Lifetime Improvement in Wireless Sensor Networks using Hybrid Differential Evolution and Simulated Annealing (DESA)
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TLDR
The proposed DESA reduces the number of dead nodes than Low Energy Adaptive Clustering Hierarchy (LEACH) by 70%, Harmony Search Algorithm (HSA), modified HSA by 40% and differential evolution by 60%.About:
This article is published in Ain Shams Engineering Journal.The article was published on 2016-05-13 and is currently open access. It has received 66 citations till now. The article focuses on the topics: Wireless sensor network & Cluster analysis.read more
Citations
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Journal ArticleDOI
Strategies based on various aspects of clustering in wireless sensor networks using classical, optimization and machine learning techniques: Review, taxonomy, research findings, challenges and future directions
TL;DR: A brief review in the field of clustering in wireless sensor networks based on three different categories, such as classical, optimization, and machine learning techniques, including cluster head selection, routing protocols, reliability, security, and unequal clustering.
Journal ArticleDOI
Hybrid Artificial Bee Colony and Monarchy Butterfly Optimization Algorithm (HABC-MBOA)-based Cluster Head Selection for WSNs
TL;DR: A Hybrid Artificial Bee Colony and Monarchy Butterfly Optimization Algorithm (HABC-MBOA)-based Cluster Head Selection Scheme is proposed for the predominant selection of cluster heads under clustering process and plays an anchor role in eliminating inadequacy of ABC algorithm towards global search potential.
Journal ArticleDOI
Moth Flame Clustering Algorithm for Internet of Vehicle (MFCA-IoV)
Muhammad Fahad Khan,Farhan Aadil,Muazzam Maqsood,Syed Hashim Raza Bukhari,Maqbool Hussain,Yunyoung Nam +5 more
TL;DR: A novel technique based on moth flame clustering algorithm for IoV (MFCA-IoV) is proposed, which generates optimized clusters for robust transmission and is evaluated experimentally with renowned techniques.
Journal ArticleDOI
A Hybrid Grey Wolf and Crow Search Optimization Algorithm-Based Optimal Cluster Head Selection Scheme for Wireless Sensor Networks
TL;DR: A hybrid grey wolf and crow search optimization algorithm-based optimal cluster head selection (HGWCSOA-OCHS) scheme was proposed for enhancing the lifetime expectancy of the network by concentrating on the minimization of delay, minimizationof distance between nodes and energy stabilization.
Journal ArticleDOI
Routing Protocol for Heterogeneous Wireless Sensor Networks Based on a Modified Grey Wolf Optimizer.
TL;DR: The experimental results indicate that the network lifecycle of the HMGWO protocol improves by 55.7%, 31.9%, 46.3%, and 27.0%, respectively, compared with the stable election protocol, distributed energy-efficient clustering algorithm, modified SEP (M-SEP), and fitness-value-based improved GWO (FIGWO) protocols.
References
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Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Journal ArticleDOI
A survey on sensor networks
TL;DR: The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections.
Proceedings ArticleDOI
Energy-efficient communication protocol for wireless microsensor networks
TL;DR: The Low-Energy Adaptive Clustering Hierarchy (LEACH) as mentioned in this paper is a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network.
Energy-efficient communication protocols for wireless microsensor networks
TL;DR: LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network, is proposed.
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