Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

A dynamic harmony search-based fuzzy clustering protocol for energy-efficient wireless sensor networks

A dynamic harmony search-based fuzzy clustering protocol for energy-efficient wireless sensor... In the development of cluster-based energy-efficient protocols for wireless sensor networks (WSNs), a particularly challenging problem is the dynamic organization of sensors into a wireless communication network and the routing of sensed information from the field sensors to a remote base station (BS) in a manner that prolongs the lifetime of WSNs. This paper presents a new energy-efficient clustering protocol for WSNs, which can minimize total network energy dissipation while maximizing network lifetime. The protocol is divided into two parts. The first deals with constructing an infrastructure for the given WSN. A newly developed algorithm, based on a harmony search (HS), automatically determines the optimal number of clusters and allocates sensors into these clusters. This algorithm also eliminates the need to set the number of clusters a priori. The second part is concerned with the process of sending sensed data from nodes to their cluster head and then to the BS. A decentralized fuzzy clustering algorithm is proposed, where the selection of cluster heads in each round is locally made in each cluster during the network lifetime. Simulation results demonstrate that the proposed protocol can achieve an optimal number of clusters, prolong the network lifetime and increase the data delivery at the BS, when compared to other well-known clustering-based routing protocols. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Telecommunications Springer Journals

A dynamic harmony search-based fuzzy clustering protocol for energy-efficient wireless sensor networks

Alia, Osama
Annals of Telecommunications , Volume 73 (6) – Oct 10, 2017
Download PDF
13 pages
Read Article

Loading next page...
 
/lp/springer_journal/a-dynamic-harmony-search-based-fuzzy-clustering-protocol-for-energy-OhN01jTZng
Publisher
Springer Journals
Copyright
Copyright © 2017 by Institut Mines-Télécom and Springer-Verlag France SAS
Subject
Engineering; Communications Engineering, Networks; Information Systems and Communication Service; Signal,Image and Speech Processing; Computer Communication Networks; Information and Communication, Circuits; R & D/Technology Policy
ISSN
0003-4347
eISSN
1958-9395
DOI
10.1007/s12243-017-0611-6
Publisher site
See Article on Publisher Site

Abstract

In the development of cluster-based energy-efficient protocols for wireless sensor networks (WSNs), a particularly challenging problem is the dynamic organization of sensors into a wireless communication network and the routing of sensed information from the field sensors to a remote base station (BS) in a manner that prolongs the lifetime of WSNs. This paper presents a new energy-efficient clustering protocol for WSNs, which can minimize total network energy dissipation while maximizing network lifetime. The protocol is divided into two parts. The first deals with constructing an infrastructure for the given WSN. A newly developed algorithm, based on a harmony search (HS), automatically determines the optimal number of clusters and allocates sensors into these clusters. This algorithm also eliminates the need to set the number of clusters a priori. The second part is concerned with the process of sending sensed data from nodes to their cluster head and then to the BS. A decentralized fuzzy clustering algorithm is proposed, where the selection of cluster heads in each round is locally made in each cluster during the network lifetime. Simulation results demonstrate that the proposed protocol can achieve an optimal number of clusters, prolong the network lifetime and increase the data delivery at the BS, when compared to other well-known clustering-based routing protocols.

Journal

Annals of Telecommunications – Springer Journals

Published: Oct 10, 2017

References

  • Wireless sensor networks: a survey
    Akyildiz, IF; Su, W; Sankarasubramaniam, Y; Cayirci, E
  • A novel traffic identification approach based on multifractal analysis and combined neural network
    Shi, H; Liang, G; Wang, H
  • Time and energy efficient relay transmission for multi-hop wireless sensor networks
    Kim, JW; Barrado, JRR; Jeon, DK
  • Farooq swarm intelligence based routing protocol for wireless sensor networks: survey and future directions
    Saleem, M; Di Caro, GA
  • Adaptive routing for dynamic on-body wireless sensor networks
    Maskooki, A; Soh, CB; Gunawan, E; Low, KS
  • An energy aware algorithm for OLSR clustering
    Loutfi, A; Elkoutbi, M; BenOthman, J; Kobbane, A
  • Energy-efficient boarder node medium access control protocol for wireless sensor networks
    Razaque, A; Elleithy, KM
  • Particle swarm optimization in wireless-sensor networks: a brief survey
    Kulkarni, RV; Venayagamoorthy, GK
  • DEC-MAC: delay-and energy-aware cooperative medium access control protocol for wireless sensor networks
    Ahmed, MHU; Razzaque, MA; Hong, CS
  • FuGeF: a resource bound secure forwarding protocol for wireless sensor networks
    Umar, IA; Mohd Hanapi, Z; Sali, A; Zulkarnain, ZA
  • Wireless sensor network survey
    Yick, J; Mukherjee, B; Ghosal, D
  • Routing techniques in wirless sensor networks: a survey
    Al-Karaki, JN; Kamal, AE
  • A survey on clustering routing protocols in wireless sensor networks
    Liu, X
  • Dynamic relocation of mobile BS in wireless sensor networks using a cluster-based harmony search algorithm
    Alia, OM
  • An effective and robust decentralized target tracking scheme in wireless camera sensor networks
    Fu, P; Cheng, Y; Tang, H; Li, B; Pei, J; Yuan, X
  • A power-efficient clustering protocol for coal mine face monitoring with wireless sensor networks under channel fading conditions
    Ren, P; Qian, J
  • A smart and balanced energy-efficient multihop clustering algorithm (smart-BEEM) for MIMO IoT systems in future networks
    Xu, L; O’Hare, GM; Collier, R
  • A local energy consumption prediction-based clustering protocol for wireless sensor networks
    Yu, J; Feng, L; Jia, L; Gu, X; Yu, D
  • An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks
    Mustapha, I; Ali, BM; Rasid, MFA; Sali, A; Mohamad, H
  • A novel energy-aware distributed clustering algorithm for heterogeneous wireless sensor networks in the mobile environment
    Gao, Y; Wkram, CH; Duan, J; Chou, J
  • A survey on an energy-efficient and energy-balanced routing protocol for wireless sensor networks
    Ogundile, OO; Alfa, AS
  • An application-specific protocol architecture for wireless microsensor networks
    Heinzelman, WB; Chandrakasan, AP; Balakrishnan, H
  • HEED: A hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networks
    Younis, O; Fahmy, S
  • Design of a distributed energy efficient clustering algorithm for heterogeneous wireless sensor networks
    Qing, L; Zhu, Q; Wang, M
  • Data gathering algorithms in sensor networks using energy metrics
    Lindsey, S; Raghavendra, C; Sivalingam, KM
  • Distance-based and low energy adaptive clustering protocol for wireless sensor networks
    Liaqat, M; Gani, A; Anisi, MH; Ab Hamid, SH; Akhunzada, A; Khan, MK; Ali, RL
  • Fuzzy-logic based distributed energy-efficient clustering algorithm for wireless sensor networks
    Zhang, Y; Wang, J; Han, D; Wu, H; Zhou, R
  • DCPVP: distributed clustering protocol using voting and priority for wireless sensor networks
    Hematkhah, H; Kavian, YS
  • 2017 DCE: a distributed energy-efficient clustering protocol for wireless sensor network based on double-phase cluster-head election
    Han, R; Yang, W; Wang, Y; You, K
  • A hybrid harmony search algorithm for MRI brain segmentation
    Alia, OM; Mandava, R; Aziz, M
  • A survey of evolutionary algorithms for clustering
    Hruschka, ER; Campello, RJ; Freitas, AA; Carvalho, AC
  • Genetic algorithms and grouping problems
    Falkenauer, E
  • Competitive swarm optimizer based gateway deployment algorithm in cyber-physical systems
    Huang, S; Tao, M
  • Cost-effective encryption-based autonomous routing protocol for efficient and secure wireless sensor networks
    Saleem, K; Derhab, A; Orgun, MA; Al-Muhtadi, J; Rodrigues, JJ; Khalil, MS; Ali Ahmed, A
  • A new heuristic optimization algorithm: harmony search
    Geem, ZW; Kim, JH; Loganathan, GV
  • Maximizing wireless sensor network coverage with minimum cost using harmony search algorithm
    Alia, OM; Al-Ajouri, A
  • The variants of the harmony search algorithm: an overview
    Alia, OM; Mandava, R
  • Energy-scalable protocols for battery-operated microsensor networks
    Wang, A; Heinzelman, WB; Sinha, A; Chandrakasan, AP
  • Validity index for crisp and fuzzy clusters
    Pakhira, MK; Bandyopadhyay, S; Maulik, U
  • Pattern recognition with fuzzy objective function algorithms
    Bezdek, JC
  • On fuzzy cluster validity indices
    Wang, W; Zhang, Y
  • On clustering validation techniques
    Halkidi, M; Batistakis, Y; Vazirgiannis, M