An Efficient Neighbor Discovery Scheme for Mobile WSN

Mobile low-duty-cycle wireless sensor network (MLDC-WSN) is a new type of WSN that has emerged in recent years. It can deploy nodes on moving objects and use the object mobility to capture a wide range of dynamic environmental information. It has diverse applications and has the ability of mobility...

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Bibliographic Details
Published in:IEEE access 2019, Vol.7, p.4843-4855
Main Authors: Saraereh, Omar A., Khan, Imran, Lee, Byung Moo
Format: Article
Language:English
Subjects:
adaptive topology
Algorithms
Delay
Energy consumption
energy efficient nodes
network optimization
Network topologies
Nodes
Wireless networks
Wireless sensor networks
WSN
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Summary:Mobile low-duty-cycle wireless sensor network (MLDC-WSN) is a new type of WSN that has emerged in recent years. It can deploy nodes on moving objects and use the object mobility to capture a wide range of dynamic environmental information. It has diverse applications and has the ability of mobility and gets into sleep for a long time. However, the mobility and sleeping features of MLDC-WSN nodes result in dynamic network topology changes, which restricts discovering their neighbor nodes quickly. Thus, the optimal distribution decision is not established by the nodes. To solve this problem, in this paper, a novel selectively proactive neighbor discovery algorithm is proposed. The proposed algorithm enables the nodes when they wake up to search their neighbor nodes, which prevent the long-time waiting delay in the traditional passive neighbor discovery mechanism. Moreover, the proposed algorithm can further reduce the delay and acquire the accurate neighbor discovery results by quickly determining the next neighbor set at the next moment due to the prediction of the movement speed and distance of neighbors. The analytical and simulation results show that the proposed algorithm can effectively reduce the network energy consumption and delay and can determine all the neighbor nodes quickly and accurately as compared with the existing algorithms.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2886779