Title :
Sensor Network Management Through Fitness Function Design In Multi-Objective Optimization
Author :
Osadciw, Lisa ; Veeramachaneni, Kalyan
Author_Institution :
Syracuse Univ., Syracuse
Abstract :
Multi-objective optimization can support sensor network management by taking advantage of the many degrees of freedom available in controlling the sensors. Fitness function design is the key to increasing efficient use of the sensors complete a successful mission. This paper discusses applying fitness functions to model performance parameter decisions. Performance constraints can be introduced preventing solutions with fatal performance flaws from being considered as well as decreasing run-time. Also, the system´s tolerance to missing performance goals may be increased or decreased by taking advantage of the weights in goal programming equations. The swarm can be designed to reduce run-time for real-time applications as well as improving the system´s performance mismatches in key areas through the introduction of limits and performance weights in the fitness function.
Keywords :
mathematical programming; particle swarm optimisation; wireless sensor networks; fitness function design; goal programming equations; multiobjective optimization; particle swarm optimization; sensor network management; Computer network management; Costs; Design optimization; Engineering management; Equations; Real time systems; Runtime; Sensor fusion; Sensor phenomena and characterization; Sensor systems; fitness; multi-objective optimization; particle swarm optimization; process refinement; sensor management;
Conference_Titel :
Signals, Systems and Computers, 2007. ACSSC 2007. Conference Record of the Forty-First Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
978-1-4244-2109-1
Electronic_ISBN :
1058-6393
DOI :
10.1109/ACSSC.2007.4487511