scholarly journals Energy-Efficient Connected-Coverage Scheme in Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6127 ◽  
Author(s):  
Yun Xu ◽  
Wanguo Jiao ◽  
Mengqiu Tian
Keyword(s):  
Routing Protocol ◽  
Energy Efficient ◽  
Sensor Node ◽  
Scheduling Algorithm ◽  
Cluster Head ◽  
Data Communication ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Scheduling

In the wireless sensor network, the lifetime of the network can be prolonged by improving the efficiency of limited energy. Existing works achieve better energy utilization, either through node scheduling or routing optimization. In this paper, an efficient solution combining node scheduling with routing protocol optimization is proposed in order to improve the network lifetime. Firstly, to avoid the redundant coverage, a node scheduling scheme that is based on a genetic algorithm is proposed to find the minimum number of sensor nodes to monitor all target points. Subsequently, the algorithm prolongs the lifetime of the network through choosing redundant sleep nodes to replace the dead node. Based on the obtained minimum coverage set, a new routing protocol, named Improved-Distributed Energy-Efficient Clustering (I-DEEC), is proposed. When considering the energy and the distance of the sensor node to the sink, a new policy choosing the cluster head is proposed. To make the energy load more balanced, uneven clusters are constructed. Meanwhile, the data communication way of sensor nodes around the sink is also optimized. The simulation results show that the proposed sensor node scheduling algorithm can reduce the number of redundant sensor nodes, while the I-DEEC routing protocol can improve the energy efficiency of data transmission. The lifetime of the network is greatly extended.

Combination of improved Harris’s hawk optimization with fuzzy to improve clustering in wireless sensor network

2021 ◽  
pp. 1-16
Author(s):  
V. Nivedhitha ◽  
P. Thirumurugan ◽  
A. Gopi Saminathan ◽  
V. Eswaramoorthy
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Fuzzy Inference ◽  
Cluster Head ◽  
Data Communication ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Distance

A Wireless Sensor Network (WSN) is divided into groups of sensor nodes for efficient transmission of data from the point of measuring to sink. By performing clustering, the network remains energy-efficient and stable. An intelligent mechanism is needed to cluster the sensors and find an organizer node, the cluster head. The organizer node assembles data from its constituent nodes called member nodes, finds an optimal route to the sink of the network, and transfers the same. The nomination of cluster head is crucial since energy utilization is a major challenge of sensor nodes deployed over a hostile environment. In this paper, a fuzzy-based Improved Harris’s Hawk Optimization Algorithm (IHHO) is proposed to select an able cluster head for data communication. The fuzzy inference model ponders balance energy, distance from self to sink node, and vicinity of nodes from cluster head as input factors and decides if a candidate node is eligible for becoming a cluster head. The IHHO tunes the logic into an energy-efficient network with less complexity and more ease. The novelty of the paper lies in applying the hawk-pack technique based on fuzzy rules. Simulations show that the combination of Fuzzy based IHHO reduces the death of nodes through which network lifetime is enhanced.

scholarly journals Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad Baniata ◽  
Jiman Hong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Chain Length ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Smart Cities ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor

The recent advances in sensing and communication technologies such as wireless sensor networks (WSN) have enabled low-priced distributed monitoring systems that are the foundation of smart cities. These advances are also helping to monitor smart cities and making our living environments workable. However, sensor nodes are constrained in energy supply if they have no constant power supply. Moreover, communication links can be easily failed because of unequal node energy depletion. The energy constraints and link failures affect the performance and quality of the sensor network. Therefore, designing a routing protocol that minimizes energy consumption and maximizes the network lifetime should be considered in the design of the routing protocol for WSN. In this paper, we propose an Energy-Efficient Unequal Chain Length Clustering (EEUCLC) protocol which has a suboptimal multihop routing algorithm to reduce the burden on the cluster head and a probability-based cluster head selection algorithm to prolong the network lifetime. Simulation results show that the EEUCLC mechanism enhanced the energy balance and prolonged the network lifetime compared to other related protocols.

Mutual Exclusive Sleep Awake Energy Efficient Distributive (MESAEED) Clustering: An Approach for Enhancing Lifetime of Wireless Sensor Network

2019 ◽  
Vol 16 (9) ◽  
pp. 3925-3931
Author(s):  
Bhupesh Gupta ◽  
Sanjeev Rana
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Sensor Node ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
A Algorithm ◽  
Extension Work ◽  
Simulation Purpose

For resource constraint network, one uses wireless sensor network in which limited resources are there for sensor nodes. Basic aim of sensor node is to sense something, monitor it and explain it. The issue arises for sensor node is its battery endurance. The battery endurance of sensor node is consuming in communication instead of sensing. In this regard clustering is using now a day’s which reduces endurance consumption. This paper comes with a new clustering protocol MESAEED (Mutual Exclusive Sleep Awake Energy Efficient Distributed clustering), which helps in saving endurance of sensor nodes so that network lifetime will prolong. It is an extension work of previous work MESADC. In previous work cluster head is chooses on the basis of sleep awake mode in mutual exclusive way under communication range and the results were obtained with the help of comparison graph between HEED and MESADC. The proposed MESAEED protocol provides benefit of A* algorithm of heuristic search, HEED and MESADC. MATLAB 8.3 is use for simulation purpose. The comparison graph between HEED, MESADC and proposed MESAEED were shown. Parameters for comparison include alive nodes versus number of rounds taken and number of nodes dead versus number of rounds taken. The graph shows improvement in performance over HEED and MESADC, which results in enhancing lifetime of WSN.

scholarly journals A sensor node scheduling algorithm for heterogeneous wireless sensor networks

2019 ◽  
Vol 15 (1) ◽  
pp. 155014771982631 ◽  
Author(s):  
Zhangquan Wang ◽  
Yourong Chen ◽  
Banteng Liu ◽  
Haibo Yang ◽  
Ziyi Su ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Optimization Model ◽  
Sensor Node ◽  
Scheduling Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Scheduling ◽  
Heterogeneous Wireless Sensor Networks

To improve the regional coverage rate and network lifetime of heterogeneous wireless sensor networks, a sensor node scheduling algorithm for heterogeneous wireless sensor networks is proposed. In sensor node scheduling algorithm, heterogeneous perception radius of sensor node is considered. Incomplete coverage constraint and arc coverage interval are analyzed. Regional coverage increment optimization model, arc coverage increment optimization model, and residual energy optimization model are proposed. Multi-objective scheduling model is established using weight factors and integrated function. Furthermore, the heuristic method is proposed to solve the multi-objective optimization model, and scheduling scheme of heterogeneous sensor nodes is obtained. When the network is in operation for a period of time, some sensor nodes are invalid and relevant regions are uncovered. The repair method is proposed to wake up sleep sensor nodes and repair the coverage blind area. The simulation results show that if keeping the same regional coverage rate, sensor node scheduling algorithm improves network lifetime, increases number of living sensor nodes, and keeps average node energy consumption at a low level. Under certain conditions, sensor node scheduling algorithm outperforms DGREEDY, two-tiered scheduling, and minimum connected cover.

Improvement on LEACH Protocol of Wireless Sensor Network

2013 ◽  
Vol 347-350 ◽  
pp. 1738-1742 ◽  
Author(s):  
Xiao Wen Ma ◽  
Xiang Yu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Routing ◽  
Leach Protocol ◽  
Steady State Simulation

Wireless sensor networks comprise of minor battery driven devices with restricted energy resources.Once installed,the minor sensor nodes are usually unapproachable to the operator, and thus auxiliary of the energy source is not practicable.Hence,energy proficiency is a vital design issue that needs to be boosted in order to increase the lifetime of the network. LEACH is a popular hierarchical routing protocol which efficiently maintains the energy storage of nodes in Wireless Sensor Network (WSN).The nodes using LEACH are divided into clusters.The advantage of LEACH is that each node has the equal probability to be a cluster head,which makes the energy dissipation of each node be relatively balanced. This paper studies LEACH protocol, and focuses on how to decide the next hop nodes more reasonable when the data are transmitted at the steady state. Simulation has been done in NS2 and the results show that the algorithm after improved is more energy-efficient than LEACH protocol.

Sector Tree-Based Clustering for Energy Efficient Routing Protocol in Heterogeneous Wireless Sensor Network

2021 ◽  
Vol 13 (5) ◽  
pp. 57-74
Author(s):  
Nguyen Duy Tan ◽  
Vu Khanh Quy ◽  
Pham Ngoc Hung ◽  
Le Van Vinh
Keyword(s):  
Routing Protocol ◽  
Energy Efficient ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Power Efficient ◽  
Heterogeneous Wireless Sensor Network ◽  
Mixed Distance

One of the main challenges for researchers to build routing protocols is how to use energy efficiently to extend the lifespan of the whole wireless sensor networks (WSN) because sensor nodes have limited battery power resources. In this work, we propose a Sector Tree-Based clustering routing protocol (STB-EE) for Energy Efficiency to cope with this problem, where the entire network area is partitioned into dynamic sectors (clusters), which balance the number of alive nodes. The nodes in each sector only communicate with their nearest neighbour by constructing a minimum tree based on the Kruskal algorithm and using mixed distance from candidate node to base station (BS) and remaining energy of candidate nodes to determine which node will become the cluster head (CH) in each cluster? By calculating the duration of time in each round for suitability, STB-EE increases the number of data packets sent to the BS. Our simulation results show that the network lifespan using STB-EE can be improved by about 16% and 10% in comparison to power-efficient gathering in sensor information system (PEGASIS) and energy-efficient PEGASIS-based protocol (IEEPB), respectively.

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

A Survey on Hierarchical Cluster Based Secure Routing Protocols and Key Management Schemes in Wireless Sensor Networks

2018 ◽  
pp. 18-26
Author(s):  
Yugashree Bhadane ◽  
Pooja Kadam
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Key Management ◽  
Energy Efficient ◽  
Base Station ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Management Schemes ◽  
Cluster Based Routing

Now days, wireless technology is one of the center of attention for users and researchers. Wireless network is a network having large number of sensor nodes and hence called as “Wireless Sensor Network (WSN)”. WSN monitors and senses the environment of targeted area. The sensor nodes in WSN transmit data to the base station depending on the application. These sensor nodes communicate with each other and routing is selected on the basis of routing protocols which are application specific. Based on network structure, routing protocols in WSN can be divided into two categories: flat routing, hierarchical or cluster based routing, location based routing. Out of these, hierarchical or cluster based routing is becoming an active branch of routing technology in WSN. To allow base station to receive unaltered or original data, routing protocol should be energy-efficient and secure. To fulfill this, Hierarchical or Cluster base routing protocol for WSN is the most energy-efficient among other routing protocols. Hence, in this paper, we present a survey on different hierarchical clustered routing techniques for WSN. We also present the key management schemes to provide security in WSN. Further we study and compare secure hierarchical routing protocols based on various criteria.

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

Quasi Oppositional Glowworm Swarm Optimization Algorithm for Energy Efficient Clustering in Wireless Sensor Networks

2020 ◽  
Vol 17 (12) ◽  
pp. 5447-5456
Author(s):  
R. M. Alamelu ◽  
K. Prabu
Keyword(s):  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Link Quality ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Degree ◽  
Swarm Optimization ◽  
Glowworm Swarm Optimization ◽  
Energy Efficient Clustering

Wireless sensor network (WSN) becomes popular due to its applicability in distinct application areas like healthcare, military, search and rescue operations, etc. In WSN, the sensor nodes undergo deployment in massive number which operates autonomously in harsh environment. Because of limited resources and battery operated sensor nodes, energy efficiency is considered as a main design issue. To achieve, clustering is one of the effective technique which organizes the set of nodes into clusters and cluster head (CH) selection takes place. This paper presents a new Quasi Oppositional Glowworm Swarm Optimization (QOGSO) algorithm for energy efficient clustering in WSN. The proposed QOGSO algorithm is intended to elect the CHs among the sensor nodes using a set of parameters namely residual energy, communication cost, link quality, node degree and node marginality. The QOGSO algorithm incorporates quasi oppositional based learning (QOBL) concept to improvise the convergence rate of GSO technique. The QOGSO algorithm effectively selects the CHs and organizes clusters for minimized energy dissipation and maximum network lifetime. The performance of the QOGSO algorithm has been evaluated and the results are assessed interms of distinct evaluation parameters.

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