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    合作性DTN的基于系统效益的内容分发

    Data Dissemination Based on System Utility in Cooperative Delay Tolerant Networks

    • 摘要: 近年来在时延容忍网络(delay tolerant network,DTN)中的数据分发成为研究热点.由于DTN节点之间不存在持续的端到端连接,节点通常采用“存储-搬运-转发”的方式进行数据递交.当两个节点相接触时,节点如何为空间有限的缓存选择存储内容是一个关键问题,这关系到整个DTN网络的分发性能.但在分布式动态的DTN环境下,每个节点难以找到全局最优的存储选择.基于这个原因,全局效益最大化问题被转变为每次接触时的效益增益最大化问题,然后将转化后的问题形式化为0-1背包问题,并设计了一种启发式贪婪算法来进行求解,使得每个节点在与其他节点发生接触时,能够依据自身维护的局部网络信息来选取转发内容,从而最大化系统分发效益的增益.此外进一步详细分析了节点维护的网络信息的范围与节点对转发内容选择之间的关系.基于Trace的仿真结果表明,与SocialCast算法相比,启发式算法可以有效地提高节点对订阅内容的接收率和降低接收时延,并且随着节点维护的网络信息范围的增大系统效益也不断增大.

       

      Abstract: Data dissemination in delay tolerant networks (DTNs) has been extensively studied in recent years. The end-to-end path between any two nodes in DTNs suffers intermittence frequently, so the nodes exploit the store-carry-forward routing paradigm to communicate with others. When two nodes come into contact with each other, how to select data objects for buffering is a critical problem for each node, which affects the data dissemination performance of the system. Nodes in DTNs usually lack the global network information, so they cannot make the global optimal selection of data objects for buffering. In order to solve this problem, the global optimization problem is converted to an optimization problem under each contact, and the new problem can be formulated as 0-1 knapsack problem in this paper. A heuristic algorithm is proposed to solve this 0-1 knapsack problem and instructs nodes to selectively buffer data objects for maximizing the gain in system utility even when nodes maintain local network information. Furthermore, this paper investigates the relationship between the decisions made by the nodes and the scope of network information they maintain. Extensive trace-driven simulations based on MIT trace are conducted to evaluate the performance of our heuristic algorithm. The results demonstrate that our heuristic algorithm can achieve better performance than SocialCast algorithm. And the simulation results also show that the larger scope of network information the nodes maintain, the better performance our heuristic algorithm can achieve.

       

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