A Mutual Algorithm for Optimizing Distributed Source Coding in Wireless Sensor Networks
Wireless Sensor Networks (WSNs) are composed of small wireless nodes equipped with sensors, a processor, and a radio communication unit, all normally powered by batteries. For most WSN applications, the network is expected to function for several months or years. In the common monitoring application...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2012-02-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2012/783798 |
| Summary: | Wireless Sensor Networks (WSNs) are composed of small wireless nodes equipped with sensors, a processor, and a radio communication unit, all normally powered by batteries. For most WSN applications, the network is expected to function for several months or years. In the common monitoring application scenario, adjacent nodes in a WSN often sense spatially correlated data. Suppressing this correlation can significantly improve the lifetime of the network. The maximum possible network data compression can be achieved using distributed source coding (DSC) techniques when nodes encode at Slepian-Wolf rates. This paper presents contributions to the lifetime optimization problem of WSNs in the form of two algorithms: the Updated-CMAX (UCMAX) power-aware routing algorithm to optimize the routing tree and the Rate Optimization (RO) algorithm to optimize the encoding rates of the nodes. The two algorithms combined offer a solution that maximizes the lifetime of a WSN measuring spatially correlated data. Simulations show that our proposed approach may significantly extend the lifetime of multihop WSNs with nodes that are observing correlated data. |
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| ISSN: | 1550-1477 |