Thesis (Ph.D.)--University of Texas at Arlington, 2009.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 2006. / Vita. Includes bibliographical references (p.166-171). Online version available

Thesis (M.S.)--Youngstown State University, 2009. / Includes bibliographical references (leaves 67-69). Also available via the World Wide Web in PDF format.

Thesis (M. Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005. / Includes bibliographical references (p. 66-69). Also available online.

Thesis (M.S.)--University of Missouri-Columbia, 2003. / Typescript. Includes bibliographical references (leaves 34-36). Also available on the Internet.

Thesis (M.S.)--University of Missouri-Columbia, 2003. / Typescript. Includes bibliographical references (leaves 34-36). Also available on the Internet.

published_or_final_version / Computer Science / Master / Master of Philosophy

Enabling "intelligent environments" that are effortlessly automated is a key promise of sensor networks of the future. These networks have a wide range of domains in which they can be effectively deployed, including health-care, emergency response, manufacturing and surveillance. Unlike the majority of existing (and perhaps better-understood) network configurations, wireless-implemented sensor networks suffer from extremely stringent constraints in terms of scalability and end-goal of deployment. Thus, it is imperative that we determine solutions that are tailored to the constraints and goals of these systems, by bringing together ideas in the domains of control, computing and communications to a common analytical platform. In this dissertation, we build a theoretical framework that uses system theory, stochastic control, queuing theory and information theory to determine the following: 1. A characterization of the stability and optimal control policies with sensor querying (i.e. which set of sensors must be queried and when) using system theory and stochastic control; 2. A delay-optimal energy efficient transmission scheme for these networks (i.e. with what power level must they communicate) using heavy traffic limits and stochastic control; and 3. A cooperative transmission strategy for maximizing capacity of these networks (i.e. how they should encode their data to send the most through) using network information theory.

M. Tech. Electrical Engineering. / Wireless Sensor Networks (WSNs), which contribute to many applications in the military, environmental, medical, and civil domains, consist of small nodes with sensing, data computation, and wireless-communication capabilities. Node routing protocols have been specifically designed for WSNs in which energy conservation is an essential design issue. Rumor Routing (RR) is a hybrid protocol which combines both proactive and reactive routing methods, which balances event and query flooding quite well. This kind of protocol is well adapted to the case of few data and many queries. In this paper, Relative Coordinate Rumor Routing (RCRR), a straight-line routing method of both event and query, is proposed. It improves RR using some topological and abstract localisation method that shortens the source-to-sink route for the data transmission in order to save energy for broadcasting, even comparing to large data amount Routing Protocol. By adapting the Sensor-MAC protocol, the power consumption is much lower than that of the RR. Nodes can change to idle mode when notification of broadcasting does not apply to them. Simulation studies of RCRR with S-MAC can reduce energy by 60% compared to RR, which is a good improvement

Wireless sensor nodes are resource constrained and have limited amount of energy. Therefore, designing protocols that conserve energy is an important area of research. Researchers have investigated architectures and topologies that allow energy efficient operation of WSNs. One of the popular techniques in this regard is clustering. A typical clustering protocol contains two main steps: cluster head election and cluster formation. This thesis is aimed at investigation of the cluster formation process. We propose a Fuzzy Logic based approach that uses three descriptors namely: energy level, distance between cluster-head and base station, and distance between the cluster-head and the sensor’s node. We compare our proposed model, FLCFP (Fuzzy Logic Clustering Formation Protocol), with the most popular model, LEACH, which was proposed previously to prolong network lifetime. FLCFP approach is shown to prolong network lifetime. In addition, it is shown that sensor node energy is consumed in a more uniform fashion.