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A Two-Tier Distributed Fuzzy Logic Based Protocol for Efficient Data Aggregation in Multihop Wireless Sensor Networks
Date
2018-12-01
Author
SERT, SEYYİT ALPER
Alchihabi, Abdullah
Yazıcı, Adnan
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This study proposes a two-tier distributed fuzzy logic based protocol (TTDFP) to improve the efficiency of data aggregation operations in multihop wireless sensor networks (WSNs). Clustering is utilized for efficient aggregation requirements in terms of consumed energy. In a clustered network, member (leaf) nodes transmit obtained data to cluster-heads (CHs) and CHs relay received packets to the base station. In multihop wireless networks, this CH-generated transmission occurs over other CHs. Due to the adoption of a multihop topology, hotspots and/or energy-hole problems may arise. This article proposes a TTDFP to extend the lifespan of multihop WSNs by taking the efficiency of clustering and routing phases jointly into account. TTDFP is a distribution-adaptive protocol that runs and scales sensor network applications efficiently. Additionally, along with the two-tier fuzzy logic based protocol, we utilize an optimization framework to tune the parameters used in the fuzzy clustering tier in order to optimize the performance of a given WSN. This paper also includes performance comparisons and experimental evaluations with the selected state-of-the-art algorithms. The experimental results reveal that TTDFP performs better than any other protocols under the same network setup considering metrics used for comparing energy-efficiency and network lifespan of the protocols.
Subject Keywords
Control and Systems Engineering
,
Computational Theory and Mathematics
,
Applied Mathematics
,
Artificial Intelligence
URI
https://hdl.handle.net/11511/36306
Journal
IEEE TRANSACTIONS ON FUZZY SYSTEMS
DOI
https://doi.org/10.1109/tfuzz.2018.2841369
Collections
Department of Computer Engineering, Article
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S. A. SERT, A. Alchihabi, and A. Yazıcı, “A Two-Tier Distributed Fuzzy Logic Based Protocol for Efficient Data Aggregation in Multihop Wireless Sensor Networks,”
IEEE TRANSACTIONS ON FUZZY SYSTEMS
, pp. 3615–3629, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/36306.