We consider a distributed storage problem in a large-scale wireless sensornetwork with $n$ nodes among which $k$ acquire (sense) independent data. Thegoal is to disseminate the acquired information throughout the network so thateach of the $n$ sensors stores one possibly coded packet and the original $k$data packets can be recovered later in a computationally simple way from any$(1+\epsilon)k$ of nodes for some small $\epsilon>0$. We propose two Raptorcodes based distributed storage algorithms for solving this problem. In thefirst algorithm, all the sensors have the knowledge of $n$ and $k$. In thesecond one, we assume that no sensor has such global information.
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机译：我们考虑具有$ n $个节点的大规模无线传感器网络中的分布式存储问题，其中$ k $个获取（感知）独立数据。目标是在整个网络上传播获取的信息，以便每个$ n $传感器存储一个可能的编码数据包，并且以后可以以计算简单的方式从任何$（1+ \ epsilon）k中恢复原始的$ k $ data数据包。较小的$ \ epsilon> 0 $的节点$。我们提出了两种基于Raptorcodes的分布式存储算法来解决此问题。在第一种算法中，所有传感器都具有$ n $和$ k $的知识。在第二个中，我们假设没有传感器具有这样的全局信息。
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