摘要
针对机会网络中的消息转发问题,提出一种基于陌生人的转发算法。定义节点的陌生度,计算节点的陌生值,对节点相遇后的陌生值排序,找出最大陌生值的节点运用加权法激励陌生人数据的转发。仿真结果表明,与Epidemic、PROPHET及STRON等算法比较,该算法通过减少节点间的转发次数,有效降低了网络传输开销,确保了数据消息传输成功率较高和传输延迟较低。
For message forwarding in opportunistic networks, a forwarding algorithm based on stranger was proposed. The value of strangeness of nodes was defined and computed. When two nodes encountered, the value of strangeness of nodes was sorted. The maximum value of strangeness was selected to incent data forwarding of strangers using weighted method. Results of simu- lation show comparing with Epidemic, PROPHET and STRON algorithm, the algorithm by reducing the number of transmis- sions between nodes, can effectively reduce the overhead of network transmission, thus ensuring higher data transmission success rate and lower transmission delay.
出处
《计算机工程与设计》
北大核心
2017年第4期893-897,共5页
Computer Engineering and Design
基金
国家自然科学基金项目(61262089
61262087)
关键词
机会网络
消息转发
陌生值
加权法
激励
opportunistic networks
message forwarding
degree of strangeness
weighted method
incent
