Title :
Maximizing multi-sensor system dependability
Author :
Brooks, R.R. ; Iyengar, S.S.
Author_Institution :
Commun. Sci. & Technol. Center, California State Univ., Seaside, CA, USA
Abstract :
This paper considers distributed sensor systems and finds redundant configurations which maximize dependability while insuring the system remains within cost or weight constraints. Given different sensor modules which fulfil the system´s operational requirements but have different dependability and cost parameters, efficient methods are used to find maximum dependability configurations. These methods limit the search to a constrained subspace of the problem space. It is shown that this region must contain the optimal configuration. Three heuristics: genetic algorithms, simulated annealing and tabu search are used. Experimental results are presented with dependability gains of between 10 and 15%. These test cases compare results from all methods and verify that in most cases the simulated annealing heuristic provides the best solutions
Keywords :
genetic algorithms; redundancy; search problems; sensor fusion; simulated annealing; cost constraints; distributed sensor systems; genetic algorithms; maximum dependability configurations; multi-sensor system dependability; operational requirements; redundant configurations; simulated annealing; tabu search; weight constraints; Communications technology; Computer science; Costs; Intelligent sensors; Nuclear magnetic resonance; Redundancy; Sensor fusion; Sensor systems; Sensor systems and applications; Simulated annealing;
Conference_Titel :
Multisensor Fusion and Integration for Intelligent Systems, 1996. IEEE/SICE/RSJ International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-3700-X
DOI :
10.1109/MFI.1996.568492