Download or read book Optimization Approaches for Reducing Energy Consumption in Wireless Sensor Nodes and Networks written by Shixin Zhuang and published by . This book was released on 2008 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Minimizing energy consumption in power-limited systems, such as wireless sensor networks (WSN), has become a critical design consideration. This dissertation addresses voltage scaling in a sensor node as an optimal control problem aiming at conserving energy while satisfying some real-time operating requirements. In addition, the joint routing and topology design problem is considered so as to maximize the network lifetime subject to energy constraints. Voltage scaling is treated as a dynamic optimization problem to assign processing times to non-preemptive tasks with uncertain arrival times. For hard real-time constraints, the optimal off-line inter-task and intra-task controllers are shown to be identical as long as the energy cost function is strictly convex, differentiable and monotonically decreasing in the processing time. In the on-line framework where the past history of the evolving process can be used and the optimal controls can be updated at certain decision points, an efficient intra-task algorithm is developed to further reduce the power consumption compared to off-line control. Different off-line controllers are also discussed when only a finite number of discrete voltage levels is available. For weakly hard constraints, it is acceptable for a subset of tasks to miss their deadlines, which allows the design of more cost-effective systems to make better use of the available resources. In this case, a number of structural properties of the solution is established, leading to an algorithm that does not require any explicit nonlinear programming solver. In the case of soft real-time systems, optimal control problems are considered to minimize an objective function that combines energy and tardiness with respect to given deadlines. Simulation examples illustrate the performance improvement in these optimally controlled systems compared to ad hoc schemes. n cluster-based sensor networks, the optimal routing of data depends on the traffic load of each cluster. The simultaneous routing and cluster density assignment problem consists of maximizing the number of successful data gathering cycles before the network loses connectivity or coverage. Routing vectors and cluster density variables are coupled through the initial energy budget constraints. The separable structure is exploited to obtain the solution through a set of relatively simple non-linear programming problems. Numerical results demonstrate that the proposed schemes significantly reduce the power consumption and improve network lifetime performance.