• Title/Summary/Keyword: Hierarchical Unequal Clustering Method

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An Energy Consumption Model using Hierarchical Unequal Clustering Method (계층적 불균형 클러스터링 기법을 이용한 에너지 소비 모델)

  • Kim, Jin-Su;Shin, Seung-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.6
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    • pp.2815-2822
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    • 2011
  • Clustering method in wireless sensor networks is the technique that forms the cluster to aggregate the data and transmit them at the same time that they can use the energy efficiently. In this paper, I propose the hierarchical unequal clustering method using cluster group model. This divides the entire network into two layers. The data aggregated from layer 2 consisted of cluster group is sent to layer 1, after re-aggregation the total data is sent to base station. This method decreases whole energy consumption by using cluster group model with multi-hop communication architecture. Hot spot problem can be solved by establishing unequal cluster. I also show that proposed hierarchical unequal clustering method is better than previous clustering method at the point of network energy efficiency.

Distance Aware Intelligent Clustering Protocol for Wireless Sensor Networks

  • Gautam, Navin;Pyun, Jae-Young
    • Journal of Communications and Networks
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    • v.12 no.2
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    • pp.122-129
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    • 2010
  • Energy conservation is one of the most important issues for evaluating the performance of wireless sensor network (WSN) applications. Generally speaking, hierarchical clustering protocols such as LEACH, LEACH-C, EEEAC, and BCDCP are more efficient in energy conservation than flat routing protocols. However, these typical protocols still have drawbacks of unequal and high energy depletion in cluster heads (CHs) due to the different transmission distance from each CH to the base station (BS). In order to minimize the energy consumption and increase the network lifetime, we propose a new hierarchical routing protocol, distance aware intelligent clustering protocol (DAIC), with the key concept of dividing the network into tiers and selecting the high energy CHs at the nearest distance from the BS. We have observed that a considerable amount of energy can be conserved by selecting CHs at the nearest distance from the BS. Also, the number of CHs is computed dynamically to avoid the selection of unnecessarily large number of CHs in the network. Our simulation results showed that the proposed DAIC outperforms LEACH and LEACH-C by 63.28% and 36.27% in energy conservation respectively. The distance aware CH selection method adopted in the proposed DAIC protocol can also be adapted to other hierarchical clustering protocols for the higher energy efficiency.