Title | ||
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An Efficient Centroid-Based Routing Protocol for Energy Management in WSN-Assisted IoT. |
Abstract | ||
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Wireless sensor networks (WSNs) distribute hundreds to thousands of inexpensive micro sensor nodes in their regions, and these nodes are important parts of Internet of Things (IoT). In WSN-assisted IoT, the nodes are resource constrained in many ways, such as storage resources, computing resources, energy resources, and so on. Robust routing protocols are required to maintain a long network lifetime and achieve higher energy utilization. In this paper, we propose a new energy-efficient centroidbased routing protocol (EECRP) for WSN-assisted IoT to improve the performance of the network. The proposed EECRP includes three key parts: a new distributed cluster formation technique that enables the self-organization of local nodes, a new series of algorithms for adapting clusters and rotating the cluster head based on the centroid position to evenly distribute the energy load among all sensor nodes, and a new mechanism to reduce the energy consumption for long-distance communications. In particular, the residual energy of nodes is considered in EECRP for calculating the centroid's position. Our simulation results indicate that EECRP performs better than LEACH, LEACH-C, and GEEC. In addition, EECRP is suitable for networks that require a long lifetime and whose base station (BS) is located in the network. |
Year | DOI | Venue |
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2017 | 10.1109/ACCESS.2017.2749606 | IEEE ACCESS |
Keywords | Field | DocType |
Internet of Things,wireless sensor networks,energy management,cluster | Base station,Key distribution in wireless sensor networks,Energy management,Link-state routing protocol,Computer science,Computer network,Mobile wireless sensor network,Energy consumption,Wireless sensor network,Distributed computing,Routing protocol | Journal |
Volume | ISSN | Citations |
5 | 2169-3536 | 7 |
PageRank | References | Authors |
0.45 | 19 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jian Shen | 1 | 1285 | 101.27 |
Anxi Wang | 2 | 23 | 5.12 |
Chen Wang | 3 | 53 | 7.23 |
Patrick C. K. Hung | 4 | 655 | 74.68 |
Chin-Feng Lai | 5 | 973 | 74.85 |