An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic Theory
Clustering is an effective method for reducing energy consumption in wireless sensor networks (WSNs). In a multihop clustered network scenario, each sensor node transmits data to its own cluster head (CH), and the CH aggregates the data from its member nodes and forwards it to the base station (BS)...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9244067/ |
| _version_ | 1818930530206351360 |
|---|---|
| author | Yang Tao Jinming Zhang Liu Yang |
| author_facet | Yang Tao Jinming Zhang Liu Yang |
| author_sort | Yang Tao |
| collection | DOAJ |
| description | Clustering is an effective method for reducing energy consumption in wireless sensor networks (WSNs). In a multihop clustered network scenario, each sensor node transmits data to its own cluster head (CH), and the CH aggregates the data from its member nodes and forwards it to the base station (BS) via other CHs. However, the “hot spot” problem is prone to occur in clustered WSNs because CHs closer to the BS have heavier intercluster forwarding tasks. To address this problem, this paper proposes an unequal clustering algorithm based on interval type-2 TSK fuzzy logic theory (UCT2TSK). The relative distance to the BS (RDB), residual energy (RE), and node density (ND) are considered as the inputs of an interval type-2 fuzzy logic system (FLS). Through fuzzy reasoning, outputs are acquired that can be used to optimize the CHs and determine the cluster sizes. Simulation results verify that UCT2TSK can effectively balance energy consumption and enhance energy efficiency because it has better performance in network lifetime and network throughput than other classical and recent clustering algorithms. |
| first_indexed | 2024-12-20T04:02:09Z |
| format | Article |
| id | doaj.art-3913993774384cbdb258a065596c02e5 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T04:02:09Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-3913993774384cbdb258a065596c02e52022-12-21T19:54:08ZengIEEEIEEE Access2169-35362020-01-01819717319718310.1109/ACCESS.2020.30346079244067An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic TheoryYang Tao0https://orcid.org/0000-0002-9535-464XJinming Zhang1https://orcid.org/0000-0001-9671-6422Liu Yang2https://orcid.org/0000-0002-9450-5469School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaSchool of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, ChinaClustering is an effective method for reducing energy consumption in wireless sensor networks (WSNs). In a multihop clustered network scenario, each sensor node transmits data to its own cluster head (CH), and the CH aggregates the data from its member nodes and forwards it to the base station (BS) via other CHs. However, the “hot spot” problem is prone to occur in clustered WSNs because CHs closer to the BS have heavier intercluster forwarding tasks. To address this problem, this paper proposes an unequal clustering algorithm based on interval type-2 TSK fuzzy logic theory (UCT2TSK). The relative distance to the BS (RDB), residual energy (RE), and node density (ND) are considered as the inputs of an interval type-2 fuzzy logic system (FLS). Through fuzzy reasoning, outputs are acquired that can be used to optimize the CHs and determine the cluster sizes. Simulation results verify that UCT2TSK can effectively balance energy consumption and enhance energy efficiency because it has better performance in network lifetime and network throughput than other classical and recent clustering algorithms.https://ieeexplore.ieee.org/document/9244067/Wireless sensor networkunequal clusteringtype-2 TSK fuzzy logic theory |
| spellingShingle | Yang Tao Jinming Zhang Liu Yang An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic Theory IEEE Access Wireless sensor network unequal clustering type-2 TSK fuzzy logic theory |
| title | An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic Theory |
| title_full | An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic Theory |
| title_fullStr | An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic Theory |
| title_full_unstemmed | An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic Theory |
| title_short | An Unequal Clustering Algorithm for Wireless Sensor Networks Based on Interval Type-2 TSK Fuzzy Logic Theory |
| title_sort | unequal clustering algorithm for wireless sensor networks based on interval type 2 tsk fuzzy logic theory |
| topic | Wireless sensor network unequal clustering type-2 TSK fuzzy logic theory |
| url | https://ieeexplore.ieee.org/document/9244067/ |
| work_keys_str_mv | AT yangtao anunequalclusteringalgorithmforwirelesssensornetworksbasedonintervaltype2tskfuzzylogictheory AT jinmingzhang anunequalclusteringalgorithmforwirelesssensornetworksbasedonintervaltype2tskfuzzylogictheory AT liuyang anunequalclusteringalgorithmforwirelesssensornetworksbasedonintervaltype2tskfuzzylogictheory AT yangtao unequalclusteringalgorithmforwirelesssensornetworksbasedonintervaltype2tskfuzzylogictheory AT jinmingzhang unequalclusteringalgorithmforwirelesssensornetworksbasedonintervaltype2tskfuzzylogictheory AT liuyang unequalclusteringalgorithmforwirelesssensornetworksbasedonintervaltype2tskfuzzylogictheory |