摘要
资源受限情况下,对云计算环境的动态传感网络路由操作效率的提升,能够有效实现传感网络的节能运行。对动态传感网络路由算法的优化,需要选取传感网络中生存周期最长的节点,获取源节点到目的节点的最短路径,完成路由算法的优化研究,传统方法设定资源受限下动态传感网络能耗,得到网络节点间的权重,但忽略了对节点传输路径的计算,导致路由优化效果不理想。提出基于蚁群优化的资源受限云计算下动态传感网络路由算法,首先从动态传感网络整体能量消耗出发,建立马尔科夫博弈模型,并求解出动态传感网络节点的能量和收益之间的纳什均衡系数。然后在保证动态传感网络生存周期最长的节点,利用蚁群优化从动态传感网络的源节点到目的节点的最短路径,采用多路数据传输,完成路由操作。仿真结果证明,所提算法提高了动态传感网络的传输效率,降低了动态传感网络的能量消耗。实现动态传感网络在通信过程中快速、节能的路由。
This article presents a dynamic sensor network routing algorithm in resource - constrained cloud com- puting based on ant colony optimization. Firstly, based on overall energy consumption of dynamic sensor network, Markov game model was built, and Nash equilibrium coefficient between the energy and the benefits of dynamic sensor network node was obtained. Then, on the premise of guaranteeing the longest lifetime of node in dynamic sensor network, ant colony was used to optimize the shortest path from the source node of dynamic sensor network to the des- tination node. Finally the multi - channel data transmission was used to complete the routing operation. Simulation results show that the proposed algorithm improves the transmission efficiency and reduces the energy consumption of dynamic sensing network, which can realize the fast and energy - efficient routing of dynamic sensing network in the process of communication.
作者
杨学颖
YANG Xue - ying(School of Information Engineering,North China University of Resources and Electric Power,Zhengzhou,Henan,4501M6,China)
出处
《计算机仿真》
北大核心
2018年第8期289-292,共4页
Computer Simulation
基金
2017教育部产学合作协同育人创新创业联合基金项目(201701045039)
2017河南省大学生创新创业训练计划项目(201710078036)
关键词
云计算
传感网络
路由算法
蚁群优化
Cloud computing
Sensor networks
Routing algorithm
Ant colony optimization
