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arXiv 0902.1278cs.ITcs.DScs.NImath.IT
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基于喷泉码的大规模无线传感器网络分布式存储算法

Fountain Codes Based Distributed Storage Algorithms for Large-scale Wireless Sensor Networks

Salah A. Aly, Zhenning Kong, Emina Soljanin

摘要:

我们考虑具有n个节点的大规模传感器网络,其中k个节点拥有,(例如,已经感测或以某种其它方式收集)k个信息分组。在网络节点由于例如有限的能量或恶劣的环境而易受攻击的场景中,期望在整个网络中传播所获取的信息,使得n个节点中的每个节点存储一个(可能编码的)分组,并且对于某个小ε> 0,可以稍后以计算简单的方式从任何(1 + ε)k个节点恢复原始k个源分组。我们开发了两个分布式算法来解决这个问题的基础上简单的随机游动和喷泉码。与所有以前开发的计划,我们的解决方案是真正的分布式,也就是说,节点不知道在网络中的n,k或连接,除了在自己的社区,他们不维护任何路由表。在第一种算法中,所有传感器都知道n和k。在第二种算法中,每个传感器通过随机游走传播估计这些参数。本文分析了这两种算法的通信/传输和编解码复杂度,并给出了大量的仿真结果

英文摘要:

We consider large-scale sensor networks with n nodes, out of which k are in possession, (e.g., have sensed or collected in some other way) k information packets. In the scenarios in which network nodes are vulnerable because of, for example, limited energy or a hostile environment, it is desirable to disseminate the acquired information throughout the network so that each of the n nodes stores one (possibly coded) packet and the original k source packets can be recovered later in a computationally simple way from any (1 + ε)k nodes for some small ε> 0. We developed two distributed algorithms for solving this problem based on simple random walks and Fountain codes. Unlike all previously developed schemes, our solution is truly distributed, that is, nodes do not know n, k or connectivity in the network, except in their own neighborhoods, and they do not maintain any routing tables. In the first algorithm, all the sensors have the knowledge of n and k. In the second algorithm, each sensor estimates these parameters through the random walk dissemination. We present analysis of the communication/transmission and encoding/decoding complexity of these two algorithms, and provide extensive simulation results as well

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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