scholarly journals An Energy Efficient Fuzzy Logic Cluster Formation Protocol in Wireless Sensor Networks

2012 ◽  
Vol 10 ◽  
pp. 255-262 ◽  
Author(s):  
Rogaia Mhemed ◽  
Nauman Aslam ◽  
William Phillips ◽  
Frank Comeau
Author(s):  
Amandeep Kaur Sohal ◽  
Ajay Kumar Sharma ◽  
Neetu Sood

Background: An information gathering is a typical and important task in agriculture monitoring and military surveillance. In these applications, minimization of energy consumption and maximization of network lifetime have prime importance for green computing. As wireless sensor networks comprise of a large number of sensors with limited battery power and deployed at remote geographical locations for monitoring physical events, therefore it is imperative to have minimum consumption of energy during network coverage. The WSNs help in accurate monitoring of remote environment by collecting data intelligently from the individual sensors. Objective: The paper is motivated from green computing aspect of wireless sensor network and an Energy-efficient Weight-based Coverage Enhancing protocol using Genetic Algorithm (WCEGA) is presented. The WCEGA is designed to achieve continuously monitoring of remote areas for a longer time with least power consumption. Method: The cluster-based algorithm consists two phases: cluster formation and data transmission. In cluster formation, selection of cluster heads and cluster members areas based on energy and coverage efficient parameters. The governing parameters are residual energy, overlapping degree, node density and neighbor’s degree. The data transmission between CHs and sink is based on well-known evolution search algorithm i.e. Genetic Algorithm. Conclusion: The results of WCEGA are compared with other established protocols and shows significant improvement of full coverage and lifetime approximately 40% and 45% respectively.


2021 ◽  
Vol 40 (5) ◽  
pp. 8727-8740
Author(s):  
Rajvir Singh ◽  
C. Rama Krishna ◽  
Rajnish Sharma ◽  
Renu Vig

Dynamic and frequent re-clustering of nodes along with data aggregation is used to achieve energy-efficient operation in wireless sensor networks. But dynamic cluster formation supports data aggregation only when clusters can be formed using any set of nodes that lie in close proximity to each other. Frequent re-clustering makes network management difficult and adversely affects the use of energy efficient TDMA-based scheduling for data collection within the clusters. To circumvent these issues, a centralized Fixed-Cluster Architecture (FCA) has been proposed in this paper. The proposed scheme leads to a simplified network implementation for smart spaces where it makes more sense to aggregate data that belongs to a cluster of sensors located within the confines of a designated area. A comparative study is done with dynamic clusters formed with a distributive Low Energy Adaptive Clustering Hierarchy (LEACH) and a centralized Harmonic Search Algorithm (HSA). Using uniform cluster size for FCA, the results show that it utilizes the available energy efficiently by providing stability period values that are 56% and 41% more as compared to LEACH and HSA respectively.


2016 ◽  
Vol 11 (2) ◽  
pp. 2641-2656
Author(s):  
Basim Abood ◽  
Aliaa Hussien ◽  
Yu Li ◽  
Desheng Wang

The most important consideration in designing protocols for wireless sensor networks is the energy constraint of nodes because in most cases battery recharging is inconvenient or impossible. Therefore, many researches have been done to overcome this demerit. Clustering is one of the main approaches in designing scalable and energy-efficient protocols for wireless sensor networks. The cluster heads take the task of data aggregation and data routing to decrease the amount of communication and this prolongs the network lifetime. LEACH protocol is one of the famous of them. In this paper, we proposed a novel scheme to investigate the cluster, the Fuzzy Logic Cluster Leach Protocol (FUZZY-LEACH), which uses Fuzzy Logic Inference System (FIS) in the cluster process. We demonstrate that using multiple parameters in cluster reduces energy consumption. We compare our technique with the LEACH protocol to show that using a multi parameter FIS enhances the network lifetime significantly. Simulation results demonstrate that the network lifetime achieved by the proposed method could be increased by nearly 28.5% more than that obtained by LEACH protocol in  scenario, and by nearly 26.4% more than that LEACH protocol in  scenario.


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