scholarly journals An Energy-Efficient Coverage Enhancement Strategy for Wireless Sensor Networks Based on a Dynamic Partition Algorithm for Cellular Grids and an Improved Vampire Bat Optimizer

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 619 ◽  
Author(s):  
Xiaoqiang Zhao ◽  
Yanpeng Cui ◽  
Zheng Guo ◽  
Zhanjun Hao

Sensor nodes perform missions based on the effectual invariable coverage of events, and it is commonly guaranteed by the determinate deployment for sensor nodes who deviate from the optimum site frequently. To reach the optimal coverage effect with the lowest costs is a primary goal of wireless sensor networks. In this paper, by splicing the sensing area optimally with cellular grids, the best deployment location for sensors and the required minimum number of them are revealed. The optimization problem of coverage rate and energy consumption is converted into a task assignment problem, and a dynamic partition algorithm for cellular grids is also proposed to improve the coverage effect when the number of sensors is variable. Furthermore, on the basis of solving the multi-objective problem of reducing and balancing the energy cost of sensors, the vampire bat optimizer is improved by introducing virtual bats and virtual preys, and finally solves the asymmetric assignment problem once the number of cellular grids is not equal to that of sensors. Simulation results indicate that the residual energy of sensors during redeployment is balanced notably by our strategy when compared to three other popular coverage-enhancement algorithms. Additionally, the total energy cost of sensor nodes and coverage rate can be optimized, and it also has a superior robustness when the number of nodes changes.

2016 ◽  
Vol 12 (07) ◽  
pp. 59
Author(s):  
Zeyu Sun ◽  
Yuanbo Li ◽  
Chuanfeng Li ◽  
Yalin Nie

<p><span style="font-family: Times New Roman;"><strong>The mismatch of task scheduling results in rapid network energy consumption during data transmission in wireless sensor networks. To address this issue, the paper proposed an </strong><strong>E</strong><strong>nergy-consumption </strong><strong>O</strong><strong>ptimization-oriented </strong><strong>T</strong><strong>ask </strong><strong>S</strong><strong>cheduling </strong><strong>A</strong><strong>lgorithm (EOTS algorithm) which formally described the overall power dissipation in the network system. On this basis, a network model was built up such that both the idle energy consumption in sensor nodes and energy consumption during the execution of tasks were taken into account, with which the whole task was effectively decomposed into sub-task sequences. They underwent simulated annealing and iterative refinement, with the intention of improving sensor nodes’ utilization rate, reducing local idle energy cost, as well as cutting down the overall energy consumption accordingly. The experiment result shows that under the environment of multi-task operation, from the perspective of energy cost optimization, the proposed scheduling strategy recorded an increase of 21.24% compared with the FIFO algorithm, and an increase of 16.77% in comparison to the EMRSA algorithm; while in light of network lifetimes, the EOTS algorithm surpassed the ECTA algorithm by a gain of 19.21%. Therefore, the effectiveness of the proposed EOTS algorithm is verified.</strong></span></p>


Many researches have been proposed for efficiency of data transmission from sensor nodes to sink node for energy efficiency in wireless sensor networks. Among them, cluster-based methods have been preferred In this study, we used the angle formed with the sink node and the distance of the cluster members to calculate the probability of cluster head. Each sensor node sends measurement values to header candidates, and the header candidate node measures the probability value of the header with the value received from its candidate member nodes. To construct the cluster members, the data transfer direction is considered. We consider angle, distance, and direction as cluster header possibility value. Experimental results show that data transmission is proceeding in the direction of going to the sink node. We calculated and displayed the header possibility value of the neighbor nodes of the sensor node and confirmed the candidates of the cluster header for data transfer as the value. In this study, residual energy amount of each sensor node is not considered. In the next study, we calculate the value considering the residual energy amount of the node when measuring the header possibility value of the cluster.


2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenjiang Zhang ◽  
Yanan Wang ◽  
Fuxing Song ◽  
Wenyu Zhang

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.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aaqil Somauroo ◽  
Vandana Bassoo

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.


2011 ◽  
Vol 474-476 ◽  
pp. 1221-1227
Author(s):  
Ying Liao ◽  
Wei Xu Hao

Wireless sensor networks (WSNs) detect and monitor the outside physical state by the sensor nodes organizing automatically. Utilizing clustering algorithm to form hierarchical network topology is the common method which implements managing network and aggregating data in WSNs. Different from the previous clustering algorithms, this article proposes a clustering algorithm for WSNs based on distance and distribution to generate clusters considering residual energy of nods in WSNs with inhomogeneous distribution. The simulation result indicates that the algorithm can establish more balanceable clustering structure effectively and enhance the network life cycle obviously.<b></b>


2015 ◽  
Vol 743 ◽  
pp. 748-752 ◽  
Author(s):  
L.F. Liu ◽  
P. Guo ◽  
J. Zhao ◽  
N. Li

Wireless sensor network routing protocol is to prolong the survival time of wireless sensor networks by using the sensor nodes energy efficiently. Traditional LEACH protocol is random in the election of the cluster head, if a less energy node is first elected as a cluster head node, then the node might die soon, it will greatly reducing the lifetime of the network. In order to collect data more efficiently and prolong the network life cycle,we need better clustering protocol. Aim at the traditional LEACH protocol have some weakness,this paper improve the protocol based on traditional LEACH protocol, two influence factors which the residual energy and the number of elected cluster head of the nodes had been introduced to make the clustering more ideal. Simulation results show that compared to the traditional Leach algorithm ,the improved LEACH protocol can prolong the network life cycle more effective and reduce the energy consumption of the whole network.


2012 ◽  
Vol 6-7 ◽  
pp. 831-835
Author(s):  
Chang Lin Ma ◽  
Yuan Ruan

In order to improve the lifetime and throughput of wireless sensor networks under the limited power, an improved clustering algorithm is proposed in this paper on the basis of LEACH protocol. The energy factor is considered in this algorithm. The residual energy of all sensor nodes is referred to select cluster-heads of wireless sensor networks. The new clustering algorithm effectively improves the energy efficiency, throughput and lifetime of wireless sensor networks. The results are proved by simulations.


2013 ◽  
Vol 11 (7) ◽  
pp. 2787-2791
Author(s):  
T. Lalitha ◽  
Jayanthila Devi ◽  
Dr.G.M. Kadh

Energy is an extremely critical resource for battery-powered wireless sensor networks (WSN), thus making energy-efficient protocol design a key challenging problem. Most of the existing energy-efficient routing protocols always forward packets along the minimum energy path to the sink to merely minimize energy consumption, which causes an unbalanced distribution of forming residue energy among sensor nodes, and eventually results in a network partition. In this paper, with the help of the concept of potential in physics, we design an Energy-Balanced Routing Protocol (EBRP) by constructing a mixed virtual potential field in terms of depth, energy density, and residual energy. The goal of this basic approach is to force packets to move toward the sink through the dense energy area to protect the nodes with relatively low residual energy. To address the routing loop problem emerging in this basic algorithm, enhanced mechanisms are proposed to detect and eliminate loops. The basic algorithm and loop elimination mechanism are first validated through extensive simulation experiments. 


2021 ◽  
Author(s):  
Meriem MEDDAH ◽  
Rim HADDAD ◽  
Tahar EZZEDDINE

Abstract Mobile Data Collector device (MDC) is adopted to reduce the energy consumption in Wireless Sensor Networks. This device travels the network in order to gather the collected data from sensor nodes. This paper presents a new Tree Clustering algorithm with Mobile Data Collector in Wireless Sensor Networks, which establishes the shortest travelling path passing throw a subset of Cluster Heads (CH). To select CHs, we adopt a competitive scheme, and the best sensor nodes are elected according to the number of packets forwarded between sensor nodes, the number of hops to the tree’s root, the residual energy, and the distance between the node and the closest CH. In simulation results, we adopt the balanced and unbalanced topologies and prove the efficiently of our proposed algorithm considering the network lifetime, the fairness index and the energy consumption in comparison with the existing mobile data collection algorithms.


Author(s):  
Abdul Rahaman Wahab Sait ◽  
◽  
M. Ilayaraja ◽  

Wireless sensor networks (WSN) encompass numerous sensor nodes deployed in the physical environment to sense parameters and transmit to the base station (BS). Since the nodes in WSN communicate via a wireless channel, security remains a significant issue that needs to be resolved. The choice of cluster heads (CHs) is critical to achieving secure data transmission in WSN. In this aspect, this article presents a novel trust-aware mothflame optimization-based secure clustering (TAMFO-SC) technique for WSN. The goal of the TAMFO-SC technique is to determine the trust level of the nodes and determine the secure CHs. The proposed TAMFO-SC technique initially determines the nodes' trust level, and the node with maximum trust factor can be chosen as CHs. In addition, the TAMFO-SC technique derives a fitness function using two parameters, namely residual energy and trust level. The inclusion of trust level in the CH selection process helps to accomplish security in WSN. A comprehensive experimental analysis exhibits the promising performance of the TAMFO-SC technique over the other compared methods.


Sign in / Sign up

Export Citation Format

Share Document