| Wireless sensor networks(WSNs) is a network formed by a large number of nodes spontaneously, it gathers information collection, processing and transmission as a whole, and has been widely deployed in environmental monitoring, habitat monitoring and seismic exploration and so on. The energy is limited in a WSNs, and the data transmission consumes the most of the energy. Therefore, how to reduce the energy consumption of data transmission has become a key issue in WSNs. Based on the research of clustering protocols and data compression techniques, which are two ways of energy saving technologies in WSNs, and combined with the regional distribution of the characteristics presented in WSNs environment, this paper proposed the sensor similar-based clustering algorithm(SSC) and minimum transmission cost-based routing algorithm(MTCR). and Proposed the SSC-based Data Compression and Transmission(SSCDCT)。The main works of this paper is as follows:1) Proposed the SSC. With deep research of the regional distribution in WSNs, we proposed a model of sensor similar measurements, and then proposed the SSC based this model. SSC groups the similar sensors in a region into the same cluster, improving the similarity among the sensing data, and the data compression works-to mine and eliminate more redundant data among those sensors, and reduce the amount of data being transmitted.2) Proposed the MTCR. Combining the disadvantages of one hop router in intra-cluster and inter-cluster in the large scale WSNs with the schema of energy consumption in data transmission, we proposed a new router protocol, MTCR. Through controlling the coverage area and in-degree, the WSNs can transmit data both 1-hop and multi-hops. MTCR reduces and balances the transmission energy consumption in WSNs with the maximum efforts.3) Proposed the SSC-based Data Compression and Transmission(SSCDCT). SSCDCT uses SSC to group the similar sensors into clusters, and compresses their sensing data, then transmits the compressed data with MTCR. SSCDCT departs the data compression and transmission into three layers, the layers work cooperatively to minimize the amount of data and transmission consumption, and reach the goals of extending the network lifetime.Experiments and cases show that, compared with LEACH protocol, the average similarity of magnitude and trend among the cluster nodes of SSC is improved by more than 15% and 8% respectively; Compared with LEACH, LEACH-C and PEGASIS, the MTCR can prolong the first node dead(FND) and the half node dead(HND) by at least 14.3% and 25.5% respectively; compared with the compression and transmission schema embedded with LEACH-C, SSCDCT can prolong FND by 12.1% and HND by 14.5% at least. |
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