scholarly journals Threshold Balanced Sampled DEEC Model for Heterogeneous Wireless Sensor Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Sercan Vançin ◽  
Ebubekir Erdem
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Distributed Energy ◽  
Clustering Method ◽  
Clustering Protocol ◽  
Energy Efficient Clustering

Due to the restricted hardware resources of the sensor nodes, modelling and designing energy efficient routing methods to increase the overall network lifetime have become one of the most significant strategies in wireless sensor networks (WSNs). Cluster-based heterogeneous routing protocols, a popular part of routing technology, have proven effective in management of topology, energy consumption, data collection or fusion, reliability, or stability in a distributed sensor network. In this article, an energy efficient three-level heterogeneous clustering method (DEEC) based distributed energy efficient clustering protocol named TBSDEEC (Threshold balanced sampled DEEC) is proposed. Contrary to most other studies, this study considers the effect of the threshold balanced sampled in the energy consumption model. Our model is compared with the DEEC, EDEEC (Enhanced Distributed Energy Efficient Clustering Protocol), and EDDEEC (Enhanced Developed Distributed Energy Efficient Clustering Protocol) using MATLAB as two different scenarios based on quality metrics, including living nodes on the network, network efficiency, energy consumption, number of packets received by base station (BS), and average latency. After, our new method is compared with artificial bee colony optimization (ABCO) algorithm and energy harvesting WSN (EH-WSN) clustering method. Simulation results demonstrate that the proposed model is more efficient than the other protocols and significantly increases the sensor network lifetime.

scholarly journals EECDA: Energy Efficient Clustering and Data Aggregation Protocol for Heterogeneous Wireless Sensor Networks

2011 ◽  
Vol 6 (1) ◽  
pp. 113 ◽  
Author(s):  
Dilip Kumar ◽  
Trilok C. Aseri ◽  
R.B. Patel
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Data Gathering ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

In recent years, energy efficiency and data gathering is a major concern in many applications of Wireless Sensor Networks (WSNs). One of the important issues in WSNs is how to save the energy consumption for prolonging the network lifetime. For this purpose, many novel innovative techniques are required to improve the energy efficiency and lifetime of the network. In this paper, we propose a novel Energy Efficient Clustering and Data Aggregation (EECDA) protocol for the heterogeneous WSNs which combines the ideas of energy efficient cluster based routing and data aggregation to achieve a better performance in terms of lifetime and stability. EECDA protocol includes a novel cluster head election technique and a path would be selected with maximum sum of energy residues for data transmission instead of the path with minimum energy consumption. Simulation results show that EECDA balances the energy consumption and prolongs the network lifetime by a factor of 51%, 35% and 10% when compared with Low-Energy Adaptive Clustering Hierarchy (LEACH), Energy Efficient Hierarchical Clustering Algorithm (EEHCA) and Effective Data Gathering Algorithm (EDGA), respectively.

scholarly journals TEDDEEC: Threshold Enhanced Developed Distributed Energy-Efficient Clustering Protocol for Heterogeneous Wireless Sensor Networks

2015 ◽  
Vol 14 (6) ◽  
pp. 5789-5795
Author(s):  
Aditi Sharma ◽  
Harjit Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
The Other ◽  
Wireless Sensor ◽  
Distributed Energy ◽  
Clustering Protocol ◽  
Heterogeneous Wireless Sensor Networks ◽  
Save Energy ◽  
Energy Efficient Clustering

In wireless sensor networks, hundreds or thousands of sensor networks are deployed in a field to sense data (like temperature, light, pressure, sound etc.) and then they transmit it to sink nodes or base station via a radio transmitter. At one side where these networks have numerous applications, they suffer from a major disadvantage on the other side. These sensor nodes are power constrained and hence they have limited lifetime. Once deployed, these nodes cannot be recharged, therefore researchers are developing protocols to enhance network lifetime. Protocols had been modified one after the other so as to save energy during their every transmission. Clustering technique was used and it was found that it is more optimistic way to save energy. In this paper, we propose a new clustering protocol: Threshold Enhanced Developed and Distributed energy-Efficient Clustering Protocol (TEDDEEC) for heterogeneous wireless sensor networks. In this technique, a modified value of threshold is presented on which a node will decide whether to become CH or not. Simulation results show that this protocol outperforms as compared to its conventional counterparts.

An Energy Efficient Clustering Protocol Based on Niching Particle Swarm Optimization for Wireless Sensor Networks

2013 ◽  
Vol 475-476 ◽  
pp. 500-503
Author(s):  
De Xin Ma ◽  
Jian Ma ◽  
Peng Min Xu
Keyword(s):  
Wireless Sensor Networks ◽  
Particle Swarm Optimization ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Particle Swarm ◽  
Wireless Sensor ◽  
Swarm Optimization ◽  
Clustering Protocol ◽  
Energy Efficient Clustering

According to the energy constraints characteristics of Wireless Sensor Networks, how to optimize clustering, reduce the node energy consumption and balance the network energy dissipation is an main target, we proposes an Energy Efficient Clustering protocol based on Niching Particle Swarm Optimization (NPSO-EEC), the algorithm considers the factors such as the nodes residual energy and neighbor nodes status, etc. The simulation results show that the proposed protocol can balance the nodes energy consumption effectively, reduce the sensor nodes death rate, and prolong the network lifetime.

scholarly journals Energy Efficient Clustering for Wireless Sensor Networks using EASSR

2015 ◽  
Vol 15 (3) ◽  
pp. 554
Author(s):  
Y. Chalapathi Rao ◽  
Ch. Santhi Rani
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Average Energy ◽  
Rechargeable Batteries ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

<p>Wireless Sensor Networks (WSNs) consist of a large quantity of small and low cost sensor nodes powered by small non rechargeable batteries and furnish with various sensing devices. The cluster-based technique is one of the good perspectives to reduce energy consumption in WSNs. The lifetime of WSNs is maximized by using the uniform cluster location and balancing the network loading between the clusters. We have reviewed various energy efficient schemes apply in WSNs of which we concerted on clustering approach. So, in this paper we have discussed about few existing energy efficient clustering techniques and proposed an Energy Aware Sleep Scheduling Routing (EASSR) scheme for WSN in which some nodes are usually put to sleep to conserve energy, and this helps to prolong the network lifetime. EASSR selects a node as a cluster head if its residual energy is more than system average energy and have low energy consumption rate in existing round. The efforts of this scheme are, increase of network stability period, and minimize loss of sensed data. Performance analysis and compared statistic results show that EASSR has significant improvement over existing methods in terms of energy consumption, network lifetime and data units gathered at BS.</p>

scholarly journals Energy Efficient Clustering Protocol to Enhance Network Lifetime in Wireless Sensor Networks

2021 ◽  
Vol 68 (3) ◽  
pp. 3595-3614
Author(s):  
S. Nanthini ◽  
S. Nithya Kalyani ◽  
Sudhakar Sengan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Wireless Sensor ◽  
Clustering Protocol ◽  
Energy Efficient Clustering
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