一种基于跨层负载感知和双向逐跳信息素更新的自组网蚂蚁算法

本文将跨层优化和蚂蚁优化方法结合起来解决自组网中的负载均衡问题，提出了一种基于跨层负载感知和双向逐跳更新信息素的蚂蚁优化路由协议（CLABHPU）.协议将整个路径中各节点MAC层的总平均估计时延和节点队列缓存的占用情况结合起来，共同作为路由选择和路由调整的重要依据，进行按需路由发现和维护;通过拥塞节点丢弃蚂蚁分组的方法减少了控制开销，增加了算法的可扩展性，较好地解决了自组网中现有基于蚂蚁算法的路由协议中普遍存在的拥塞问题和路由开销问题.同时，协议在路由发现阶段通过中间节点对信息素表进行双向和逐跳更新，提高了算法的收敛速度和对异常情况的反应速度.通过概率选路提供到目的节点的大量冗余路由，提高了算法的可靠性和顽存性.仿真结果表明，CLABHPU在分组成功递交率、路由开销以及端到端平均时延等方面具有优良性能，能很好地实现网络业务流负载均衡.

A Cross-layer Load-aware Based Ant-colony Optimization Routing Protocol with Bi-directional and Hop-by-hop Pheromone Update for Ad hoc Networks(CLABHPU)

In this paper,we present a cross-layer load-aware based ant colony optimization routing protocol with bi-di- rectional and hop-by-hop pheromone update for ad hoc networks(CLABHPU).CLABHPU combines the total path av- erage estimated delay with the buffer occupation ratio of MAC layer as the primary metric for route selection and route adjustment during the on-demand route discovery and route maintenance periods,and CLABHPU makes use of some data paekets to implement route maintenance and allow the heavy load nodes to drop the ants.Thus it ean decrease the route overhead,inerease the scalability of the algorithm and improve the congestion problem commonly existed in exist- ing ant-based routing protocols for ad hoe networks.At the same time,the intermediate nodes bi-directionally update the pheromone table hop-by-hop,which can accelerate the eonvergence rate of the algorithm and improve the speed of response to abnormal cases.Besides,CLABHPU depends on probability routing table,thus providing a number of re- dundant paths to the destination and helping increasing the reliability and survivability of the algorithm.The perform- ance of the algorithm is measured.Simulation results show that CLABHPU performs well in the packet delivery rate and routing overhead as well as end-to-end delay.