基于引力场的机会网络路由算法

A routing algorithm for the opportunistic network based on the gravitation field

机会网络通过节点的运动带来相遇机会进行数据传递,结构的拓扑变化给机会网络的路由算法设计带来了挑战.现有的经典路由算法认为节点与节点的关系是独立的,没考虑节点之间的关系,根据"节点的最大介数与网络的传输能力呈近似反比的关系"这一关系,结合引力场理论,将机会网络抽象为一个引力场,网络中的节点视为引力场中的暗能量和星体,节点间的相互作用转化为路径对数据包的吸引力,提出了基于引力场的机会网络路由算法(routing algorithm for opportunistic network based on gravitation field,BGF),通过在ONE上的仿真实验,然后与Epidemic算法、Prophet算法对比,实验结果表明:在节点数与节点缓存比较大时,BGF算法的传输成功率最高,传输延迟与路由开销最小.

The opportunistic network that transmits data by mobile nodes brings encounter while this constantly changing topological structure also brings challenges to the design of the routing algorithm of the opportunistic network.The existing classical routing algorithms regard the nodes as independent.Accepting the idea that the network transmission capacity has an approximate inverse relation with the maximum betweenness,this paper uses the gravitational field theory,abstracts the opportunistic network as a gravitation field,regards the nodes in the network as the dark energy and stars in the gravitation field,and the interaction between the nodes as the attraction of the path to the data package.It then comes up with a new routing algorithm,that is,a routing algorithm for the opportunistic network based on the gravitation field.Lastly,according to the simulation in ONE,when the number of the nodes and caches is larger,the new routing algorithm has a higher delivery ratio and lower delivery delay,better than the Epidemic algorithm and the Prophet algorithm.