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MND: An Information of Detected Neighbors Based Multi-channel Neighbor Discovery Protocol for Wireless Sensor Networks

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Part of the book series:Communications in Computer and Information Science ((CCIS,volume 334))

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Abstract

Multi-channel neighbor discovery protocol based on information of detected neighbors for wireless sensor networks is proposed in this paper, called MND. To make sure that the discovery among nodes is as quick as possible, MND uses the schedule mechanism in which the nodes compute the potential neighbors set so as to calculate the sleep and wake schedule of the node. To minimize the influence of channel conflict to the performance, MND uses multi-channel mechanism and calculates the required total number of channels according to the duty cycle and network density. Through analysis, we can get how to choose the total number of channels for each node and the fact that the common neighbor node of the neighbors of a node is the neighbor of this node in a large probability. The simulation and test-bed experiment results show the discovery rate and discovery latency of MND is higher and lower, respectively.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Key Laboratory of Database and Parallel Computing, Heilongjiang University, Harbin, 150080, Heilongjiang Province, China

    Jinbao Li, Zhigang Wang, Liang Yao & Longjiang Guo

Authors
  1. Jinbao Li
  2. Zhigang Wang
  3. Liang Yao
  4. Longjiang Guo

Editor information

Editors and Affiliations

  1. College of Computer, Nanjing University of Posts and Telecommunications, 66 Xin Mofan Road, Mailbox 157, 210003, Nanjing, China

    Ruchuan Wang  & Fu Xiao  & 

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Li, J., Wang, Z., Yao, L., Guo, L. (2013). MND: An Information of Detected Neighbors Based Multi-channel Neighbor Discovery Protocol for Wireless Sensor Networks. In: Wang, R., Xiao, F. (eds) Advances in Wireless Sensor Networks. CWSN 2012. Communications in Computer and Information Science, vol 334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36252-1_16

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  • Available as PDF
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Price includes VAT (Japan)
  • Compact, lightweight edition
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