scholarly journals Energy Efficient Model for Maximizing the Network Coverage Time in Non-Deterministic WSN Model

2019 ◽  
Vol 9 (2) ◽  
pp. 27-32
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Sensor Node ◽  
Deterministic Model ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Network Coverage ◽  
Node Placement ◽  
Node Location ◽  
Death And Loss

WSN are the group nodes and these nodes are grouped into several clusters, each cluster has its own CH (Cluster Head). Moreover, each cluster Head collects the data and sends either through the corresponding CH or through the CH. Moreover, the clustering plays one of the eminent role in WSN, since Clustering reduces the energy consumption in the cluster Head and improvises the lifetime and scalability of WSN. However, this maximizes the burden on the CH and certainly, it causes the coverage loss. Hence, in this paper we design a model named as EE-NCT (Energy Efficient model for maximizing the network coverage time) which helps in increasing the Network Coverage time for the non-deterministic model, i.e. Sensor nodes location are not known. Non –deterministic model makes hard to maximize, as the node placement is not known. Moreover, this is achieved through monitoring the sensor node location and applying the routing based clustering scheme. Our model is evaluated by considering the various constraint such as first sensor node death, 75% of node death and loss of connectivity by considering the parameter as energy consumption and average number of failed nodes

Nature-Inspired Algorithms in Wireless Sensor Networks

2019 ◽  
pp. 246-275
Author(s):  
Ajay Kaushik ◽  
S. Indu ◽  
Daya Gupta
Keyword(s):  
Wireless Sensor Networks ◽  
Big Data ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Sensor Node ◽  
Optimization Problem ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nature Inspired Algorithms

Wireless sensor networks (WSNs) are becoming increasingly popular due to their applications in a wide variety of areas. Sensor nodes in a WSN are battery operated which outlines the need of some novel protocols that allows the limited sensor node battery to be used in an efficient way. The authors propose the use of nature-inspired algorithms to achieve energy efficient and long-lasting WSN. Multiple nature-inspired techniques like BBO, EBBO, and PSO are proposed in this chapter to minimize the energy consumption in a WSN. A large amount of data is generated from WSNs in the form of sensed information which encourage the use of big data tools in WSN domain. WSN and big data are closely connected since the large amount of data emerging from sensors can only be handled using big data tools. The authors describe how the big data can be framed as an optimization problem and the optimization problem can be effectively solved using nature-inspired algorithms.

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 Energy-Efficient Unequal Clustering Routing Algorithm for WSNs

2019 ◽  
Vol 8 (3) ◽  
pp. 5540-5548
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Sensor Node ◽  
Routing Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Energy Balancing ◽  
Unequal Clustering ◽  
Network Nodes ◽  
New Energy

Wireless sensor networks(WSNs) are used to monitor the environment where the networks are deployed. The Lifetime of WSNs can be increased by energy-efficient or energy balancing algorithms. Balanced energy consumption among all nodes is the main issue. In this paper, a new energy-efficient unequal clustering routing protocol (EEUCR) has been presented. In this protocol, the area of the network is divided into the number of rings of unequal size and each ring is further divided into a number of clusters. Rings nearer to the base station(BS) have a smaller area and the area of rings keeps on increasing as the distance from BS increases. This helps to balance the energy consumption among the sensor nodes. The nodes with heterogeneous energy are deployed in the network. Nodes nearer to the base station have higher energy as compared to farther nodes. Static clustering is used but cluster heads(CHs) are not fixed and are elected on the basis of the remaining energy of the sensor node. Simulation results are compared with existing protocols and show improvement in energy consumption, which, in turn, increases the network lifetime of WSN and also balance the energy consumption of sensor node

scholarly journals Greedy Knapsack Based Energy Efficient Routing in WMSNS

2019 ◽  
Vol 8 (10) ◽  
pp. 1455-1461
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Sensor Node ◽  
Life Time ◽  
Residual Energy ◽  
Multimedia Data ◽  
Sensor Nodes ◽  
Wireless Multimedia ◽  
Energy Efficient Routing ◽  
Critical Situation

Managing the energy is very challenging in wireless multimedia sensor networks because of heavy consumption of energy by the sensor nodes. Multimedia data transmission contains heavy energy consumption operations such as sensing, aggregating, compressing and transferring the data from one sensor node to neighbour sensor node. Many routing techniques considers residual energy of a neighbour node to forward the data to that node. But, in reality a critical situation occurs where required energy is greater than individual neighbour node’s residual energy. In this situation it is not possible to select any neighbour node as a data forwarder. The proposed greedy knapsack based energy efficient routing algorithm (GKEERA) can address this critical situation very efficiently. And also a Two-in-One Mobile Sink (TIOMS) is used to provide the power supply and to collect the data from a battery drained sensor node. GKEERA improves the life time of a network by balancing the energy consumption between the neighbour nodes.

scholarly journals Energy-Efficient Clustering Multi-Hop Routing Protocol in a UWSN

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 627
Author(s):  
Nhat-Tien Nguyen ◽  
Thien T. T. Le ◽  
Huy-Hung Nguyen ◽  
Miroslav Voznak
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Depth Level ◽  
Large Numbers ◽  
Energy Efficient Clustering

Underwater wireless sensor networks are currently seeing broad research in various applications for human benefits. Large numbers of sensor nodes are being deployed in rivers and oceans to monitor the underwater environment. In the paper, we propose an energy-efficient clustering multi-hop routing protocol (EECMR) which can balance the energy consumption of these nodes and increase their network lifetime. The network area is divided into layers with regard to the depth level. The data sensed by the nodes are transmitted to a sink via a multi-hop routing path. The cluster head is selected according to the depth of the node and its residual energy. To transmit data from the node to the sink, the cluster head aggregates the data packet of all cluster members and then forwards them to the upper layer of the sink node. The simulation results show that EECMR is effective in terms of network lifetime and the nodes’ energy consumption.

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.

scholarly journals Improved energy efficient hierarchical cluster tree based routing to prolong network lifetime

2021 ◽  
Vol 9 (2) ◽  
pp. 694-706
Author(s):  
Venkatesh Prasad B S , Et. al.
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Large Scale ◽  
Cluster Head ◽  
Hierarchical Cluster ◽  
Base Station ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Cluster Tree

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.        

scholarly journals FOC-MOP – Fuzzy Optimal Clustering based Multi-Objective Parameter Route Selection for Energy Efficiency

2021 ◽  
Author(s):  
Pogula Sreed ◽  
S. Venkateswarlu
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Node Degree ◽  
Emperor Penguin ◽  
Delivery Ratio ◽  
Cluster Heads ◽  
Ch Selection

Abstract Recently, the research area interest towards the development of wireless sensor network (WSN) has increased. However, WSNs have one of significant issues as improving an energy-efficient routing protocol. A WSN has a crucial problem of energy consumption that effects the network lifetime as sensor nodes have a limitation of power. To overcome these limitations, it’s required to improve energy-efficient communication protocols for WSNs. Different types of techniques have considered by various research communities for providing energy-efficient solutions for WSNs. The energy consumption reduces using the clustering as an efficient data collection method and the collected data forward to a cluster-head which belong to the nodes in clustered networks. The information transmits to BS (base station) either in an uncompressed or compressed manner after collecting all data by a cluster-head from all member nodes. Based on other cluster-heads, the data transmit in a multi-hop network. Due to the heavy inter-cluster relay, earlier death happens to the cluster-heads (CHs) that locates very closely to the sink. Therefore, a fuzzy optimal CH selection algorithm has proposed to select the optimal CHs to improve the lifetime. Based on different parameters like cluster load, communication cost, neighbour density, node degree, inter and intra cluster distance, and node energy, the proposed algorithm of CH selection chooses the CHs. To determine an optimal route for transmitting the data from CH to sink, the modified Emperor Penguin Optimization (EPO) uses after selecting the CH. The proposed technique implements and compares with other earlier methods in terms of packet delivery ratio, lifetime, energy consumption, end to end delay and throughput. The proposed approach shows best performance than the other methods based on the simulation results.

scholarly journals A Modified Energy-Efficient Clustering with Splitting and Merging for Wireless Sensor Networks using Cluster-Head Handover Mechanism

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Abdoulie M.S. Tekanyi ◽  
Jinadu A Braimoh ◽  
Buba G Bajoga
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Cluster Head ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Modified Model ◽  
Handover Mechanism ◽  
Energy Efficient Clustering

Energy efficiency is one of the most important challenges for Wireless Sensor Networks (WSNs). This is due to the fact that sensor nodes have limited energy capacity. Therefore, the energy of sensor nodes has to be efficiently managed to provide longer lifetime for the network. To reduce energy consumption in WSNs, a modified Energy Efficient Clustering with Splitting and Merging (EECSM) for WSNs using Cluster-Head Handover Mechanism was implemented in this research. The modified model used information of the residual energy of sensor nodes to select backup Cluster Heads (CHs) while maintaining a suitable CH handover threshold to minimize energy consumption in the network. The backup CHs take over the responsibilities of the CHs once the handover threshold is reached. The modified model was validated in terms of network lifetime and residual energy ratio with EECSM using MATLAB R2013a. Average improvements of 7.5% and 50.7% were achieved for the network lifetime and residual energy ratio respectively which indicates a significant reduction in energy consumption of the network nodes. Keywords— Clustering, Energy-Efficiency, Handover, Lifetime, Wireless Sensor Network

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.

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