Improved metaheuristic-based energy-efficient clustering protocol with optimal base station location in wireless sensor networks
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Improved metaheuristic-based energy-efficient clustering protocol with optimal base station location in wireless sensor networks
Authors
Keywords
Wireless sensor networks, Energy-efficient clustering, Improved artificial bee colony (iABC) metaheuristic
Journal
SOFT COMPUTING
Volume -, Issue -, Pages -
Publisher
Springer Nature
Online
2017-09-13
DOI
10.1007/s00500-017-2815-0
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A power efficient cluster-based routing algorithm for wireless sensor networks: Honeybees swarm intelligence based approach
- (2016) Ado Adamou Abba Ari et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- A rule-driven multi-path routing algorithm with dynamic immune clustering for event-driven wireless sensor networks
- (2016) Yongsheng Ding et al. NEUROCOMPUTING
- Differential Evolution with Population and Strategy Parameter Adaptation
- (2015) V. Gonuguntla et al. MATHEMATICAL PROBLEMS IN ENGINEERING
- Energy efficient clustering and routing algorithms for wireless sensor networks: Particle swarm optimization approach
- (2014) Pratyay Kuila et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Real-Time Implementation of a Harmony Search Algorithm-Based Clustering Protocol for Energy-Efficient Wireless Sensor Networks
- (2013) Duc Chinh Hoang et al. IEEE Transactions on Industrial Informatics
- A global best artificial bee colony algorithm for global optimization
- (2012) Weifeng Gao et al. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
- A Novel Artificial Bee Colony Algorithm Based on Modified Search Equation and Orthogonal Learning
- (2012) Wei-feng Gao et al. IEEE Transactions on Cybernetics
- A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks
- (2011) Bara’a A. Attea et al. APPLIED SOFT COMPUTING
- Development and investigation of efficient artificial bee colony algorithm for numerical function optimization
- (2011) Guoqiang Li et al. APPLIED SOFT COMPUTING
- An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times
- (2011) Rui Zhang et al. Entropy
- A distributed energy-efficient clustering algorithm with improved coverage in wireless sensor networks
- (2011) Zhixin Liu et al. Future Generation Computer Systems-The International Journal of eScience
- Improved artificial bee colony algorithm for global optimization
- (2011) Weifeng Gao et al. INFORMATION PROCESSING LETTERS
- A survey on coverage and connectivity issues in wireless sensor networks
- (2011) Chuan Zhu et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks
- (2011) Enan A. Khalil et al. Swarm and Evolutionary Computation
- Computational Intelligence in Wireless Sensor Networks: A Survey
- (2010) Raghavendra V. Kulkarni et al. IEEE Communications Surveys and Tutorials
- Differential Evolution: A Survey of the State-of-the-Art
- (2010) Swagatam Das et al. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
- A Multipath Routing Protocol Based on Clustering and Ant Colony Optimization for Wireless Sensor Networks
- (2010) Jing Yang et al. SENSORS
- A distributed energy-efficient clustering protocol for wireless sensor networks
- (2009) Ali Chamam et al. COMPUTERS & ELECTRICAL ENGINEERING
- EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks
- (2008) Dilip Kumar et al. COMPUTER COMMUNICATIONS
- Wireless sensor network survey
- (2008) Jennifer Yick et al. Computer Networks
- Real-Valued Compact Genetic Algorithms for Embedded Microcontroller Optimization
- (2008) E. Mininno et al. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
- On the performance of artificial bee colony (ABC) algorithm
- (2007) D. Karaboga et al. APPLIED SOFT COMPUTING
- EEMC: An energy-efficient multi-level clustering algorithm for large-scale wireless sensor networks
- (2007) Yan Jin et al. Computer Networks
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started