摘要
面向低占空比传感网的实时QoS需求,提出基于动态规划和免疫遗传算法的端到端延迟控制方法,通过在接收节点上增加最少数量的活跃时隙以保障数据的实时传输。针对链式网络,利用动态规划递归地增加节点的活跃时隙获得满足延迟约束的最优解;针对树状网络,利用免疫遗传算法调整活跃时隙以满足端到端延迟约束。仿真结果表明:动态规划算法可以在链式网络中获得最优解,而在树状网络中,免疫遗传算法可以弥补动态规划算法的不足,以较低的复杂度有效地控制低占空比传感网的端到端延迟。
To satisfy the real-time QoS requirement of low-duty-cycled sensor networks,end-to-end delay control methods are proposed based on dynamic programming and immune genetic algorithm.For chain-based network,dynamic programming is used to recursively augment the node’s active slot so that an optimized solution can be obtained.For tree-based network,immune genetic algorithm is used to adjust the active bit of the nodes to meet the delay constraint.Simulation results show that dynamic programming can obtain optimal solution for chain-based network,while immune genetic algorithm can make up the limitation of dynamic programming in tree-based network and effectively control the end-to-end delay with a lower computational complexity.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第S1期171-175,共5页
Journal of Central South University:Science and Technology
基金
国家自然科学基金资助项目(61003264
61001126)
浙江省自然科学基金资助项目(LY13F020028)
关键词
低占空比
延迟控制
动态规划
遗传算法
传感网
low-duty-cycle
delay control
dynamic programming
genetic algorithm
sensor networks
