消息重要程度感知的机会网络自适应队列管理策略

Message-importance aware adaptive queue management mechanism in opportunistic networks

机会网络中节点存储资源有限,为了提高机会网络中节点存储资源的使用效率,本文首先提出一种准确的节点活跃程度估计方法,并用于衡量消息的重要程度,进而,根据评估结果设计了适用于机会网络的自适应队列管理策略,确定节点队列内部消息优先级以及携带决策。该策略根据节点与其他节点相遇的次数估计节点活跃程度。节点活跃程度与消息成功传输直接相关,可用于衡量消息的重要程度。仿真结果表明,所提出的节点活跃度估计方法比较准确,误差小于5%,同时消息重要程度感知的自适应队列管理策略策略能有效提高消息成功投递率,降低网络平均时延和网络负载率。

The network resources are limited in opportunistic networks. For improving the effectiveness of nodes＇ storage resources, this paper proposes a proper method to estimate node＇s activity degree. Based on the node＇s activity degree, we estimate the messages＇ importance degree, and then design a message importance degree aware adaptive queue management mechanism （MAQM） by the importance of message. This mechanism estimate node＇s activity degree by its meeting times with other nodes, and estimate messages＇ importance degree by node＇s activity degree . Simulation results show that the method to evaluate node＇s activity degree is accurate. Deviation is less than 5%. Tompared with other cache management mechanisms, MAQM can improve message delivery rate effectively, while reducing latency and overhead ratio.