scholarly journals Optimal clustering algorithm for wireless sensor networks using combined turbid ant swarm and improved myopic algorithm for maximizing life of sensors

2021 ◽  
Author(s):  
Muthukumar S ◽  
D. Hevin Rajesh
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Control Factor ◽  
Network Simulator ◽  
Adaptive Clustering ◽  
Save Energy

Abstract Wireless sensor network (WSNs) consistsof a variety of sensor nodes to sense the environmentalparameters and communicate to the sink knot. The control factor is that controlling the power of the sensor nodes and charging or replacing the battery is an expensive and complicated process, which affects the sensor node lifetime as well as network lifetime. Clustering is one of the schemes that save energy by reducing the amount of intra-cluster communication cost. In this paper, an optimal clustering (OC) algorithm proposed to maximizes the network lifetime at data transmission without compromising energy expenditure. In OC algorithm, first we propose the turbid ant swarm(TAS) algorithm to form the clusters, which reduces much amount of energy consumption. Then, an improved myopic (IM) algorithm proposed to determines the cluster head (CH) of cluster, which minimizes re-clustering frequency and intra-communication charge. The proposed OC-TAS-IM algorithm is concentrate to get better the energy efficiency and extend the network life span. Moreover, the planned algorithm is practical to the low-energy adaptive clustering hierarchy (LEACH) to perform the entire routing. The completion and imitation experiment with Network Simulator (NS2) are obtainable in order to authenticate our planned OC-TAS-IM algorithm. Imitation outcome illustrate that OC-TAS-IM algorithm is stable in terms of energy consumption and network lifetime because of optimal clustering.

Routing Algorithm based on Clustering for Increasing the Lifetime of Sensor Networks by Using Meta-Heuristic Bee Algorithms

2020 ◽  
Vol 10 (1) ◽  
pp. 25-36
Author(s):  
Mohammad Sedighimanesh ◽  
Hesam Zand Hesami ◽  
Ali Sedighimanesh
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Heuristic Algorithms ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Cost Effective ◽  
Sensor Nodes ◽  
Wireless Sensor

Background: Nowadays, the use of wireless sensor networks is developing rapidly. these networks are applicable in many fields, including military, medical, and environment. these networks use hundreds or thousands of cheap sensor nodes with low power-low and low energy to perform large tasks. These networks have limitations that can lead to inefficiency or not cost - effective. Among these limitations, consumption of energy and issues related to the lifetime of the network. One of the solutions that can assist the load balancing between sensor nodes, increased scalability, improving energy consumption and consequently, increasing network lifetime, clustering of sensor nodes and placing a suitable cluster head in all clusters. Choosing the right cluster head, significantly reduces energy consumption in the network and increases network lifetime. Objective: The purpose of this paper is to increase network lifetime by using the efficient clustering algorithm, which is used in Meta-heuristic bee colony to select the cluster head. Simulation of this paper is performed by MATLB software and the proposed method is compared with LEACH and GACR approaches. Conclusion: The simulation findings in this study show that the intended study has remarkably increased the length of the network lifetime by LEACH and GACR algorithms. Due to the limitation of energy in the wireless sensor network such solutions and using Meta-heuristic algorithms can give rise a remarkable increasing in network lifetime.

Organized Selection Cluster Head on Fuzzy Low-Energy Adaptive Clustering Hierarchy Protocol in Three-Dimensional Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abderrahmane El Aalaoui ◽  
Abderrahmane Hajraoui
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Cluster Head ◽  
Three Dimensional ◽  
Low Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Balancing ◽  
Adaptive Clustering ◽  
Development Approach

: In this paper, we propose an enhancement approach to reduce the energy consumption, extend the network lifetime and improve the performance of protocol Fuzzy Low-Energy Adaptive Clustering Hierarchy Algorithm (Fuzzy LEACH). This improvement in order to augment the energy balancing in clusters among all sensor nodes and to minimize the energy dissipation during network communications. The proposed method is based on a cluster head selection method. Moreover, an enhanced organization of this selection has been implemented. Therefore, the development approach indicates a progress in terms of network lifetime, energy consumption and number of packets transferred to BS compared to Low-Energy Adaptive Clustering Hierarchy Algorithm (LEACH) and other related extended spaces protocols. Mathematical analysis and MATLAB 2013a simulation results show the effectiveness of the proposed approach. The new approach reduce the energy consumption of Wireless Sensor Network (WSN) about 0.99% to 5.64%, prolongs the network life cycle by 42% and increases the number of packets sent by 86% to 732%.

scholarly journals Routing and Clustering of Sensor Nodes in the Honeycomb Architecture

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Amine Rais ◽  
Khalid Bouragba ◽  
Mohammed Ouzzif
Keyword(s):  
Energy Consumption ◽  
Routing Protocol ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Delivery ◽  
Hybrid Routing ◽  
Hybrid Routing Protocol ◽  
Hierarchical Protocols

Energy is the most valuable resource in wireless sensor networks; this resource is limited and much in demand during routing and communication between sensor nodes. Hierarchy structuring of the network into clusters allows reducing the energy consumption by using small distance transmissions within clusters in a multihop manner. In this article, we choose to use a hybrid routing protocol named Efficient Honeycomb Clustering Algorithm (EHCA), which is at the same time hierarchical and geographical protocol by using honeycomb clustering. This kind of clustering guarantees the balancing of the energy consumption through changing in each round the location of the cluster head, which is in a given vertex of the honeycomb cluster. The combination of geographical and hierarchical routing with the use of honeycomb clustering has proved its efficiency; the performances of our protocol outperform the existing protocols in terms of the number of nodes alive, the latency of data delivery, and the percentage of successful data delivery to the sinks. The simulations testify the superiority of our protocol against the existing geographical and hierarchical protocols.

A Cluster Algorithm for Wireless Sensor Networks Based on Energy Efficiency

2015 ◽  
Vol 785 ◽  
pp. 744-750
Author(s):  
Lei Gao ◽  
Qun Chen
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Selection Criterion ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Head Node

In order to solve the energy limited problem of sensor nodes in the wireless sensor networks (WSN), a fast clustering algorithm based on energy efficiency for wire1ess sensor networks is presented in this paper. In the system initialization phase, the deployment region is divided into several clusters rapidly. The energy consumption ratio and degree of the node are chosen as the selection criterion for the cluster head. Re-election of the cluster head node at this time became a local trigger behavior. Because of the range of the re-election is within the cluster, which greatly reduces the complexity and computational load to re-elect the cluster head node. Theoretical analysis indicates that the timing complexity of the clustering algorithm is O(1), which shows that the algorithm overhead is small and has nothing to do with the network size n. Simulation results show that clustering algorithm based on energy efficiency can provide better load balancing of cluster heads and less protocol overhead. Clustering algorithm based on energy efficiency can reduce energy consumption and prolong the network lifetime compared with LEACH protocol.

scholarly journals Distributed fuzzy logic based cluster head election scheme (DFLCHES) for prolonging the lifetime of the wireless sensor network

2017 ◽  
Vol 7 (1.5) ◽  
pp. 111
Author(s):  
S. Ramakrishnan ◽  
S. Prayla Shyry
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Significant Feature ◽  
Cluster Head Election ◽  
Wide Range

Wireless sensor networks (WSNs) is considered as the predominant technology due to their high suitability and adaptability that makes it possible to be deployed in wide range of applications like civil and military domain. But energy-constraint is the significant feature that needs to be addressed for sensor networks since energy drain of sensor nodes affects network lifetime, stability and co-operation of sensor nodes in the event of enforce reliable data dissemination. Cluster head election has to been performed periodically in order to handle energy balance for facilitating reliable packet delivery. Most of the cluster head election schemes of the literature elect a node as cluster head either randomly or by elucidating their stochastic probabilities. Hence a Distributed Fuzzy Logic based Cluster Head Election Scheme (DFLCHES) that discriminates and discards packets from the sensor nodes that has the least probability of being elected as cluster head is proposed. DFLCHES utilizes five significant parameters such as trust, energy, node density, hop count and centrality measure for quantifying the probability of cluster head election. This DFLCHES is run on each neighbor nodes of the cluster members to facilitate the action of discrimination. DFLCHES also balances the energy consumption of the cluster members during transmission as it discards packets from ineligible nodes. Further the action of cluster head election has to be optimized periodically for reducing and balancing energy consumption for prolonging the network lifetime. In DFLCHES, the process of optimizing cluster head depends on the incorporation of the concept of Genetic algorithms for enabling and ensuring reliable routing.

A New Clustering Routing Algorithm for WSN Based on PSO

2013 ◽  
Vol 850-851 ◽  
pp. 689-692
Author(s):  
Li Fu Wang ◽  
Jian Ding ◽  
Zhi Kong
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Pso Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Long Distance ◽  
Wireless Sensor Nodes ◽  
Spatially Distributed

A wireless sensor network (WSN) consists of spatially distributed wireless sensor nodes. The node power constrains the development of WSN. Employing techniques of clustering can reduce energy consumption of wireless sensor nodes and prolong the network lifetime. Therefore, in the study a new clustering routing algorithm is presented. The clustering algorithm uses the double-layer sensor nodes to communicate. And in order to optimize power energy consumption for WSN node energy, PSO algorithm is employed to find cluster head in each layer. Simulation results show that the algorithm not only can equal power energy of node, but also can reduce consumption in the long distance data transmission.

scholarly journals An enhancement of path selection to cluster head based on multi-hop routing in two-tier wireless sensor network

2019 ◽  
Vol 9 (6) ◽  
pp. 5360
Author(s):  
Wan Isni Sofiah Wan Din ◽  
Asyran Zarizi Bin Abdullah ◽  
Razulaimi Razali ◽  
Ahmad Firdaus ◽  
Salwana Mohamad ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Data Transmission ◽  
Cluster Head ◽  
Threshold Value ◽  
Path Selection ◽  
Sensor Nodes ◽  
Wireless Sensor

<span lang="EN-US">Wireless Sensor Network (WSN) is a distributed wireless connection that consists many wireless sensor devices. It is used to get information from the surrounding activities or the environment and send the details to the user for future work. Due to its advantages, WSN has been widely used to help people to collect, monitor and analyse data. However, the biggest limitation of WSN is about the network lifetime. Usually WSN has a small energy capacity for operation, and after the energy was used up below the threshold value, it will then be declared as a dead node. When this happens, the sensor node cannot receive and send the data until the energy is renewed. To reduce WSN energy consumption, the process of selecting a path to the destination is very important. Currently, the data transmission from sensor nodes to the cluster head uses a single hop which consumes more energy; thus, in this paper the enhancement of previous algorithm, which is MAP, the data transmission will use several paths to reach the cluster head. The best path uses a small amount of energy and will take a short time for packet delivery. The element of Shortest Path First (SPF) Algorithm that is used in a routing protocol will be implemented. It will determine the path based on a cost, in which the decision will be made depending on the lowest cost between several connected paths. By using the MATLAB simulation tool, the performance of SPF algorithm and conventional method will be evaluated. The expected result of SPF implementation will increase the energy consumption in order to prolong the network lifetime for WSN.</span>

scholarly journals Efficient organization of nodes in wireless sensor networks (clustering location-based LEACH)

2022 ◽  
Vol 12 (1) ◽  
pp. 1011
Author(s):  
Mohammed Réda El Ouadi ◽  
Abderrahim Hasbi
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Rapid Development ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Main Element

The rapid development of connected devices and wireless communication has enabled several researchers to study wireless sensor networks and propose methods and algorithms to improve their performance. Wireless sensor networks (WSN) are composed of several sensor nodes deployed to collect and transfer data to base station (BS). Sensor node is considered as the main element in this field, characterized by minimal capacities of storage, energy, and computing. In consequence of the important impact of the energy on network lifetime, several researches are interested to propose different mechanisms to minimize energy consumption. In this work, we propose a new enhancement of low-energy adaptive clustering hierarchy (LEACH) protocol, named clustering location-based LEACH (CLOC-LEACH), which represents a continuity of our previous published work location-based LEACH (LOC-LEACH). The proposed protocol organizes sensor nodes into four regions, using clustering mechanism. In addition, an efficient concept is adopted to choose cluster head. CLOC-LEACH considers the energy as the principal metric to choose cluster heads and uses a gateway node to ensure the inter-cluster communication. The simulation with MATLAB shows that our contribution offers better performance than LEACH and LOC-LEACH, in terms of stability, energy consumption and network lifetime.

scholarly journals Data Clustering Method in Wireless Sensor Networks Based on Residual Energy Perception

2018 ◽  
Vol 14 (06) ◽  
pp. 85 ◽  
Author(s):  
Xudong Yang
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Data Gathering ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Forwarding ◽  
Cluster Data ◽  
Head Node

<p class="0abstract"><span lang="EN-US">To prolong the survival time of wireless sensor network, an iterative scheme was proposed. First of all, spectrum clustering algorithm iteratively segmented the network into clusters, and cluster head nodes in each sub cluster were determined depending on the size of residual energy of sensor nodes. Then, a data forwarding balance tree was constructed in each sub cluster. Data forwarding path of each non-cluster head node was defined, and the moving path of a mobile data collector was determined, which used the residual energy as the basis for the network optimization. Finally, this scheme was simulated, and two traditional data gathering algorithms were compared. The results showed that the algorithm designed in this experiment could effectively balance energy consumption among all WSN nodes and had great performance improvement compared with the traditional data collection algorithm. To sum up, this algorithm can significantly reduce the energy consumption of the network and improve the lifetime of the network. </span></p>

Improvement of Clustering Algorithm for WSNs

2014 ◽  
Vol 665 ◽  
pp. 745-750
Author(s):  
Qi Gong Chen ◽  
Yong Zhi Wang ◽  
Li Sheng Wei ◽  
Wen Gen Gao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Optimal Number ◽  
Low Energy ◽  
Experimental Results ◽  
Wireless Sensor ◽  
Adaptive Clustering

Energy consumption is a hot issue in WSNs (Wireless Sensor Networks). In this paper, we present an improved clustering algorithm. By changing the order of traditional WSNs clustering algorithm, this algorithm uses k-means clustering firstly base on optimal number of cluster head is determined; Then selects cluster head by an improved LEACH (Low Energy Adaptive Clustering Hierarchy) algorithm; Finally, Our experimental results demonstrate that this approach can reduces energy consumption and increases the lifetime of the WSNs.

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