Journal ArticleDOI
A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks
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An energy efficient cluster head selection algorithm which is based on particle swarm optimization (PSO) called PSO-ECHS is proposed with an efficient scheme of particle encoding and fitness function and the results are compared with some existing algorithms to demonstrate the superiority of the proposed algorithm.Abstract:
Clustering has been proven to be one of the most efficient techniques for saving energy of wireless sensor networks (WSNs). However, in a hierarchical cluster based WSN, cluster heads (CHs) consume more energy due to extra overload for receiving and aggregating the data from their member sensor nodes and transmitting the aggregated data to the base station. Therefore, the proper selection of CHs plays vital role to conserve the energy of sensor nodes for prolonging the lifetime of WSNs. In this paper, we propose an energy efficient cluster head selection algorithm which is based on particle swarm optimization (PSO) called PSO-ECHS. The algorithm is developed with an efficient scheme of particle encoding and fitness function. For the energy efficiency of the proposed PSO approach, we consider various parameters such as intra-cluster distance, sink distance and residual energy of sensor nodes. We also present cluster formation in which non-cluster head sensor nodes join their CHs based on derived weight function. The algorithm is tested extensively on various scenarios of WSNs, varying number of sensor nodes and the CHs. The results are compared with some existing algorithms to demonstrate the superiority of the proposed algorithm.read more
Citations
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Steady-State Sine Cosine Genetic Algorithm Based Chaotic Search for Nonlinear Programming and Engineering Applications
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A novel approach for particle swarm optimization‐based clustering with dual sink mobility in wireless sensor network
Supreet Kaur,Vinit Grewal +1 more
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A quantum inspired PSO algorithm for energy efficient clustering in wireless sensor networks
TL;DR: This paper proposes a Quantum inspired PSO (particle swarm optimization) called Quantum-inspired PSO for Energy Efficient Clustering (QPSOEEC), and its results are compared to existing algorithms that demonstrate the superiority of the algorithm.
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Energy-Balancing Unequal Clustering Approach to Reduce the Blind Spot Problem in Wireless Sensor Networks (WSNs).
TL;DR: A novel clustering approach that partitions the monitoring area in a cognitive way for balancing the energy consumption and reduces the blind spot problem that escalates once the nodes start dying is proposed.
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Towards Controlled Transmission: A Novel Power-Based Sparsity-Aware and Energy-Efficient Clustering for Underwater Sensor Networks in Marine Transport Safety
Israa Adil Hayder,Sundas Naqeeb Khan,Faisal Althobiani,Muhammad Irfan,Muhammad Idrees,Saeed Ullah,Faisal Alsaaq,Adam Glowacz,Iwona Goldasz,Marcin Tomczyk,Radu Martis +10 more
TL;DR: This paper integrates the three main techniques that have been used for managing Transmission Power-based Sparsity-conscious Energy-Efficient Clustering (CTP-SEEC) in UWSNs and proposes a new protocol that converts to a suitable Transmission Power Level (TPL) and deploys collaboration mobile sinks or Autonomous Underwater Vehicles (AUVs).
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
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.
Journal ArticleDOI
An application-specific protocol architecture for wireless microsensor networks
TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
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