A Clustering Method for Wireless Sensor Networks with Heterogeneous Node Types
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- PRIYANKARA Sampath
- Department of Information Networking, Graduate School of Information Science and Technology, Osaka University
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- KINOSHITA Kazuhiko
- Department of Information Networking, Graduate School of Information Science and Technology, Osaka University
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- TODE Hideki
- Department of Computer Sciences and Intelligent Systems, Graduate School of Engineering, Osaka Prefecture University
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- MURAKAMI Koso
- Department of Information Networking, Graduate School of Information Science and Technology, Osaka University
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Description
Wireless Sensor Networks (WSNs) are gradually moving toward the adoption of clustered heterogeneous designs, incorporating a mixture of variety kinds of sensor nodes with different radio coverage and battery capacity. Compared with homogeneous networks, heterogeneous networks are able to reduce the initial cost of the network or prolong the network lifetime. The architecture and routing protocol for this type of heterogeneous WSN should be energy aware in order to prolong the lifetime of the network. However, most of the existing clustering methods consider only initial energy of the sensor nodes and ignore the non-uniform energy drainage caused by many-to-one traffic near sink and/or cluster heads in heterogeneous network environment. In this paper, we propose a new clustering method for WSN with heterogeneous node types which selects cluster heads considering not only the transmission power and residual energy of each node but also those of its adjacent nodes. Simulation experiments show that the proposed method increases network lifetime by 80% and 60% more than that of the CC and HEED, respectively.
Journal
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- IEICE Transactions on Communications
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IEICE Transactions on Communications E94-B (8), 2254-2264, 2011
The Institute of Electronics, Information and Communication Engineers
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Details 詳細情報について
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- CRID
- 1390282679351134848
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- NII Article ID
- 10030186990
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- NII Book ID
- AA10826261
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- BIBCODE
- 2011IEITC..94.2254P
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- ISSN
- 17451345
- 09168516
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed