Optimal Cluster Head selection in Wireless Sensor Networks using Integer Linear Programming Techniques

2014 ◽  
Vol 3 (3) ◽  
pp. 186
Author(s):  
Zahra Eskandari ◽  
Seyed Amin Hosseini Seno ◽  
Muhamed Shenify ◽  
Rahmat Budiarto
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Clustering Problem ◽  
Programming Techniques ◽  
Optimal Cluster

Wireless sensor network (WSN) consists of sensor nodes which are deployed in the environment densely and randomly. The main constraint of these nodes is limited energy resources, so, the operations which are performed in the network, must be energy efficient. For this reason, routing and data transmission in these networks perform hierarchically and in multi hop manner. One of these hierarchical architectures which have a considerable positive effect on energy consumption is clustering algorithm. But what is important is that the cluster heads election should be done efficiently. Recently some works have focused on optimal cluster head election using Integer Linear Programming techniques. In this paper, Integer Linear Programming techniques are used to formulate the clustering problem.  At first, by using Integer Linear Programming techniques, a scalable and multi objective model for optimal cluster head selection is presented and then the distributed clustering algorithm is proposed. As shown in simulation results, the proposed clustering algorithm is more efficient in terms of energy vs. LEACH algorithm.

Hybrid artificial bee colony and glow worm algorithm for energy efficient cluster head selection in wireless sensor networks

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jasleen Kaur ◽  
Punam Rani ◽  
Brahm Prakash Dahiya
Keyword(s):  
Artificial Bee Colony ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Swarm Optimization ◽  
Content Type ◽  
Bee Colony ◽  
Glowworm Swarm Optimization ◽  
Optimal Cluster

Purpose This paper aim to find optimal cluster head and minimize energy wastage in WSNs. Wireless sensor networks (WSNs) have low power sensor nodes that quickly lose energy. Energy efficiency is most important factor in WSNs, as they incorporate limited sized batteries that would not be recharged or replaced. The energy possessed by the sensor nodes must be optimally used so as to increase the lifespan. The research is proposing hybrid artificial bee colony and glowworm swarm optimization [Hybrid artificial bee colony and glowworm swarm optimization (HABC-GSO)] algorithm to select the cluster heads. Previous research has considered fitness-based glowworm swarm with Fruitfly (FGF) algorithm, but existing research was limited to maximizing network lifetime and energy efficiency. Design/methodology/approach The proposed HABC-GSO algorithm selects global optima and improves convergence ratio. It also performs optimal cluster head selection by balancing between exploitation and exploration phases. The simulation is performed in MATLAB. Findings The HABC-GSO performance is evaluated with existing algorithms such as particle swarm optimization, GSO, Cuckoo Search, Group Search Ant Lion with Levy Flight, Fruitfly Optimization algorithm and grasshopper optimization algorithm, a new FGF in the terms of alive nodes, normalized energy, cluster head distance and delay. Originality/value This research work is original.

Clustering Algorithm to Reduce Power Consumptions for Wireless Sensor Networks

2012 ◽  
Vol 433-440 ◽  
pp. 5228-5232
Author(s):  
Mohammad Ahmadi ◽  
Hamid Faraji ◽  
Hossien Zohrevand
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Cluster Heads

A sensor network has many sensor nodes with limited energy. One of the important issues in these networks is the increase of the life time of the network. In this article, a clustering algorithm is introduced for wireless sensor networks that considering the parameters of distance and remaining energy of each node in the process of cluster head selection. The introduced algorithm is able to reduce the amount of consumed energy in the network. In this algorithm, the nodes that have more energy and less distance from the base station more probably will become cluster heads. Also, we use algorithm for finding the shortest path between cluster heads and base station. The results of simulation with the help of Matlab software show that the proposed algorithm increase the life time of the network compared with LEACH algorithm.

scholarly journals Optimal Cluster Head Selection and Clustering for WSN using PSO

2020 ◽  
Vol 9 (3) ◽  
pp. 389-395
Keyword(s):  
Wireless Sensor Network ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Cluster Distance ◽  
Optimal Cluster ◽  
Selection Of

Nowadays, Wireless Sensor Network is the promising and booming technology used in a variety of applications like disaster monitoring, health care, environmental monitoring, agriculture, industrial automation, etc. However the main drawback of the wireless sensor network is the limited energy source of the sensor nodes. Consequently, efficient utilization of the energy becomes essential for increasing the lifetime of network. Clustering protocol is one of the best energy efficient approach for saving the energy and maximizing the network lifetime. But the improper selection of cluster heads (CHs) may lead to the death of the CHs which deteriorate the performance of the network. Therefore the proper selection of cluster head becomes important for the energy conservation of sensor nodes and to maximize the lifetime of network. In this paper, we have presented PSO based optimal cluster head selection algorithm, in which the best possible CHs are chosen on the basis of parameters like residual energy, intra-cluster distance, and inter-cluster distance of the sensor node. With the effective scheme of particle encoding and fitness function, the proposed PSO algorithm is implemented for reducing the energy consumption and improving lifetime of network. The proposed algorithm also ensures the uniform distribution of the energy over network, by changing the role of CHs after each round. We extend our research to cluster formation approach where the sensor nodes are joined to the CH on the basis distance and energy of cluster head. The proposed algorithm is simulated extensively under various conditions like number of sensor nodes in the field, number of CHs, the position of the base station, constant energy and random energy, etc. and the simulation results are analyzed with the extant algorithms. Under all the circumstances the proposed algorithm outperforms the existing LEACH and SEP protocols in terms of average residual energy, the network lifetime and number of data packets received by the base station. Because of the improvement in the lifetime of the network, the proposed algorithm can be used in the applications like environmental monitoring, agriculture etc.

Developing Multi-Tier Network Design for Effective Energy Consumption of Cluster Head Selection in WSN

2016 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Wan Isni Sofiah Wan Din ◽  
Saadiah Yahya ◽  
Mohd Nasir Taib ◽  
Ahmad Ihsan Mohd Yassin ◽  
Razulaimi Razali
Keyword(s):  
Sensor Network ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Cluster Head Selection ◽  
Energy Usage ◽  
Network Cluster ◽  
Fuzzy Logic Approach ◽  
The Stability

Clustering in Wireless Sensor Network (WSN) is one of the methods to minimize the energy usage of sensor network. The design of sensor network itself can prolong the lifetime of network. Cluster head in each cluster is an important part in clustering to ensure the lifetime of each sensor node can be preserved as it acts as an intermediary node between the other sensors. Sensor nodes have the limitation of its battery where the battery is impossible to be replaced once it has been deployed. Thus, this paper presents an improvement of clustering algorithm for two-tier network as we named it as Multi-Tier Algorithm (MAP). For the cluster head selection, fuzzy logic approach has been used which it can minimize the energy usage of sensor nodes hence maximize the network lifetime. MAP clustering approach used in this paper covers the average of 100Mx100M network and involves three parameters that worked together in order to select the cluster head which are residual energy, communication cost and centrality. It is concluded that, MAP dominant the lifetime of WSN compared to LEACH and SEP protocols. For the future work, the stability of this algorithm can be verified in detailed via different data and energy. 

Salp

2020 ◽  
pp. 41-56 ◽  
Author(s):  
Vrajesh Kumar Chawra ◽  
Govind P. Gupta
Keyword(s):  
Wireless Sensor Networks ◽  
Network Lifetime ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Research Issue ◽  
Energy Hole ◽  
Node Clustering

The formation of the unequal clusters of the sensor nodes is a burning research issue in wireless sensor networks (WSN). Energy-hole and non-uniform load assignment are two major issues in most of the existing node clustering schemes. This affects the network lifetime of WSN. Salp optimization-based algorithm is used to solve these problems. The proposed algorithm is used for cluster head selection. The performance of the proposed scheme is compared with the two-node clustering scheme in the term of residual energy, energy consumption, and network lifetime. The results show the proposed scheme outperforms the existing protocols in term of network lifetime under different network configurations.

Super Strongly Perfect Graphs in the Selection of Cluster Heads in Wireless Sensor Networks

2014 ◽  
Vol 591 ◽  
pp. 206-210
Author(s):  
R. Mary Jeya Jothi ◽  
S. Emalda Roslin ◽  
N.M. Nandhitha
Keyword(s):  
Energy Consumption ◽  
Topology Control ◽  
Dominating Set ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Battery Lifetime ◽  
Hierarchical Topology ◽  
Computationally Intensive

Wireless sensor network comprises of dense sensor nodes which are randomly deployed. Major challenges in WSN are limited battery source and computation capacity. Considerable research has been carried out in the area of maximizing battery lifetime by reducing the energy consumption. Once such proposed technique involves hierarchical topology control. Conventionally proposed algorithm for hierarchical topology control involves computationally intensive soft computing tools. It leads to higher energy consumption in the sink node. Hence it necessitates computationally less intensive technique for cluster head selection. In this paper, an efficient cluster head selection is proposed using minimal dominating set in Super Strongly Perfect (SSP) graph.

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.

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