scholarly journals An Efficent Coverage and Maximization of Network Lifetime in WSN Through Metaheuristics

2021 ◽  
Vol 10 (3) ◽  
pp. 159
Author(s):  
A. Nageswar Rao ◽  
B. Rajendra Naik ◽  
L. Nirmala Devi
Keyword(s):  
Network Lifetime ◽  
Sensor Node ◽  
Relay Node ◽  
Base Station ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Relay Node Placement ◽  
Data Forwarding ◽  
Relay Nodes ◽  
Node Placement

<span>In wireless sensor networks (WSNs), energy, connectivity, and coverage are the three most important constraints for guaranteed data forwarding from every sensor node to the base station. Due to continuous sensing and transmission tasks, the sensor nodes deplete more quickly and hence they seek the help of data forwarding nodes, called relay nodes. However, for a given set of sensor nodes, finding optimal locations to place relay nodes is a very challenging problem. Moreover, from the earlier studies, the relay node placement is defined as a non-deterministic polynomial tree hard (NP-Hard) problem. To solve this problem, we propose a multi-objective firefly algorithm-based relay node placement (MOFF-RNP) to deploy an optimal number of relay nodes while considering connectivity, coverage, and energy constraints. To achieve network lifetime, this work adopted energy harvesting capabilities to the sensor nodes and backup relay strategy such that every sensor node is always connected to at least one relay to forward the data. The optimal relay placement is formulated as an objective function and MOFF is applied to achieve a better solution. Extensive Simulations are carried out over the proposed model to validate the performance and the obtained results are compared with state-of-art methods)</span>

scholarly journals Clustered Relay Node Placement for WSN through Metaheuristics Algorithm

2020 ◽  
Vol 13 (6) ◽  
pp. 67-80
Author(s):  
Nageswar Amgoth ◽  
◽  
Rajendra Bhukya ◽  
Nirmala Lavadya ◽  
◽  
...  
Keyword(s):  
Network Lifetime ◽  
Average Energy ◽  
Relay Node ◽  
Critical Issue ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Relay Node Placement ◽  
Node Placement ◽  
Multi Objective

In the field of Wireless Sensor Networks (WSNs), after the deployment of sensor nodes, transmission of data with an effective energy is becoming a critical issue due to the limited battery of sensor nodes. To solve this issue, most of the past developed approaches focused on the implementation of clustering in which the sensor nodes forward their data through Cluster Heads (CHs) to Base Station (BS). However, the main issue is to select an optimal CH or CHs such that every sensor node is ensured with at least one path to base station, directly, through CHs or through relay nodes. Towards this objective, we have proposed a new method called Multi-Objective Assisted Clustered Relay Node Placement (MOCRNP) to achieve improved energy efficiency along with an enhanced network lifespan. Firstly, to select the CH, the Multi-Objective Genetic Algorithm is introduced based on energy, distance and node density. Secondly, in the process of rely node placement, Multi-objective firefly algorithm is introduced and for this purpose, two constraints such as Coverage and Connectivity are considered. We have conducted several experimentations using several setups of the WSN and the performance is evaluated in terms of Network lifetime, average energy consumption, average residual energy, and throughput. On an average, the proposed approach has gained an improvement of 150 sec network lifetime, 104 Kbps Throughput when compared with state-of-art methods.

scholarly journals LOCATION AWARE CLUSTER BASED ROUTING IN WIRELESS SENSOR NETWORKS

2015 ◽  
pp. 36-41
Author(s):  
S. JERUSHA ◽  
K. KULOTHUNGAN ◽  
A Kannan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Network ◽  
Network Lifetime ◽  
Minimum Distance ◽  
Sensor Node ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor

Wireless sensor nodes are usually embedded in the physical environment and report sensed data to a central base station. Clustering is one of the most challenging issues in wireless sensor networks. This paper proposes a new cluster scheme for wireless sensor network by modified the K means clustering algorithm. Sensor nodes are deployed in a harsh environment and randomly scattered in the region of interest and are deployed in a flat architecture. The transmission of packet will reduce the network lifetime. Thus, clustering scheme is required to avoid network traffic and increase overall network lifetime. In order to cluster the sensor nodes that are deployed in the sensor network, the location information of each sensor node should be known. By knowing the location of the each sensor node in the wireless sensor network, clustering is formed based on the highest residual energy and minimum distance from the base station. Among the group of nodes, one node is elected as a cluster head using centroid method. The minimum distance between the cluster node’s and the centroid point is elected as a cluster head. Clustering of nodes can minimize the residual energy and maximize the network performance. This improves the overall network lifetime and reduces network traffic.

scholarly journals Linear Time Approximation Algorithms for the Relay Node Placement Problem in Wireless Sensor Networks with Hexagon Tessellation

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Chi-Chang Chen ◽  
Chi-Yu Chang ◽  
Po-Ying Chen
Keyword(s):  
Approximation Algorithm ◽  
Linear Time ◽  
Relay Node ◽  
Wireless Sensor ◽  
Relay Node Placement ◽  
Relay Nodes ◽  
Placement Problem ◽  
Worst Case ◽  
Time Approximation ◽  
Node Placement

The relay node placement problem in wireless sensor network (WSN) aims at deploying the minimum number of relay nodes over the network so that each sensor can communicate with at least one relay node. When the deployed relay nodes are homogeneous and their communication ranges are circular, one way to solve the WSN relay node placement problem is to solve the minimum geometric disk cover (MGDC) problem first and place the relay nodes at the centers of the covering disks and then, if necessary, deploy additional relay nodes to meet the connection requirement of relay nodes. It is known that the MGDC problem is NP-complete. A novel linear time approximation algorithm for the MGDC problem is proposed, which identifies covering disks using the regular hexagon tessellation of the plane with bounded area. The approximation ratio of the proposed algorithm is (5+ϵ), where0<ϵ≤15. Experimental results show that the worst case is rare, and on average the proposed algorithm uses less than 1.7 times the optimal disks of the MGDC problem. In cases where quick deployment is necessary, this study provides a fast 7-approximation algorithm which uses on average less than twice the optimal number of relay nodes in the simulation.

A Grid-Based Relay Node Placement Algorithm in Wireless Sensor Networks

2013 ◽  
Vol 385-386 ◽  
pp. 1632-1637
Author(s):  
Zhu Wang ◽  
Cui Cui Lv ◽  
Ling Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Relay Node ◽  
Network Connectivity ◽  
Wireless Sensor ◽  
Physical Factors ◽  
Relay Node Placement ◽  
Relay Nodes ◽  
Node Placement ◽  
Placement Algorithm

The relay node placement in wireless sensor networks is usually constrained by physical factors, while most of present relay node placement approaches are unconstrained. To solve the problem, the paper presents a constrained relay node placement algorithm. Based on grid routing mechanism, the algorithm determines the grid intersections as candidates for the relay node locations, and places as fewer relay nodes as possible to assure the network connectivity. Consideration must be given to both the number of relay nodes and energy efficient, the paper uses the greedy norm and constrains to place relay nodes. By the analysis and study of the experiments, the performance of the proposed algorithm is more superior to the algorithm without constrains.

Fuzzy Logic-Based Cluster Heads Percentage Calculation for Improving the Performance of the LEACH Protocol

Fuzzy Systems ◽  
2017 ◽  
pp. 609-627 ◽  
Author(s):  
Omar Banimelhem ◽  
Eyad Taqieddin ◽  
Moad Y. Mowafi ◽  
Fahed Awad ◽  
Feda' Al-Ma'aqbeh
Keyword(s):  
Fuzzy Logic ◽  
Network Lifetime ◽  
Sensor Node ◽  
Base Station ◽  
Sensor Nodes ◽  
Number Of Clusters ◽  
Network Characteristics ◽  
Clustering Protocol ◽  
Proper Number ◽  
Leach Protocol

In wireless sensor networks, cluster-based routing was proven to be the most energy-efficient strategy to deal with the scaling problem. In addition, selecting the proper number of clusters is a critical decision that can impose a significant impact on the energy consumption and the network lifetime. This paper presents FL-LEACH, a variant of the well-known LEACH clustering protocol, which attempts to relax the stringent strategy of determining the number of clusters used by LEACH via fuzzy logic decision-making scheme. This relates the number of clusters to a number of network characteristics such as the number of sensor nodes, the area of the sensing field, and the location of the base station. The performance of FL-LEACH was evaluated via simulation and was compared against LEACH using standard metrics such as network lifetime and remaining network energy. The results depicted that the proposed approach has the potential to substantially conserve the sensor node energy and extend lifetime of the network.

Research on Fault-Tolerant Relay Node Placement Based on Greedy Optimization Algorithm in Wireless Sensor Networks

2011 ◽  
Vol 204-210 ◽  
pp. 1000-1004
Author(s):  
Zhu Wang ◽  
Qi Wang ◽  
De Bao Wei
Keyword(s):  
Optimization Algorithm ◽  
Fault Tolerant ◽  
Relay Node ◽  
Relay Node Placement ◽  
Relay Nodes ◽  
Evaluation Standard ◽  
Node Placement ◽  
Communication Capacity ◽  
Placement Algorithm ◽  
Greedy Optimization

In this paper, relay node’s communication capacity was introduced into the existing model of relay node placement. And we presented a new evaluation standard based on the minimum distance factor of communication network. A new relay node placement algorithm was implemented in solutions, and the algorithm was based on greedy optimization algorithm. The simulation result demonstrates that the algorithm can limit the communication capacity of relay nodes conveniently. Compared with other placement algorithms, improvement of energy-efficiencies in this algorithm is obvious.

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