scholarly journals Enhancing Clustering in Wireless Sensor Networks with Energy Heterogeneity

2013 ◽  
pp. 259-273
Author(s):  
Femi A. Aderohunmu ◽  
Jeremiah D. Deng ◽  
Martin Purvis
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Research Question ◽  
Energy Levels ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Complex Functions

While wireless sensor networks (WSN) are increasingly equipped to handle more complex functions, in-network processing still requires the battery-powered sensors to judiciously use their constrained energy so as to prolong the elective network life time. There are a few protocols using sensor clusters to coordinate the energy consumption in a WSN, but how to deal with energy heterogeneity remains a research question. The authors propose a modified clustering algorithm with a three-tier energy setting, where energy consumption among sensor nodes is adaptive to their energy levels. A theoretical analysis shows that the proposed modifications result in an extended network stability period. Simulation has been conducted to evaluate the new clustering algorithm against some existing algorithms under different energy heterogeneity settings, and favourable results are obtained especially when the energy levels are significantly imbalanced.

scholarly journals Enhancing Clustering in Wireless Sensor Networks with Energy Heterogeneity

2011 ◽  
Vol 7 (4) ◽  
pp. 18-31 ◽  
Author(s):  
Femi A. Aderohunmu ◽  
Jeremiah D. Deng ◽  
Martin Purvis
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Research Question ◽  
Energy Levels ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Complex Functions

While wireless sensor networks (WSN) are increasingly equipped to handle more complex functions, in-network processing still requires the battery-powered sensors to judiciously use their constrained energy so as to prolong the elective network life time. There are a few protocols using sensor clusters to coordinate the energy consumption in a WSN, but how to deal with energy heterogeneity remains a research question. The authors propose a modified clustering algorithm with a three-tier energy setting, where energy consumption among sensor nodes is adaptive to their energy levels. A theoretical analysis shows that the proposed modifications result in an extended network stability period. Simulation has been conducted to evaluate the new clustering algorithm against some existing algorithms under different energy heterogeneity settings, and favourable results are obtained especially when the energy levels are significantly imbalanced.

Energy Efficient Image Compression and Transmission in WSN

2016 ◽  
pp. 67-78
Author(s):  
Wajeeha Aslam ◽  
Muazzam A. Khan ◽  
M. Usman Akram ◽  
Nazar Abbas Saqib ◽  
Seungmin Rho
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Image Compression ◽  
Sensor Network ◽  
Image Data ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life

Wireless sensor networks are greatly habituated in widespread applications but still yet step behind human intelligence and vision. The main reason is constraints of processing, energy consumptions and communication of image data over the sensor nodes. Wireless sensor network is a cooperative network of nodes called motes. Image compression and transmission over a wide ranged sensor network is an emerging challenge with respect to battery, life time constraints. It reduces communication latency and makes sensor network efficient with respect to energy consumption. In this paper we will have an analysis and comparative look on different image compression techniques in order to reduce computational load, memory requirements and enhance coding speed and image quality. Along with compression, different transmission methods will be discussed and analyzed with respect to energy consumption for better performance in wireless sensor networks.

A Cluster Algorithm for Wireless Sensor Networks Based on Energy Efficiency

2015 ◽  
Vol 785 ◽  
pp. 744-750
Author(s):  
Lei Gao ◽  
Qun Chen
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Selection Criterion ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Head Node

In order to solve the energy limited problem of sensor nodes in the wireless sensor networks (WSN), a fast clustering algorithm based on energy efficiency for wire1ess sensor networks is presented in this paper. In the system initialization phase, the deployment region is divided into several clusters rapidly. The energy consumption ratio and degree of the node are chosen as the selection criterion for the cluster head. Re-election of the cluster head node at this time became a local trigger behavior. Because of the range of the re-election is within the cluster, which greatly reduces the complexity and computational load to re-elect the cluster head node. Theoretical analysis indicates that the timing complexity of the clustering algorithm is O(1), which shows that the algorithm overhead is small and has nothing to do with the network size n. Simulation results show that clustering algorithm based on energy efficiency can provide better load balancing of cluster heads and less protocol overhead. Clustering algorithm based on energy efficiency can reduce energy consumption and prolong the network lifetime compared with LEACH protocol.

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.

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 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 AN ENHANCED CLUSTERING APPROACH FOR ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORKS

2018 ◽  
Vol 17 (1) ◽  
pp. 7111-7119
Author(s):  
Harpinderjeet Kaur Sekhon ◽  
Dr. Mohita
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Clustering Algorithm ◽  
Its Region ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
State Transitions ◽  
Energy Efficient Routing ◽  
Fuzzy Variables

Energy consumption is the core issue in wireless sensor networks (WSN). To generate a node energy model that can accurately reveal the energy consumption of sensor nodes is an extremely important part of protocol development, system design and performance evaluation in WSNs. In this paper, by studying component energy consumption in different node states and within state transitions, the authors present the energy models of the node core components, including processors, RF modules and sensors. One of the major issues in wireless sensor networks is developing a routing protocol which has a significant impact on the overall lifetime of the sensor network. The network area is divided into same sized small–small regions. Sensor nodes are randomly deployed in each predefined sub-area. Each region will have its region head (RH) and multiple member nodes. The member nodes in a specific region will send the data to the RH. RH within the region will be elected by distributed mechanism and will be based on fuzzy variables. It was found that the proposed algorithm gives a much improved network lifetime as compared to existing work. Based on our model, transmission tuning algorithm for cluster-based WSNs has been proposed to balance the load among cluster heads that fall in different regions. This algorithm is applied prior to a cluster algorithm to improve the performance of the clustering algorithm without affecting the performance of individual sensor nodes.

scholarly journals Performance Analysis of Data Compression Algorithms for Energy Efficient Wireless Sensor Networks

2019 ◽  
Vol 9 (1S) ◽  
pp. 404-408
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Compression ◽  
Energy Saving ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Piecewise Linear Approximation ◽  
Compression Algorithms

Wireless Sensor Networks (WSN), is an intensive area of research which is often used for monitoring, sensing and tracking various environmental conditions. It consists of a number of sensor nodes that are powered with fixed low powered batteries. These batteries cannot be changed often as most of the WSN will be in remote areas. Life time of WSN mainly depends on the energy consumed by the sensor nodes. In order to prolong the networks life time, the energy consumption has to be reduced. Different energy saving schemes has been proposed over the years. Data compression is one among the proposed schemes that can scale down the amount of data transferred between nodes and results in energy saving. In this paper, an attempt is made to analyze the performances of three different data compression algorithms viz. Light Weight Temporal Compression (LTC), Piecewise Linear Approximation with Minimum Number of Line Segments (PLAMLIS) and Univariate Least Absolute Selection and Shrinkage Operator (ULASSO). These algorithms are tested on standard univariate datasets and evaluated using assessment metrics like Mean Square Error (MSE), compression ratio and energy consumption. The results show that the ULASSO algorithm outperforms other algorithms in all three metrics and contributes more towards energy consumption

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.

scholarly journals CAF: Cluster Algorithm and A-Star with Fuzzy Approach for Lifetime Enhancement in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-17 ◽  
Author(s):  
Yali Yuan ◽  
Caihong Li ◽  
Yi Yang ◽  
Xiangliang Zhang ◽  
Lian Li
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Fuzzy Inference ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fuzzy Approach

Energy is a major factor in designing wireless sensor networks (WSNs). In particular, in the real world, battery energy is limited; thus the effective improvement of the energy becomes the key of the routing protocols. Besides, the sensor nodes are always deployed far away from the base station and the transmission energy consumption is index times increasing with the increase of distance as well. This paper proposes a new routing method for WSNs to extend the network lifetime using a combination of a clustering algorithm, a fuzzy approach, and an A-star method. The proposal is divided into two steps. Firstly, WSNs are separated into clusters using the Stable Election Protocol (SEP) method. Secondly, the combined methods of fuzzy inference and A-star algorithm are adopted, taking into account the factors such as the remaining power, the minimum hops, and the traffic numbers of nodes. Simulation results demonstrate that the proposed method has significant effectiveness in terms of balancing energy consumption as well as maximizing the network lifetime by comparing the performance of the A-star and fuzzy (AF) approach, cluster and fuzzy (CF)method, cluster and A-star (CA)method, A-star method, and SEP algorithm under the same routing criteria.

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