Based on the above scheme, we propose a number of solutions to reduce the computational complexity and communication cost. To reduce the computational complexity, we propose to aggregate the local data and transit data and route them with a single set of routing variables. To reduce the communication overhead, a different smoothing function is proposed that only requires the information of a set of bottleneck nodes. The optimality conditions are derived and a distributed algorithm is designed accordingly. Simulation results illustrate the effectiveness and efficiency of the proposed solution. / Sleeping scheduling is another approach to save energy consumption for sensor networks. The basic idea is to schedule the duty-cycles of sensor nodes such that off-duty sensors are turned off as long as the network functionality can be maintained by working nodes. For applications whereby coordination of sleeping among sensors is not possible or inconvenient, random sleeping is the only option. We present the Asynchronous Random Sleeping (ARS) scheme whereby sensors (i) do not need to synchronize with each other, and (ii) do not need to coordinate their wakeup patterns. The stationary coverage probability and the expected coverage periods for ARS are derived. For surveillance application, we derive in addition the detection probability and detection delay distribution. We find that the expected detection delay of asynchronous random sleeping is smaller than that of the synchronous random sleeping. / This thesis is focused on the design and analysis of energy conservation methods for wireless sensor networks (WSNs). Unlike traditional wireless networks, sensor nodes in WSNs are collaborating towards a common mission. The failure of some sensor nodes may cause significant topological changes and loss of information at the target region. Therefore, network lifetime is the primary objective for designing energy conservation solutions for WSNs. / We address the energy conservation problem from the aspects of maximum lifetime routing, data aggregation and sleeping scheduling. We first propose a data aggregated maximum lifetime routing scheme for wireless sensor networks. We adopt a data aggregation model that decouples the routing of local data and transit data. The objective is to jointly optimize data aggregation and routing so that the network lifetime can be maximized. A recursive smoothing method is adopted to overcome the nondifferentiability of the objective function. We derive the necessary and sufficient conditions for achieving the optimality of the smoothing function and design a distributed gradient algorithm accordingly. We show that the proposed scheme can significantly reduce the data traffic and improve the network lifetime. The distributed algorithm can converge to the optimal value efficiently under all network configurations. / Hua Cunqing. / "June 2006." / Adviser: Tak-Shing Yum. / Source: Dissertation Abstracts International, Volume: 68-03, Section: B, page: 1825. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 120-131). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

Call number: LD2668 .T4 1979 N368 / Master of Science