scholarly journals An Unequal Cluster-based Routing Protocol Based on Data Controlling for Wireless Sensor Network

2016 ◽  
Vol 6 (5) ◽  
pp. 2403
Author(s):  
Slaheddine Chelbi ◽  
Majed Abdouli ◽  
Mourad Kaddes ◽  
Claude Duvallet ◽  
Rafik Bouaziz
Keyword(s):  
Energy Consumption ◽  
Communication Networks ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensitive Data ◽  
Link Cost ◽  
Data Controller ◽  
Routing Tree ◽  
Multiple Metrics

<p>Wireless Sensor Networks (WSN) differ from traditional wireless communication networks in several characteristics. One of these characteristics is power awarness, due to the fact that the batteries of sensor nodes have a restricted lifetime and are difficult to be replaced. Therefore, all protocols must be designed to minimize energy consumption and preserve the longevity of the network. In this paper, we propose (i) to fairly balance the load among nodes. For this, we generate an unequal clusters size where the cluster heads (CH) election is based on energy availability, (ii) to reduce the energy consumption due to the transmission by using multiple metrics in the CH jointure process and taking into account the link cost, residual energy and number of cluster members to construct the routing tree and (iii) to minimize the number of transmissions by avoiding the unnecessary updates using sensitive data controller. Simulation results show that our Advanced Energy-Efficient Unequal Clustering (AEEUC) mechanism improves the fairness energy consumption among all sensor nodes and achieves an obvious improvement on the network lifetime.</p>

An Unequal Cluster-based Routing Protocol Based on Data Controlling for Wireless Sensor Network

2016 ◽  
Vol 6 (5) ◽  
pp. 2403
Author(s):  
Slaheddine Chelbi ◽  
Majed Abdouli ◽  
Mourad Kaddes ◽  
Claude Duvallet ◽  
Rafik Bouaziz
Keyword(s):  
Energy Consumption ◽  
Communication Networks ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensitive Data ◽  
Link Cost ◽  
Data Controller ◽  
Routing Tree ◽  
Multiple Metrics

<p>Wireless Sensor Networks (WSN) differ from traditional wireless communication networks in several characteristics. One of these characteristics is power awarness, due to the fact that the batteries of sensor nodes have a restricted lifetime and are difficult to be replaced. Therefore, all protocols must be designed to minimize energy consumption and preserve the longevity of the network. In this paper, we propose (i) to fairly balance the load among nodes. For this, we generate an unequal clusters size where the cluster heads (CH) election is based on energy availability, (ii) to reduce the energy consumption due to the transmission by using multiple metrics in the CH jointure process and taking into account the link cost, residual energy and number of cluster members to construct the routing tree and (iii) to minimize the number of transmissions by avoiding the unnecessary updates using sensitive data controller. Simulation results show that our Advanced Energy-Efficient Unequal Clustering (AEEUC) mechanism improves the fairness energy consumption among all sensor nodes and achieves an obvious improvement on the network lifetime.</p>

scholarly journals An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

2021 ◽  
Author(s):  
Meriem MEDDAH ◽  
Rim HADDAD ◽  
Tahar EZZEDDINE
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Mobile Data ◽  
Data Collector ◽  
Mobile Data Collector

Abstract Mobile Data Collector device (MDC) is adopted to reduce the energy consumption in Wireless Sensor Networks. This device travels the network in order to gather the collected data from sensor nodes. This paper presents a new Tree Clustering algorithm with Mobile Data Collector in Wireless Sensor Networks, which establishes the shortest travelling path passing throw a subset of Cluster Heads (CH). To select CHs, we adopt a competitive scheme, and the best sensor nodes are elected according to the number of packets forwarded between sensor nodes, the number of hops to the tree’s root, the residual energy, and the distance between the node and the closest CH. In simulation results, we adopt the balanced and unbalanced topologies and prove the efficiently of our proposed algorithm considering the network lifetime, the fairness index and the energy consumption in comparison with the existing mobile data collection algorithms.

scholarly journals Data Clustering Method in Wireless Sensor Networks Based on Residual Energy Perception

2018 ◽  
Vol 14 (06) ◽  
pp. 85 ◽  
Author(s):  
Xudong Yang
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Data Gathering ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Forwarding ◽  
Cluster Data ◽  
Head Node

<p class="0abstract"><span lang="EN-US">To prolong the survival time of wireless sensor network, an iterative scheme was proposed. First of all, spectrum clustering algorithm iteratively segmented the network into clusters, and cluster head nodes in each sub cluster were determined depending on the size of residual energy of sensor nodes. Then, a data forwarding balance tree was constructed in each sub cluster. Data forwarding path of each non-cluster head node was defined, and the moving path of a mobile data collector was determined, which used the residual energy as the basis for the network optimization. Finally, this scheme was simulated, and two traditional data gathering algorithms were compared. The results showed that the algorithm designed in this experiment could effectively balance energy consumption among all WSN nodes and had great performance improvement compared with the traditional data collection algorithm. To sum up, this algorithm can significantly reduce the energy consumption of the network and improve the lifetime of the network. </span></p>

scholarly journals An Equilibrium Strategy-Based Routing Optimization Algorithm for Wireless Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3477 ◽  
Author(s):  
Liangrui Tang ◽  
Zhilin Lu ◽  
Jinqi Cai ◽  
Jiangyu Yan
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Algorithm ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Equilibrium Strategy ◽  
Term Operation ◽  
Link Cost ◽  
Transmission Energy Consumption

In energy-constrained wireless sensor networks (WSNs), the design of an energy-efficient smart strategy is a key to extend the network lifetime, but the unbalance of energy consumption and node load severely restrict the long-term operation of the network. To address these issues, a novel routing algorithm which considers both energy saving and load balancing is proposed in this paper. First of all, the transmission energy consumption, node residual energy and path hops are considered to create the link cost, and then a minimum routing graph is generated based on the link cost. Finally, in order to ensure the balance of traffic and residual energy of each node in the network, an “edge-cutting” strategy is proposed to optimize the minimum routing graph and turn it into a minimum routing tree. The simulation results show that, the proposed algorithm not only can balance the network load and prolong the lifetime of network, but meet the needs of delay and packet loss rate.

scholarly journals Tree-Based Multihop Routing Method for Energy Efficiency of Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jin Yong ◽  
Zhou Lin ◽  
Wei Qian ◽  
Bai Ke ◽  
Wang Chen ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Resources ◽  
Multihop Routing

In wireless sensor networks (WSNs), due to the limited energy of sensor nodes, how to design efficient hierarchical routing algorithms to balance network resources and extend network life is an important problem to be solved. Aiming at the problems such as random selection of cluster head, redundancy of working node, and construction of cluster head transmission path, which affect network energy consumption, this paper proposes a multihop routing algorithm based on path tree (MHRA-PT) to optimize the network energy. Firstly, some nodes are those close to the base station and have large remaining energy which are selected to construct a cluster head set. Then, after clustering, each cluster is divided into different regions, and in each region, nodes with residual energy greater than the average residual energy of the cluster are selected as a working node. Finally, the cluster heads are sorted according to their distance from base station, and the next hop node is selected for each cluster head in turn until a path tree rooted at base station is formed completely, leading to data transmission from working node to base station. Simulation results show that the proposed algorithm can effectively reduce network energy consumption, balance network resources, and prolong network life cycle.

scholarly journals HFLBSC: Heuristic and Fuzzy based Load Balanced, Scalable Clustering Algorithm for Wireless Sensor Network

2021 ◽  
Author(s):  
Priti Maratha ◽  
Kapil Gupta
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Power Transmission ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Scalable Clustering ◽  
Main Challenge ◽  
Union Curve ◽  
Load Balanced

Abstract In spite of the severe limitations on the resources of the sensor nodes such as memory, computational power, transmission range and battery, the application areas of Wireless Sensor Networks (WSNs) are increasing day by day. The main challenge in WSNs is energy consumption. It becomes significant when a large number of nodes are deployed. Although clustering is one of the solutions to cater to this problem, but it suffers from severe energy consumption due to the non-uniform selection of CHs and frequent re-clustering. In this paper, we propose a heuristic and fuzzy based load balanced, scalable clustering algorithm for WSNs called HFLBSC. In this algorithm, we have segregated the network into a layered structure using the area under intersection over union curve. We have selected the CHs by considering residual energy and distance threshold. We have stalled the frequent re-clustering by utilizing the decision made with the help of fuzzy logic. Our proposed scheme is capable enough to elongate the network lifetime. Statistical analysis and simulation results confirm the superiority of proposed work in comparison to its competitor protocol.

scholarly journals An Adaptive Hybrid Routing Scheme For Energy Management In Wireless Sensor Networks

2021 ◽  
Author(s):  
Raviteja Kocherla ◽  
Chandra sekhar M ◽  
Ramesh Vatambeti
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Life Time ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Grey Wolf ◽  
Hybrid Routing ◽  
Huge Data ◽  
Ant Lion

Abstract In Wireless Sensor Network (WSN) the life time of nodes and energy management are important issues, because the nodes in WSN required more energy when it is used in different applications. On the other hand, unstable energy consumption among intermediate nodes tends to huge data loss. To address this problem the present research introduced a novel Hybrid Gossip Grey Wolf Ant lion (HGGW-AL) protocol to afford an efficient and better transmission channel. Here, the fitness of grey wolf and ant lion helps to categorize the energy drained node and also, to predict the malicious activities. Furthermore, the novel Rest Awake (RA) is initialized to process the clustering strategy to maintain the residual energy in WSN. Moreover, it enhances the energy level of sensor nodes by increasing its lifetime. Finally, the efficiency of the proposed strategy is compared with the existing works and achieved better performance by reducing the energy consumption of each sensor node.

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

scholarly journals WSN Routing Protocol Using a Multiobjective Greedy Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Seyed Reza Nabavi ◽  
Nafiseh Osati Eraghi ◽  
Javad Akbari Torkestani
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Communication Networks ◽  
Optimal Path ◽  
Base Station ◽  
Packet Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Greedy Approach

Due to the widespread use of communication networks and the ease of transmitting and gathering information through these networks, wireless sensor networks (WSN) have become increasingly popular. Usability in any environment without the need for environmental monitoring and engineering of these networks has led to their increasing usage in various fields. Routing information from the sensor node to sink, so that node energy is consumed uniformly and network life is not reduced, is one of the most important challenges in wireless sensor networks. Most wireless networks have no infrastructure, and embedded sensor nodes have limited power. Thus, the early termination of the wireless node’s energy based on the transmission of messages over the network can disrupt the entire network process. In this paper, the object is designed to find the optimal path in WSN based on the multiobjective greedy approach to the near optimal path. The proposed model is presented in this method to transfer sensed data of the sensor network to the base station for the desired applications. In this method, the sensor nodes are identified as adjacent nodes based on their distance. The energy of all nodes initially is approximately equal, which decreases with the transfer of information between the nodes. In this way, when a node senses a message, it checks several factors for transmitting information to its adjacent nodes and selects the node with the largest amount of factors as the next hop. The simulation results show that the energy consumption in the network grids is almost symmetrically presented, and the network lifetime is reduced with a gentle slope that provides optimum energy consumption in the networks. Also, the packet transmission delay in the network reaches 450 milliseconds for the transmission of information between 15 nodes and 650 connections. Besides, network throughput increases by approximately 97%. It also shows better performance compared to other previous methods in terms of evaluation criteria.

scholarly journals Energy-aware determination of compression for low latency in solar-powered wireless sensor networks

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769416 ◽  
Author(s):  
Min Jae Kang ◽  
Semi Jeong ◽  
Ikjune Yoon ◽  
Dong Kun Noh
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Delay Time ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Transfer Data ◽  
Surplus Energy ◽  
Solar Powered

There have been many studies performed about increasing network lifetime in wireless sensor networks that involve reducing data size, since the data transmission process takes up a large part of energy consumption. However, reducing data size results in increased delay time due to not only the compression computation time but also the waiting time to gather a sufficient amount of data for compression. Meanwhile, in solar-powered wireless sensor networks, the harvested energy may be surplus to the basic operations of sensor nodes. In this study, such surplus energy is utilized to reduce the delay time between nodes. Nodes with residual energy less than a certain threshold transfer data with compression in order to reduce energy consumption, and nodes with residual energy over the threshold (which means there is surplus energy) transfer data without compression to reduce the delay time between nodes by using the surplus energy. Simulation-based performance verifications show that the technique proposed in this study exhibits optimal performance in terms of both energy and delay times compared with traditional methods.

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