摘要
As a novel application technology,wireless video sensor networks become the current research focus,especially on target tracking and surveillance scenario.Based on multiple agents' technique,this article introduces a series of intelligent algorithms such as simulated annealing algorithm(SA),genetic algorithm(GA),and ant colony optimization algorithm(ACO) or their mixed algorithms,to resolve the optimization of tasks schedule and data transmission.This article analyzes the performance of abovementioned algorithms and verifies their feasibility associated with agents.The simulations demonstrates that the mixed algorithms based on SA and GA obtain the optimal solution to tasks schedule,and those combined with SA-ACO show advantages on multimedia sensor networks routing optimization.
As a novel application technology,wireless video sensor networks become the current research focus,especially on target tracking and surveillance scenario.Based on multiple agents' technique,this article introduces a series of intelligent algorithms such as simulated annealing algorithm(SA),genetic algorithm(GA),and ant colony optimization algorithm(ACO) or their mixed algorithms,to resolve the optimization of tasks schedule and data transmission.This article analyzes the performance of abovementioned algorithms and verifies their feasibility associated with agents.The simulations demonstrates that the mixed algorithms based on SA and GA obtain the optimal solution to tasks schedule,and those combined with SA-ACO show advantages on multimedia sensor networks routing optimization.
基金
sponsored by the National Natural Science Foundation of China (60973139, 60773041)
the Natural Science Foundation of Jiangsu Province (BK2008451)
the Hi-Tech Research and Development Program of China (2007AA01Z404, 2007AA01Z478)
Special Fund for Software Technology of Jiangsu Province
Foundation of National Laboratory for Modern Communications (9140C1105040805)
Postdoctoral Foundation (0801019C, 20090451240)
the six kinds of Top Talent of Jiangsu Province (2008118)