Accession Number:

ADA621592

Title:

Topology Optimization for Energy Management in Underwater Sensor Networks

Descriptive Note:

Journal article preprint

Corporate Author:

PENNSYLVANIA STATE UNIV STATE COLLEGE DEPT OF MECHANICAL AND NUCLEAR ENGINEERING

Report Date:

2015-02-01

Pagination or Media Count:

15.0

Abstract:

In general, battery-powered sensors in a sensor network are operable as long as they can communicate sensed data to a processing node. In this context, a sensor network has two competing objectives i maximization of the network performance with respect to the probability of successful search for a specified upper bound on the probability of false alarms and ii maximization of the networks operable life. As both sensing and communication of data consume battery energy at the sensing nodes of the sensor network, judicious use of sensing power and communication power is needed to improve the lifetime of the sensor network. This paper presents an adaptive energy management policy that will optimally allocate the available energy between sensing and communication at each sensing node to maximize the network performance subject to specified constraints. Under the assumptions of fixed total energy allocation for a sensor network operating for a specified time period, the problem is reduced to synthesis of an optimal network topology that maximizes the probability of successful search of a target over a surveillance region. In a two-stage optimization a genetic algorithm GA-based meta-heuristic search is first used to efficiently explore the global design space, and then a local pattern search PS algorithm is used for convergence to an optimal solution. The results of performance optimization are generated on a simulation test bed to validate the proposed concept. Adaptation to energy variations across the network is shown to be manifested as a change in the optimal network topology by using sensing and communication models for underwater environment. The approximate Pareto-optimal surface is obtained as a trade-off between network lifetime and probability of successful search over the surveillance region.

Subject Categories:

  • Electric Power Production and Distribution
  • Statistics and Probability
  • Underwater and Marine Navigation and Guidance
  • Non-Radio Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE