Identifying Energy Holes in Randomly Deployed Hierarchical Wireless Sensor Networks
This paper proposes a novel protocol, called an aggregation-based topology learning (ATL) protocol, to identify energy holes in a randomly deployed hierarchical wireless sensor network (HWSN). The approach taken in the protocol design is to learn the routing topology of a tree-structured HWSN in rea...
Main Authors: | Ayesha Naureen, Ning Zhang, Steve Furber |
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Format: | Article |
Language: | English |
Published: |
IEEE
2017-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8047942/ |
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