scholarly journals An energy consumption minimization approach in wireless sensor networks

2021 ◽  
Vol 22 (3) ◽  
pp. 1485
Author(s):  
Muhsin J. Al-Amery ◽  
Mohammed H. Ghadban
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
General System ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
System Life ◽  
Time Division

There is no doubt that the most challenging aspect in the wireless sensor networks (WSN) is the lifetime, due to limitations in their energy. WSN depends on a specific group of sensor nodes to gather the data from other nodes and forward it to the base station (BS). These nodes are called cluster heads. Having reliable cluster head’s (CH) means longer life to the network. In this paper, a versatile calculation has been acquainted and analyzed for selecting the CH that maintains the least vitality utilization in the network with appropriate life time during every correspondence round. The altered methodology depends on the improved calendar of the time division multiple access (TDMA) plans. This methodology is created to decide the next CH based on lifetime, expended vitality, number of CH’s, and the frequent contact to the BS. A comparative analysis is introduced, the proposed algorithm assistant cluster heads (ACHS) shows energizing outcomes in vitality utilization in WSNs just as expanding the general system dependability with reasonable viability and productivity in terms of lifetime. The ACHS strategy shows a decrease in the WSN vitality utilization up to about 25% and shows an expansion in the system life time by 30% than the upgraded timetable of time TDMA plan approach.

Clustering Algorithm to Reduce Power Consumptions for Wireless Sensor Networks

2012 ◽  
Vol 433-440 ◽  
pp. 5228-5232
Author(s):  
Mohammad Ahmadi ◽  
Hamid Faraji ◽  
Hossien Zohrevand
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection ◽  
Cluster Heads

A sensor network has many sensor nodes with limited energy. One of the important issues in these networks is the increase of the life time of the network. In this article, a clustering algorithm is introduced for wireless sensor networks that considering the parameters of distance and remaining energy of each node in the process of cluster head selection. The introduced algorithm is able to reduce the amount of consumed energy in the network. In this algorithm, the nodes that have more energy and less distance from the base station more probably will become cluster heads. Also, we use algorithm for finding the shortest path between cluster heads and base station. The results of simulation with the help of Matlab software show that the proposed algorithm increase the life time of the network compared with LEACH algorithm.

An Improvement Routing Protocol Based LEACH for Wireless Sensor Networks

2014 ◽  
Vol 614 ◽  
pp. 472-475 ◽  
Author(s):  
Jin Gang Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Base Station ◽  
Optimal Number ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Number Of Clusters ◽  
Cluster Heads

Due to limited energy, computing ability, and memory of Wireless sensor Networks(WSN), routing issue is one of the key factors for WSN. LEACH is the first clustering routing protocol, which can efficiently reduce the energy consumption and prolong the lifetime of WSN, but it also has some disadvantage. This paper proposed an improvement based LEACH, called LEACH-T. According to different number of clusters, LEACH-T uses variable time slot for different clusters in steady-state phase, and single-hop or multi-hop to transmit data between cluster heads and Base Station. Also it considered residual energy of sensor nodes and the optimal number of clusters during selection of the cluster heads. The simulation results show that LEACH-T has better performance than LEACH for prolonging the lifetime and reducing the energy consumption.

scholarly journals Differential Evolution Algorithm with Diversified Vicinity Operator for Optimal Routing and Clustering of Energy Efficient Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Subramaniam Sumithra ◽  
T. Aruldoss Albert Victoire
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Routing Problem

Due to large dimension of clusters and increasing size of sensor nodes, finding the optimal route and cluster for large wireless sensor networks (WSN) seems to be highly complex and cumbersome. This paper proposes a new method to determine a reasonably better solution of the clustering and routing problem with the highest concern of efficient energy consumption of the sensor nodes for extending network life time. The proposed method is based on the Differential Evolution (DE) algorithm with an improvised search operator called Diversified Vicinity Procedure (DVP), which models a trade-off between energy consumption of the cluster heads and delay in forwarding the data packets. The obtained route using the proposed method from all the gateways to the base station is comparatively lesser in overall distance with less number of data forwards. Extensive numerical experiments demonstrate the superiority of the proposed method in managing energy consumption of the WSN and the results are compared with the other algorithms reported in the literature.

scholarly journals Hybrid Swarm Intelligence Energy Efficient Clustered Routing Algorithm for Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Rajeev Kumar ◽  
Dilip Kumar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Data Transmission ◽  
Energy Efficient ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Abc Algorithm ◽  
Cluster Heads

Currently, wireless sensor networks (WSNs) are used in many applications, namely, environment monitoring, disaster management, industrial automation, and medical electronics. Sensor nodes carry many limitations like low battery life, small memory space, and limited computing capability. To create a wireless sensor network more energy efficient, swarm intelligence technique has been applied to resolve many optimization issues in WSNs. In many existing clustering techniques an artificial bee colony (ABC) algorithm is utilized to collect information from the field periodically. Nevertheless, in the event based applications, an ant colony optimization (ACO) is a good solution to enhance the network lifespan. In this paper, we combine both algorithms (i.e., ABC and ACO) and propose a new hybrid ABCACO algorithm to solve a Nondeterministic Polynomial (NP) hard and finite problem of WSNs. ABCACO algorithm is divided into three main parts: (i) selection of optimal number of subregions and further subregion parts, (ii) cluster head selection using ABC algorithm, and (iii) efficient data transmission using ACO algorithm. We use a hierarchical clustering technique for data transmission; the data is transmitted from member nodes to the subcluster heads and then from subcluster heads to the elected cluster heads based on some threshold value. Cluster heads use an ACO algorithm to discover the best route for data transmission to the base station (BS). The proposed approach is very useful in designing the framework for forest fire detection and monitoring. The simulation results show that the ABCACO algorithm enhances the stability period by 60% and also improves the goodput by 31% against LEACH and WSNCABC, respectively.

DATA GATHERING AND COMMUNICATION FOR WIRELESS SENSOR NETWORKS — A CENTRALIZED APPROACH

2005 ◽  
Vol 02 (04) ◽  
pp. 267-278 ◽  
Author(s):  
PETER X. LIU ◽  
NANCY DING
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Gathering ◽  
Life Time ◽  
Optimization Method ◽  
Chain Structure ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
The Social

This paper introduces a centralized approach to data gathering and communication for wireless sensor networks. Inspired by the social behaviors of natural ants, we clearly partition the task for the base station and sensor nodes in a wireless sensor network according to their different functions and capabilities. An ant colony optimization method is employed at the base station to form a near-optimal chain for sensor nodes to transmit collected data. Sensor nodes in the network then form a bi-direction chain structure, which is self-adaptive to any minor changes of the network topology. The simulation results show that the developed algorithm, which we call AntChain algorithm, performs much better than many other protocols in terms of energy efficiency, data integrity and life time when the base station is near where the sensor nodes are deployed.

An Energy-Efficient Unequal Clustering Algorithm in Wireless Sensor Networks

2012 ◽  
Vol 629 ◽  
pp. 801-807 ◽  
Author(s):  
Run Ze Wan ◽  
Jian Jun Lei ◽  
Qing Wei Xu ◽  
Xi Mei Gou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Life Time ◽  
Base Station ◽  
Energy Utilization ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Cluster Heads

For wireless sensor networks, clustering algori-thms provides an effective way to prolong the life time using the multi-hop forwarding model. Nevertheless, they rarely consider the hot spots problem and the problem of unbalanced energy consumption among cluster heads. To solve the problems, we proposed an energy-efficient unequal clustering algorithm with the ideal of unequal clustering in the circle area where the cluster heads are in charge of different geographical scope according to different distance to the base station. Considering the cluster heads closer to the BS be burdened with heavy relay traffic, the cluster in inner layers, which is closer to the base station, is smaller than the outer layer. It could reduce the number of cluster members and lead to the proportional energy dissipation in each layer. Simulation results show that our algorithm improve energy utilization and prolonged the life of the entire Wireless Sensor Networks effectively.

K-Centers Clustering Protocol over Heterogeneous Wireless Sensor Networks

2014 ◽  
Vol 6 (4) ◽  
pp. 42-54
Author(s):  
Qing Yan Xie ◽  
Yizong Cheng ◽  
Qing-An Zeng
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Routing ◽  
Cluster Heads ◽  
Clustering Protocol ◽  
Heterogeneous Wireless Sensor Networks

This paper introduces a K-Centers clustering protocol for heterogeneous wireless sensor networks. Energy consumption is an important issue for wireless sensor networks, and sensor nodes consume most of their energy with data delivery. The energy needed to transmit data is proportional to the distance between sensor nodes and either cluster heads or a base station. Clustering is an efficient technique for saving energy and extending network life. The authors' protocol uses a K-centers clustering algorithm to alter the network, topology and establish data routing. The result is k cluster heads which accommodate the distribution of sensor nodes and achieve minimum maximum intra-cluster distances. Their simulations show that their algorithm will outperform K-Means under many but not all conditions. The authors' always produce better minimum maximum intra-cluster distances compared to K-means.

scholarly journals Tree Based Energy Balancing Routing Protocol by Self Organizing in Wireless Sensor Networks

2015 ◽  
Vol 5 (6) ◽  
pp. 1486
Author(s):  
Syed Umar ◽  
P.V.R. D Prasada Rao ◽  
Sridevi Gutta
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Balancing ◽  
Self Organizing

Today the wireless sensor networks (WSN) play a crucial role in wireless technology in various domains like military, medicine, communications etc. The energy conservation is the crucial factor in the WSN. The WSN is a system which has more number of nodes in which various sensors are fabricated on the nodes to monitor various factors of the given task. These nodes will form a network by connecting the one to other for the effective communication between the nodes, and sends the whole information to the base station (BS). As the nodes which we use for the WSN are of low cost and are battery operated. The main drawback is replacement of the battery in the WSN. The main goal is to conserve the energy consumption in WSN and also to balance the load on WSN. For this many protocols are designed like LEACH, PEGASIS, PEDAP, etc. in those balancing the load and time delayed. some drawbacks are there. So we proposed a protocol so called “Tree Based Energy Balancing routing Protocol by Self Organizing” (TEBRSO), in which instead of routing tables a routing tree will be used for routing from nodes to base station (BS), which chooses one root/control node for the broadcasting messages to the selected sensor nodes. By this protocol we can save the energy consumption in WSN and can extend the life time of it. The performance of this protocol is better when we compare with other energy saving protocols.

QoS Aware Multi-hop Multi-path Routing Approach in Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 43-52
Author(s):  
Omkar Singh ◽  
Vinay Rishiwal
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Life Time ◽  
Base Station ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
End To End

Background & Objective: Wireless Sensor Network (WSN) consist of huge number of tiny senor nodes. WSN collects environmental data and sends to the base station through multi-hop wireless communication. QoS is the salient aspect in wireless sensor networks that satisfies end-to-end QoS requirement on different parameters such as energy, network lifetime, packets delivery ratio and delay. Among them Energy consumption is the most important and challenging factor in WSN, since the senor nodes are made by battery reserved that tends towards life time of sensor networks. Methods: In this work an Improve-Energy Aware Multi-hop Multi-path Hierarchy (I-EAMMH) QoS based routing approach has been proposed and evaluated that reduces energy consumption and delivers data packets within time by selecting optimum cost path among discovered routes which extends network life time. Results and Conclusion: Simulation has been done in MATLAB on varying number of rounds 400- 2000 to checked the performance of proposed approach. I-EAMMH is compared with existing routing protocols namely EAMMH and LEACH and performs better in terms of end-to-end-delay, packet delivery ratio, as well as reduces the energy consumption 13%-19% and prolongs network lifetime 9%- 14%.

scholarly journals Calculating the Number of Cluster Heads Based on the Rate-Distortion Function in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Mingxin Yang ◽  
Jingsha He ◽  
Yuqiang Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Rate Distortion ◽  
Distortion Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Cluster Heads

Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs). Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

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