scholarly journals Genetic algorithm based protocols to select cluster heads and find multi-hop path in wireless sensor networks: review

2018 ◽  
Vol 218 ◽  
pp. 03019 ◽  
Author(s):  
Mohammed Al-Shalabi ◽  
Mohammed Anbar ◽  
Tat-Chee Wan
Keyword(s):  
Genetic Algorithm ◽  
Optimization Technique ◽  
Specific Area ◽  
Modern Technology ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Path Finding ◽  
Radio Communication ◽  
Cluster Heads

A wireless sensor network (WSN) is a modern technology in radio communication. A WSN comprises a number of sensor nodes that are randomly spread in a specific area for sensing and monitoring physical attributes that are difficult to monitor by humans, such as temperature, fire, and pressure. Many problems, including data transmission, power consumption and selecting cluster heads, may occur due to the nature of WSNs. Various protocols have been conducted to resolve these issues. Most of the proposed protocols are based on the Genetic Algorithm as an optimization technique to select the Cluster Heads (CHs) or to find a multi-hop path for sending the data from the CHs to the Base Station (BS). This paper presents a comprehensive study of the protocols for WSNs that are proposed to come up with these issues. This study emphasises on CHs selection protocols and multi-hop path finding protocols and their strengths and weaknesses. A new taxonomy is presented to discuss these protocols on the basis of different classes. A complete comparison of the main features and behaviors of the protocols is conducted. This study will give basic guidelines for the researchers those have a motivation to develop a new CHs selection protocol or a multi-hop path finding protocol.

scholarly journals An Integrated Routing Mechanism on Homogenous Wireless Sensor Networks using Genetic Algorithm

2021 ◽  
Author(s):  
Ramin Danehchin
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Hop Count ◽  
Routing Problem ◽  
Cluster Heads

Abstract Data collection on Wireless Sensor Networks (WSNs) is a significant challenge to satisfy the requirements of various applications. Providing an energy-efficient routing technique is the primary step in data collection over WSNs. The existing data collection techniques in the WSNs field struggle with the imbalance load distribution and the short lifetime of the network. This paper proposes a novel mechanism to select cluster-heads, cluster the wireless sensor nodes, and determine the optimal route from source nodes to the sink. We employ the genetic algorithm to solve the routing problem considering the hop-count of the cluster-heads to the sink, the number of each cluster member, residual energy of cluster-heads, and the number of cluster-heads connected to the sink as the fitness criteria. Our proposed mechanism uses a greedy approach to calculate the hop-count of each cluster-head to the sink for integrating the clustering and routing process on WSNs. The simulation results demonstrate that our proposed mechanism improves the energy consumption, the number of live nodes, and the lifetime of the network compared to other data collection approaches on WSNs.

A Heuristic Optimized Algorithm for Energy Optimization in Wireless Sensor Networks

2010 ◽  
Vol 34-35 ◽  
pp. 1019-1023
Author(s):  
Zhao Feng Yang ◽  
Ai Wan Fan
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Optimal Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Adaptive Clustering ◽  
Battery Capacity

Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. In this paper we propose an optimal algorithm with genetic algorithm taken into consideration, and compare it with three well known and widely used approaches, i.e., LEACH and LEACH-C, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, and data delivery at the base station than the other routing protocols. Key words: Wireless sensor networks, base station, heuristic optimized genetic algorithm, low energy adaptive clustering hierarchy

scholarly journals An Improved Leach Algorithm Based on Wireless Sensor Networks

2019 ◽  
Vol 8 (2S8) ◽  
pp. 1623-1628
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Base Station ◽  
Low Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Current Generation ◽  
Cluster Heads ◽  
Computation Algorithm ◽  
Stable Election Protocol

In our current generation, wireless sensor network is much in use and has become quintessential. With wide improvement of technology and the various ranges developed in communication and in other aspects, this document mainly focuses on the LEACH algorithm (Adaptive Low Energy Hierarchy) and the second most important methodology used is the SEP (stable election protocol). We have discovered improvements in energy efficiency by comparing our results with these two algorithms and the sensor mortality rate is reduced to a greater extent. This research proposes an improved computation algorithm method for the calculation of LEACH clustering, by considering the importance of the cluster heads and the sensor nodes present, T (n) is reorganisedrecommendinga procedure that focuses on reducing the energy consumption. The combined rate of information is found by allowing cluster heads to gather information before it is sent to base station. This improved computation algorithmwill be able to increase vital utilisation of networks and increase sensor life.

scholarly journals Energy-efficient genetic algorithm variants of PEGASIS for 3D Wireless Sensor Networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aaqil Somauroo ◽  
Vandana Bassoo
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Delay Performance

Due to its boundless potential applications, Wireless Sensor Networks have been subject to much research in the last two decades. WSNs are often deployed in remote environments making replacement of batteries not feasible. Low energy consumption being of prime requisite led to the development of energy-efficient routing protocols. The proposed routing algorithms seek to prolong the lifetime of sensor nodes in the relatively unexplored area of 3D WSNs. The schemes use chain-based routing technique PEGASIS as basis and employ genetic algorithm to build the chain instead of the greedy algorithm. Proposed schemes will incorporate an energy and distance aware CH selection technique to improve load balancing. Clustering of the network is also implemented to reduce number of nodes in a chain and hence reduce delay. Simulation of our proposed protocols is carried out for homogeneous networks considering separately cases for a static base-station inside and outside the network. Results indicate considerable improvement in lifetime over PEGASIS of 817% and 420% for base station inside and outside the network respectively. Residual energy and delay performance are also considered.

Design of Hybridized Wireless Sensor Network using K-Means Clustering and Genetic Algorithm

2017 ◽  
Vol 2 (5) ◽  
pp. 1-6
Author(s):  
M. D. Gbolagade ◽  
R. G. Jimoh ◽  
K. A. Gbolagade ◽  
O. V. Mejabi
Keyword(s):  
Data Transfer ◽  
Cluster Head ◽  
Simulated Data ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life ◽  
Cluster Heads ◽  
Main Challenge

Prolonging the network lifetime in wireless sensor networks (WSNs), Clustering has been recognized has one of the significant methods in achieving this, It entails grouping of sensor nodes into clusters and electing cluster heads (CHs) for all the clusters. CH’s accept data from relevant cluster’s nodes and forward the aggregate data to base station. A main challenge in WSNs is the selection of appropriate cluster heads. This work proposes a system that is efficient, scalable and load balanced. The proposed scheme combines two known algorithms namely k-means clustering and genetic algorithms based on the weaknesses identified in the two. The simulated data is obtained through the enhancement of clustering by the cluster head (base station) that helps in locating the nearest node that is important in the data transfer instead of transferring to a node that is not necessary, thereby wasting time and resources. The obtained simulation results indicate that this approach is efficient and last longer in elongating the battery life time than the conventional method by 60%.

Efficient Power Control and Clustering Method Based on Hybrid Clonal Genetic Algorithm in Wireless Sensor Networks

2012 ◽  
Vol 263-266 ◽  
pp. 889-897
Author(s):  
Xiang Xian Zhu ◽  
Su Feng Lu
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Large Scale ◽  
Clonal Selection ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Clonal Selection Algorithm ◽  
Clustering Methods

Wireless sensor networks (WSNs) lifetime for large-scale surveillance systems is defined as the time span that all targets can be covered. How to manage the combination of the sensor nodes efficiently to prolong the whole network’s lifetime while insuring the network reliability, it is one of the most important problems to research in WSNs. An effective optimization framework is then proposed, where genetic algorithm and clonal selection algorithm are hybridized to enhance the searching ability. Our goal can be described as minimizing the number of active nodes and the scheduling cost, thus reducing the overall energy consumption to prolong the whole network’s lifetime with certain coverage rate insured. We compare the proposed algorithm with different clustering methods used in the WSNs. The simulation results show that the proposed algorithm has higher efficiency and can achieve better network lifetime and data delivery at the base station.

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.

An Improvement Routing Protocol Based LEACH for Wireless Sensor Networks

2014 ◽  
Vol 614 ◽  
pp. 472-475 ◽  
Author(s):  
Jin Gang Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Base Station ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Number Of Clusters ◽  
Cluster Heads

Due to limited energy, computing ability, and memory of Wireless sensor Networks(WSN), routing issue is one of the key factors for WSN. LEACH is the first clustering routing protocol, which can efficiently reduce the energy consumption and prolong the lifetime of WSN, but it also has some disadvantage. This paper proposed an improvement based LEACH, called LEACH-T. According to different number of clusters, LEACH-T uses variable time slot for different clusters in steady-state phase, and single-hop or multi-hop to transmit data between cluster heads and Base Station. Also it considered residual energy of sensor nodes and the optimal number of clusters during selection of the cluster heads. The simulation results show that LEACH-T has better performance than LEACH for prolonging the lifetime and reducing the energy consumption.

scholarly journals Path Optimization Algorithm in Wireless Sensor Network with Obstacle

2018 ◽  
Vol 9 (3) ◽  
pp. 599
Author(s):  
J. S. Praveen ◽  
Mr. Mayilvahanan
Keyword(s):  
Wireless Sensor Network ◽  
Quality Factor ◽  
Sensor Network ◽  
Optimization Algorithm ◽  
Optimization Technique ◽  
Base Station ◽  
Path Optimization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hop Count

<p>Clustering is used for prolonging the network lifetime in WSN. It groups sensor nodes into different groups and selects a single node as a cluster head (CH) for all the groups. CHS collect the data from consonant clusters and forward the data to base station. In this paper, we proposed path optimization algorithm in Wireless Sensor Network with an obstacle (POAWSNO) that periodically selects the cluster heads according to quality factor. The quality factor is estimated by three criteria including quality of the link, remaining energy and degree of the node. Path optimization technique determines the shortest path during obstacle present in the WSN. POT is used to reduce the hop count and packet delay. The simulation results demonstrate that this approach improves the throughput and reduce the loss of packets and energy consumption in the network using network simulator.</p>

scholarly journals FLOWER POLLINATION AND GENETIC ALGORITHM BASED OPTIMIZATION FOR NODE DEPLOYMENT IN WIRELESS SENSOR NETWORKS

2020 ◽  
Vol 5 (2) ◽  
pp. 281-293
Author(s):  
Kapil Keswani ◽  
Dr. Anand Bhaskar
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Environment ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Field Energy ◽  
Main Concern ◽  
Node Placement ◽  
Flower Pollination

Wireless sensor network (WSN) most popular area of research where lots of work done in this field. Energy efficiency is one of the most focusing areas because life time of network is most common issue. In the WSN, the node placement is very essential part for the proper communication between the sensor nodes and base station (BS). For better communication nodes should be aware about their own or neighbor node’s location. Better optimization of resources and performance improvement are the main concern for the WSN. Optimal techniques should be utilized to place the nodes at the best possible locations for achieving the desired goal. For node placement, flower pollination optimization and genetic algorithm are useful to generate better result. BS is responsible for the communication of nodes with each other and it should be reachable to nodes. For this Region of Interest (RoI) is helpful to choose the best location. Placement of BS in the middle is suitable place for the static nodes deployment and there should be other strategy for the dynamic environment. Nodes should be connected to each other for the transmission of data from the source to BS properly. From the MATLAB simulation, it has been shown that the proposed methodology improves the network performance in terms of dead nodes, energy remaining and various packets sent to BS.

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