Multipart Layer Node Deployment and Computational Technique with Finest Cluster Head Selection for Network Lifetime Enhancement

2016 ◽  
Vol 13 (10) ◽  
pp. 6642-6648
Author(s):  
S. G Susila ◽  
J Arputhavijayaselvi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Computational Technique ◽  
Cluster Head Selection ◽  
Node Deployment ◽  
Cluster Heads

The continual research and development in wireless sensor networks, power is most vital resource because each sensor node has limited battery power. Numerous clustering concept routing protocols have been developed to balance and enhance lifetime of the sensor nodes in wireless sensor networks. Available clustering routing protocols are select cluster heads periodically and they considered only how can select cluster heads energy-efficiently and the most excellent selection of cluster heads, without considering energy-efficient period of the cluster heads replacement. Herein paper, it is employed different formulae in homogeneous merged layer node deployment system, which has a threshold-based cluster head selection mechanism for clustering routing protocols of wireless sensor networks. The proposed routing protocol is minimizes the number of cluster head selection difficulty by using threshold of residual energy comparison. Reducing the amount of difficulty for cluster head selection procedure yields better life span of the whole sensor networks and it is compared with the available clustering routing protocols. In the proposed system of work, node scheduling or activation techniques are also integrated and the obtained simulation results illustrate that the best to the obtainable clustering protocols in wireless sensor networks (WSNs).

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 An Energy-Balanced Mechanism for Hierarchical Routing in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenjiang Zhang ◽  
Yanan Wang ◽  
Fuxing Song ◽  
Wenyu Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Balance ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Hierarchical Routing ◽  
Cluster Heads

In wireless sensor networks (WSNs), energy-constrained sensor nodes are always deployed in hazardous and inaccessible environments, making energy management a key problem for network design. The mechanism of RNTA (redundant node transmission agents) lacks an updating mechanism for the redundant nodes, causing an unbalanced energy distribution among sensor nodes. This paper presents an energy-balanced mechanism for hierarchical routing (EBM-HR), in which the residual energy of redundant nodes is quantified and made hierarchic, so that the cluster head can dynamically select the redundant node with the highest residual energy grade as a relay to complete the information transmission to the sink node and achieve an intracluster energy balance. In addition, the network is divided into several layers according to the distances between cluster heads and the sink node. Based on the energy consumption of the cluster heads, the sink node will decide to recluster only in a certain layer so as to achieve an intercluster energy balance. Our approach is evaluated by a simulation comparing the LEACH algorithm to the HEED algorithm. The results demonstrate that the BEM-HR mechanism can significantly boost the performance of a network in terms of network lifetime, data transmission quality, and energy balance.

Enhanced Auxiliary Cluster Head Selection Routing Algorithm in Wireless Sensor Networks

2019 ◽  
Vol 12 ◽  
Author(s):  
Gaurav Kumar Nigam ◽  
Chetna Dabas
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Cluster Head ◽  
Base Station ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection

Background & Objective: Wireless sensor networks are made up of huge amount of less powered small sensor nodes that can audit the surroundings, collect meaningful data, and send it base station. Various energy management plans that pursue to lengthen the endurance of overall network has been proposed over the years, but energy conservation remains the major challenge as the sensor nodes have finite battery and low computational capabilities. Cluster based routing is the most fitting system to help for burden adjusting, adaptation to internal failure, and solid correspondence to draw out execution parameters of wireless sensor network. Low energy adaptive clustering hierarchy is an efficient clustering based hierarchical protocol that is used to enhance the lifetime of sensor nodes in wireless sensor network. It has some basic flaws that need to be overwhelmed in order to reduce the energy utilization and inflating the nodes lifetime. Methods : In this paper, an effective auxiliary cluster head selection is used to propose a new enhanced GC-LEACH algorithm in order to minimize the energy utilization and prolonged the lifespan of wireless sensor network. Results & Conclusion: Simulation is performed in NS-2 and the outcomes show that the GC-LEACH outperforms conventional LEACH and its existing versions in the context of frequent cluster head rotation in various rounds, number of data packets collected at base station, as well as reduces the energy consumption 14% - 19% and prolongs the system lifetime 8% - 15%.

Improvement of Cluster-Head Selection Mechanism Based on LEACH Protocol in Wireless Sensor Networks

2014 ◽  
Vol 989-994 ◽  
pp. 4273-4276
Author(s):  
Shi Ping Fan ◽  
Xiao Di Zhang ◽  
Hai Li Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cluster Head ◽  
Premature Death ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Selection Mechanism ◽  
Cluster Heads ◽  
Leach Protocol

In order to prolong the lifetime of wireless sensor networks, improvement of cluster-head selection mechanism based on LEACH protocol is proposed. To make the energy distribution more uniform, we consider the relationship of the density of nodes, residual energy of nodes and distance between nodes and Sink node. It eliminates the defect of energy consumption imbalance in the network caused by random position of cluster-heads and the problem of premature death of nodes caused by low energy nodes becoming cluster-heads. Simulation results show that compared with LEACH algorithm, the improved algorithm extend the network lifetime.

Optimization of Energy Conservation in Wireless Sensor Networks

2020 ◽  
Vol 17 (6) ◽  
pp. 2658-2663
Author(s):  
Anju Rani ◽  
Amit Kumar Bindal
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cluster Head ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Adaptive Clustering ◽  
Cluster Heads ◽  
Heterogeneous Wireless Sensor Network ◽  
Stable Election Protocol

Presently, Wireless Sensor Networks (WSNs) is quickest developing technology which broadly embracing for different application services including; climate observing, traffic expectation, reconnaissance, research and scholastic fields and so on. As the sensor nodes are haphazardly conveyed in remote condition, security measurements turns out to be most encouraging test where correspondence wirelesses systems confronting today. The Stable Election Protocol (SEP) is an enhanced algorithm of Adaptive Clustering Hierarchy (LEACH) with low energy in heterogeneous Wireless Sensor Network (WSN) for improving the life cycle. Be that as it may, the unequal energy circulation of cluster heads and nodes would diminish the lifetime. From one perspective, adding node vitality to cluster head selection to decrease the energy utilization of cluster heads; on the contrary, decline the energy utilization of nodes in cluster through not directly transmitted by interlude nodes. SEP, a protocol of heterogeneous-aware to drag out the time interim before the passing of the first node (we allude to as steady period), which is essential for some applications where the input from the sensor arrange must be solid. SEP depends on weighted election decision probabilities of every node to turn into cluster head as indicated by the rest of the energy in every node. The outcomes show that the E-SEP protocol functions admirably in adjusting the vitality utilization for improving the lifetime looking at LEACH and SEP protocol with enhanced SEP along with proposed E-SEP algorithm using MATLAB.

scholarly journals Energy Optimization in Cluster-Based Routing Protocols for Large-Area Wireless Sensor Networks

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 37 ◽  
Author(s):  
Sang H. Kang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Cluster Head ◽  
Hierarchical Cluster ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Large Area ◽  
Cluster Based Routing

In large-area wireless sensor networks with hierarchical cluster-based routing protocols, the average number of clusters, k, and the transmission range for the control messages, R, significantly affect the network lifespan. We analyze energy consumption in depth as a function of ( k , R ) , taking into account the energy dissipation of cluster head nodes and the member nodes, separately. To achieve joint optimization of ( k o p t , R o p t ) , we adopt derivative-free Nelder–Mead Simplex method. Computer simulations have shown that our approach effectively reduces energy consumption of sensor nodes in the process of clustering and data transmission in large-area sensor fields. Our optimization can be applied to existing cluster-based routing schemes to maximize their energy efficiency.

scholarly journals Energy-Efficient Cluster-Head Selection for Wireless Sensor Networks Using Sampling-Based Spider Monkey Optimization

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5281 ◽  
Author(s):  
Jin-Gu Lee ◽  
Seyha Chim ◽  
Ho-Hyun Park
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Cluster Head ◽  
Spider Monkey ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Adaptive Clustering ◽  
Cluster Heads ◽  
Spider Monkey Optimization

Extending the lifetime and stability of wireless sensor networks (WSNs) through efficient energy consumption remains challenging. Though clustering has improved energy efficiency through cluster-head selection, its application is still complicated. In existing cluster-head selection methods, the locations where cluster-heads are desirable are first searched. Next, the nodes closest to these locations are selected as the cluster-heads. This location-based approach causes problems such as increased computation, poor selection accuracy, and the selection of duplicate nodes. To solve these problems, we propose the sampling-based spider monkey optimization (SMO) method. If the sampling population consists of nodes to select cluster-heads, the cluster-heads are selected among the nodes. Thus, the problems caused by different locations of nodes and cluster-heads are resolved. Consequently, we improve lifetime and stability of WSNs through sampling-based spider monkey optimization and energy-efficient cluster head selection (SSMOECHS). This study describes how the sampling method is used in basic SMO and how to select cluster-heads using sampling-based SMO. The experimental results are compared to similar protocols, namely low-energy adaptive clustering hierarchy centralized (LEACH-C), particle swarm optimization clustering protocol (PSO-C), and SMO based threshold-sensitive energy-efficient delay-aware routing protocol (SMOTECP), and the results are shown in both homogeneous and heterogeneous setups. In these setups, SSMOECHS improves network lifetime and stability periods by averages of 13.4%, 7.1%, 34.6%, and 1.8%, respectively.

scholarly journals Dynamic cluster heads selection and data aggregation for efficient target monitoring and tracking in wireless sensor networks

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771878317 ◽  
Author(s):  
Juan Feng ◽  
Xiaozhu Shi ◽  
Jinxin Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Data Aggregation ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Cluster Heads ◽  
Energy Limitation ◽  
Data Source

Due to energy limitation in wireless sensor networks, clustering is an efficient scheme which has been widely used in building practical wireless sensor networks, and various cluster head selection methods have been proposed nowadays. However, less emphasis was placed on the application constraints cluster head selection. In traditional clustering wireless sensor networks, cluster head is always located at the cluster centre and cannot detect an intruding target since the target first transits the border. Moreover, the data sensed from a target are sent by each cluster head through different routings to the sink so that it cannot be aggregated efficiently near the data source. In order to address these problems, this article proposes an efficient target tracking approach, in which the nodes on the edge of a cluster instead of the centred nodes are chosen as cluster heads so that cluster heads can serve as manager and monitoring node. Furthermore, we choose a collecting cluster head to collect the sensed data from the cluster heads around the target to facilitate data aggregation. Hence, the sensed data can be aggregated near to the data source, which avoids the data long-distance transmission and reduces data gathering costs. Moreover, each cluster head has different lifetime in the efficient target tracking approach according to its location and residual energy to balance the energy cost. Experimental results show that efficient target tracking approach outperformed the state-of-the-art approaches by improving the energy consumption as well as prolonging the network lifetime by about 20% as the 20% nodes die.

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