1 research outputs found
Distributed Data Storage in Large-Scale Sensor Networks Based on LT Codes
This paper proposes an algorithm for increasing data persistency in
large-scale sensor networks. In the scenario considered here, k out of n nodes
sense the phenomenon and produced ? information packets. Due to usually
hazardous environment and limited resources, e.g. energy, sensors in the
network are vulnerable. Also due to the large size of the network, gathering
information from a few central hopes is not feasible. Flooding is not a desired
option either due to limited memory of each node. Therefore the best approach
to increase data persistency is propagating data throughout the network by
random walks. The algorithm proposed here is based on distributed LT (Luby
Transform) codes and it benefits from the low complexity of encoding and
decoding of LT codes. In previous algorithms the essential global information
(e.g., n and k) are estimated based on graph statistics, which requires
excessive transmissions. In our proposed algorithm, these values are obtained
without additional transmissions. Also the mixing time of random walk is
enhanced by proposing a new scheme for generating the probabilistic forwarding
table of random walk. The proposed method uses only local information and it is
scalable to any network topology. By simulations the improved performance of
developed algorithm compared to previous ones has been verified.Comment: 9 pages, 4 figures, 2 table