机会网络中面向周期性间歇连通的数据传输

Periodic Intermittently Connected-Based Data Delivery in Opportunistic Networks

提出一种在机会网络中基于周期性间歇连通的数据传输策略PICD(periodic intermittently connected-based data delivery in opportunistic networks).通过有效利用节点间的周期间歇连通性改善数据传输性能.节点传输概率的计算则充分考虑了其与汇聚点间存在的间歇多跳路径,并将其与消息容忍的传输延迟相结合.首先,采用随机动态规划的方法建立与延迟相关的传输概率模型;然后,通过基于多跳的函数空间迭代法求出一个周期内的与延迟相关的传输概率分布矩阵;节点面向不同消息延迟的传输概率则基于分布矩阵计算获得,以此作为选择下一跳的依据.与延迟相关的概率转发机制提高了消息在容忍的延迟内被成功递交的可能.仿真实验结果表明,与现有的几种数据传输算法相比,在节点具有循环运动特征的环境下,PICD具有较高的数据传输成功率和较低的递交延迟.

This paper propos a periodic intermittently connected-based data delivery in opportunistic networks （PICD）. By effectively utilizing periodic intermittent connectivity between any two nodes, PICD can improve data delivery： First, for a certain node, based on its periodic intermittently-connected paths to the sink and its data delay tolerance, PICD establishes the delay probability model by means of random dynamic programming. Next, PICD will calculate the node＇s periodic delay probability distribution matrix by the function space iteration. Next, according to the node＇s distribution matrix, the current data delivery probability can be calculated by specifying period and tolerable delay, and this will become the key-player of the next-hop choosing. In short, the probability forwarding mechanism is delay-relevant and can increase data delivery probability within a tolerable amount of delay. Simulation shows that compared with existing algorithms, which only take advantage of single-hop delivery probability, P1CD is better at data delivery and can also lower delay.