机会网络中高效的数据分发机制——CRLNC

CRLNC:Efficient Data Dissemination Mechanism For Opportunistic Network

针对如何提高机会网络中数据分发效率的问题,提出了一种数据分簇和随机线性网络编码结合的数据分发机制——CRLNC。其核心思想是先将数据分成几簇,然后在簇内分成相同数量的数据块,源节点发送一簇中的数据块,中间节点运用随机线性编码算法将其中的数据块编码转发出去,目标节点接收到其中的编码数据块后采用高斯—约旦消元法将数据渐进还原。在这种数据分发机制中,针对节点缓存空间的冗余问题提出一种基于簇号和线性相关性的节点缓存策略。理论分析和仿真结果证明,与传统的数据分发相比,该算法可以有效地提高网络吞吐量,减小端到端的时延。

Aiming at improving the efficiency of data dissemination in opportunistic network, an efficient data dissemination mechanism combined with clustering and random linear network coding is proposed. The core idea is dividing the data into several clusters firstly, and then dividing each cluster in- to the same number of data blocks, the source node sends the data blocks in each cluster, the intermediate node encodes the data blocks with random lin- ear coding algorithm and then forwards the encoded data block, the destination node uses Gauss-Jordan elimination method to restore the data progres- sively after receiving the encoded data blocks. Aiming at the redundancy of node cache space, this data dissemination mechanism proposes a node cac- hing strategy based on cluster number and linear correlation. Theoretical analysis and simulation results show that CRLNC outperforms the traditional data dissemination mechanism, CRLNC mechanism effectively improves network throughput and reduces the end-to-end delay.