一种无线传感器网络蚁群优化路由算法

如何在资源受限的无线传感器网络中进行高效的数据路由是无线传感器网络研究的热点之一.将蚁群优化算法(ACO)应用于无线传感器网络的路由,提出一种无线传感器网络蚁群优化路由算法.该算法利用蚁群的自组织、自适应和动态寻优能力进行网络优化路径的建立与维护,采用Stigmergy的概念来减少控制信息的流量,以实现网络数据的高效传输.仿真分析表明,该算法和DD算法相比在传输延时方面性能相当,在路由代价方面效果显著.另外,该算法还具有可靠性高、适应性强等优点,并能够根据需要实现网络的拥堵控制和能量均衡等综合优化.

An ACO-based Routing Algorithm for Wireless Sensor Networks(ARAWSN)

How to get high efficient data routing for the limited energy resource networks is an important problem in the study of the wireless sensor networks. Appling the Ant Colony Optimization Algorithm (ACO) on the routing of wireless sensor networks, we proposed an ACO-based routing algorithm for wireless sensor networks called ARAWSN. The algorithm utilized the self-organization, self-adaptability and dynamic optimization capabilities of the Ant Colony to build and maintain the optimal network path. It adopted the conception of Stigmergy to minimize the flow number of the control information and achieve high efficient data transitions for the network. In our experiment, the average time delay using the ACO-based routing algorithm is comparative to that of Directed Diffusion (DD) algorithm but has notable effect in the energy cost of routing compared to DD algorithm. In addition, this algorithm also has good dependability and high adaptability. And it can also achieve congestion control and energy balance for wireless sensor networks if needed.