we provide a simple successive convex approximation based algorithm for the NOMA case that converges fast to a suboptimal solution. / In the second part of the thesis, we propose an optimal power allocation scheme with a K-block coding delay constraint on data transmission using a three node cooperative relay network assuming a block fading channel model. Channel information is fed back to the transmitter only in a causal fashion, so that the optimal power allocation strategy is only based on the current and past channel gains. We consider the two simplest schemes for information transmission using a three node (a source, a relay and a destination) relay network, namely the amplify and forward (AF) and decode and forward (DF) protocols. We use the dynamic programming methodology to solve the (K-block delay constrained) expected capacity maximization problem and the outage probability minimization problem with a short term sum power (total transmission power of the source and the relay) constraint. / The main contribution of the thesis is a comprehensive suite of power minimization and lifetime maximization methods that can be used in wireless sensor networks. We present several such applications and extensive numerical examples at the end of each chapter.

Dissertation (Ph.D.)--Auburn University, 2007. / Abstract. Includes bibliographic references (p.127-137).

Thesis (M.S. in computer science)--Washington State University, May 2009. / Title from PDF title page (viewed on July 21, 2009). "School of Electrical Engineering and Computer Science." Includes bibliographical references (p. 113-117).

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 70-73).