scholarly journals An Algorithmic Approach to the Node Selection Problem in Industrial Wireless Sensor Networks

2021 ◽  
Author(s):  
Veeramani Sonai ◽  
Indira Bharathi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Industrial Wireless Sensor Networks ◽  
Placement Problem ◽  
Node Placement ◽  
Minimum Number ◽  
Sink Node Placement

Industrial Wireless Sensor Networks (IWSN) are the special class of WSN where it faces many challenges like improving process efficiency and meet the financial requirement of the industry. Most of the IWSNs contains a large number of sensor nodes over the deployment field. Due to lack of predetermined network infrastructure demands, IWSNs to deploy a minimum number of sink nodes and maintain network connectivity with other sensor nodes. Capacitated Sink Node Placement Problem (CSNPP) finds its application in the Industrial wireless sensor network (IWSN), for the appropriate placement of sink nodes. The problem of placing a minimum number of sink nodes in a weighted topology such that each sink node should have a maximum number of sensor nodes within the given capacity is known as Capacitated Sink Node Placement Problem. This chapter proposes a heuristic based approach to solve Capacitated Sink Node Placement Problem.

scholarly journals Optimal Sink Node Placement in Large Scale Wireless Sensor Networks Based on Harris’ Hawk Optimization Algorithm

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 19381-19397 ◽  
Author(s):  
Essam H. Houssein ◽  
Mohammed R. Saad ◽  
Kashif Hussain ◽  
William Zhu ◽  
Hassan Shaban ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Algorithm ◽  
Large Scale ◽  
Wireless Sensor ◽  
Sink Node ◽  
Node Placement ◽  
Sink Node Placement

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

scholarly journals Qualification of Cluster Header and Cluster Member in Wireless Sensor Networks

2019 ◽  
Vol 8 (2S6) ◽  
pp. 101-105
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Sensor Node ◽  
Data Transfer ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node

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.

scholarly journals Sensor Duty Cycle for Prolonging Network Lifetime Using Quantum Clone Grey Wolf Optimization Algorithm in Industrial Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yang Liu ◽  
Jing Xiao ◽  
Chaoqun Li ◽  
Hu Qin ◽  
Jie Zhou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Duty Cycle ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Maintenance Cost ◽  
Local Optimum ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Industrial Wireless Sensor Networks

The application of industrial wireless sensor networks (IWSNs) frequently appears in modern industry, and it is usually to deploy a large quantity of sensor nodes in the monitoring area. This way of deployment improves the robustness of the IWSNs but introduces many redundant nodes, thereby increasing unnecessary overhead. The purpose of this paper is to increase the lifetime of IWSNs without changing the physical facilities and ensuring the coverage of sensors as much as possible. Therefore, we propose a quantum clone grey wolf optimization (QCGWO) algorithm, design a sensor duty cycle model (SDCM) based on real factory conditions, and use the QCGWO to optimize the SDCM. Specifically, QCGWO combines the concept of quantum computing and the clone operation for avoiding the algorithm from falling into a local optimum. Subsequently, we compare the proposed algorithm with the genetic algorithm (GA) and simulated annealing (SA) algorithm. The experimental results suggest that the lifetime of the IWSNs based on QCGWO is longer than that of GA and SA, and the convergence speed of QCGWO is also faster than that of GA and SA. In comparison with the traditional IWSN working mode, our model and algorithm can effectively prolong the lifetime of IWSNs, thus greatly reducing the maintenance cost without replacing sensor nodes in actual industrial production.

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.

scholarly journals Delay and Lifetime Issues for Wireless Sensor Networks

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1199-1203
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Joint Control ◽  
Sink Node ◽  
Neighboring Node ◽  
Main Factors ◽  
Event Based

The network delay and power consumptions are the two main factors governing the efficiency of wireless sensor networks. In this paper, our goal is to minimize the delay and maximize the lifespan of event-based wireless sensor networks in which activities occur infrequently.In such architectures, most of the power is fed on when the radios are on, ready for a packet to arrive.Sleep–wake scheduling is a highly efficient mechanism to prolong the lifetime of these power-constrained wireless sensor networks. However, sleep–wake scheduling could provide result with considerable delays. This research attempts to limit these delays by developing “anycast” based packet forwarding schemes that places each node opportunistically forwards a packet to the first neighboring node which wakes up amongst more than one candidate nodes.In this paper, we propose to optimize the anycast forwarding schemes by minimizing the anticipated packetdelivery delays from the sensor nodes to the sink node. Based on this analysis, we then provide a solution to the joint control problem of how to optimally manage the architecture parameters of the sleep–wake scheduling protocol and the any-cast packetforwarding protocol to maximize the network lifetime, with reference to a constraint on the expected end-to-end packetarriving delay.

scholarly journals SALP Swarm Optimization Approach for Maximization The Lifetime of Wireless Sensor Network

2021 ◽  
Vol 1 (2) ◽  
pp. 16-20
Author(s):  
Mohammed M. Ahmed*
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Minimum Spanning Tree ◽  
Fitness Function ◽  
Shortest Paths ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimization Approach ◽  
Sink Node ◽  
Swarm Optimization

In recent years, the maximization of a lifetime for wireless sensor networks is considered an important area for researchers. The wireless sensor networks (WSNs) contain two types of sensors that called sensor nodes and sink nodes which sensor node send information to the central node (sink node) that collected its data. Choosing the best location of sink node considered the critical problem that faces the lifetime of wireless sensor networks. In this paper, we propose a method that choosing best location of a sink node by applying Salp Swarm Algorithm (SSA) after determining sink node location we create transmission paths between the sink node and rest of nodes using Prim's minimum spanning tree to choose shortest paths. Accordingly, for fitness function that used to decrease energy consumption for a network. Simulation results clarify that our proposed algorithm that solves localization of sink node presents the best results for prolonging the network's lifetime compared to Cat Swarm Optimization algorithm (CSA) and Particle Swarm Optimization (PSO).

Sign in / Sign up

Export Citation Format

Share Document