基于自适应矢量压缩的机会网络高效低时延路由算法

发布时间：2018-11-07 06:44

【摘要】：针对采用epidemic机制的机会网络路由算法在汇总矢量(summary vector,SV)的交换、存储和请求矢量(request vector,RV)的交换过程中存在冗余开销影响效率的问题,提出一种基于自适应矢量压缩的路由算法(epidemic routing based on adaptive compression of vector,ERACV),所提算法通过采用自适应压缩SV和RV的长度、改进SV交换、收到SV分组后优先发送目的地为相遇节点的数据分组等新机制,减少控制开销和节点的存储开销,降低数据分组时延。理论分析验证了ERACV算法的有效性,仿真结果显示,与经典的感染路由算法分销及其改进后的消息传输控制算法相比,ERACV算法的控制和SV存储开销分别减少了39%和96.4%,数据分组的平均端到端时延则降低了2.5%以上,并且维持了100%的数据传送成功率。
[Abstract]:In order to solve the problem that redundancy overhead affects the efficiency of the switching, storage and request vector (request vector,RV) switching of summary vector (summary vector,SV) in the opportunistic network routing algorithm based on epidemic mechanism. A routing algorithm based on adaptive vector compression (epidemic routing based on adaptive compression of vector,ERACV) is proposed. The proposed algorithm improves SV switching by using adaptive compression of the length of SV and RV. After receiving the SV packet, we preferentially send the data packet to the encounter node, which reduces the control overhead and the storage overhead of the node, and reduces the delay of the data packet. The theoretical analysis verifies the effectiveness of the ERACV algorithm. The simulation results show that compared with the classical infection routing algorithm and the improved message transmission control algorithm, the control of the ERACV algorithm and the storage overhead of the SV algorithm are reduced by 39% and 96.4%, respectively. The average end-to-end delay of data packet is reduced by more than 2.5%, and the data transmission success rate of 100% is maintained.
【作者单位】：重庆邮电大学移动通信技术重庆市重点实验室;
【基金】：国家自然科学基金(60972068) 长江学者和创新团队发展计划基金(IRT1299) 重庆市自然科学基金(cstc2012jjA40051) 重庆市科委重点实验室专项经费(D2011-24) 应急通信重庆市重点实验室开放课题(201201)资助课题
【分类号】：TN929.5

【相似文献】