scholarly journals Energy Efficiency in Wireless Sensor Network using Randomized Switching for Maximizing Lifetime

2019 ◽  
Vol 8 (6) ◽  
pp. 1058-1061
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Threshold Energy ◽  
Life Time ◽  
Distributed Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Switching Algorithm

Wireless Sensor Network is distributed networks of sensors which have the ability to sense, process and communicate. Sensor nodes are also responsible for collection of data. Due to the limited battery power of sensor node energy consumption is an essential issue. To reduce the energy consumption balancing of node load is one of the major task. In this paper, we have used switching algorithm to switch the nodes to balance the node load which further increases the life time of each node by finding the shortest path to destination from the source node based on the threshold energy. Further we applied base localization algorithm to check the lifetime of each node.

WSN Management Self-Silence Design and Data Analysis for Neural Network Based Infrastructure

2020 ◽  
pp. 1440-1458
Author(s):  
Nilayam Kumar Kamila ◽  
Sunil Dhal
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Conservation ◽  
Sensor Network ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Infrastructure ◽  
Network Life Time

In recent Wireless Sensor Network environment, battery energy conservation is one of the most important focus of research. The non-maintainable wireless sensor nodes need modern innovative ideas to save energy in order to extend the network life time. Different strategy in wireless sensor routing mechanism has been implemented to establish the energy conservation phenomenon. In earlier days, the nodes are dissipating maximum energy to communicate with each other(flooding) to establish the route to destination. In the next evolution of this research area, a clustering mechanism introduced which confirms the energy saving over the flooding mechanism. Neural Network is an advanced approach for self-clustering mechanism and when applied on wireless sensor network infrastructure, it reduces the energy consumption required for clustering. Neural network is a powerful concept with complex algorithms and capable to provide clustering solutions based on the wireless sensor network nodes properties. With the implementation of Neural Network on Wireless Sensor Network resolves the issues of high energy consumption required for network clustering. The authors propose a self-silence wireless sensor network model where sensor nodes change the sensing and transmitting mechanism by making self-silent in order to conserve the energy. This concept is simulated in neural network based wireless sensor network infrastructure of routing methodology and the authors observe that it extends the network life time. The mathematical analysis and simulation study shows the improved performance over the existing related neural network based wireless sensor routing protocols. Furthermore, the performance & related model parameters data set analysis provides the respective dependent relation information.

WSN Management Self-Silence Design and Data Analysis for Neural Network Based Infrastructure

2017 ◽  
Vol 4 (4) ◽  
pp. 82-100 ◽  
Author(s):  
Nilayam Kumar Kamila ◽  
Sunil Dhal
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Conservation ◽  
Sensor Network ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Infrastructure ◽  
Network Life Time

In recent Wireless Sensor Network environment, battery energy conservation is one of the most important focus of research. The non-maintainable wireless sensor nodes need modern innovative ideas to save energy in order to extend the network life time. Different strategy in wireless sensor routing mechanism has been implemented to establish the energy conservation phenomenon. In earlier days, the nodes are dissipating maximum energy to communicate with each other(flooding) to establish the route to destination. In the next evolution of this research area, a clustering mechanism introduced which confirms the energy saving over the flooding mechanism. Neural Network is an advanced approach for self-clustering mechanism and when applied on wireless sensor network infrastructure, it reduces the energy consumption required for clustering. Neural network is a powerful concept with complex algorithms and capable to provide clustering solutions based on the wireless sensor network nodes properties. With the implementation of Neural Network on Wireless Sensor Network resolves the issues of high energy consumption required for network clustering. The authors propose a self-silence wireless sensor network model where sensor nodes change the sensing and transmitting mechanism by making self-silent in order to conserve the energy. This concept is simulated in neural network based wireless sensor network infrastructure of routing methodology and the authors observe that it extends the network life time. The mathematical analysis and simulation study shows the improved performance over the existing related neural network based wireless sensor routing protocols. Furthermore, the performance & related model parameters data set analysis provides the respective dependent relation information.

scholarly journals Routing Algorithm using Fuzzy Logic Based Clustering with Mobile Sink for Wireless Sensor Network

2019 ◽  
Vol 8 (4) ◽  
pp. 4000-4005
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Life Time ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Degree

Minimization of the energy consumption in Wireless Sensor Network (WSN) is one of the most important area which has been explored by researchers through different methods. The use of non-stationary mobile sink has undoubtedly decreased the energy consumption within the sensor nodes and hence the life time of the system. Applying the Fuzzy Logic could effectively optimize the selection of Cluster Head. In this paper, Fuzzy Logic has been implemented for Cluster Head selection along with a mobile sink. The energy remaining in the sensor node, distance between the sink and the node, and the node degree are considered as the fuzzy inference variables. The life time of the node has been compared with the LEACH and Fuzzy logic based Clustering Combined with Mobile Sink (FCCMS) with mobile sink.

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.

Energy-Efficient Technique for Monitoring of Agricultural Areas with Terrestrial Wireless Sensor Networks

2019 ◽  
Vol 29 (09) ◽  
pp. 2050141 ◽  
Author(s):  
Muhammed Enes Bayrakdar
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Fading Channels ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Efficient Manner

In this paper, a monitoring technique based on the wireless sensor network is investigated. The sensor nodes used for monitoring are developed in a simulation environment. Accordingly, the structure and workflow of wireless sensor network nodes are designed. Time-division multiple access (TDMA) protocol has been chosen as the medium access technique to ensure that the designed technique operates in an energy-efficient manner and packet collisions are not experienced. Fading channels, i.e., no interference, Ricean and Rayleigh, are taken into consideration. Energy consumption is decreased with the help of ad-hoc communication of sensor nodes. Throughput performance for different wireless fading channels and energy consumption are evaluated. The simulation results show that the sensor network can quickly collect medium information and transmit data to the processing center in real time. Besides, the proposed technique suggests the usefulness of wireless sensor networks in the terrestrial areas.

scholarly journals A Localization Algorithm of Wireless Sensor Network Based on Statistical Uncorrelated Vector

2017 ◽  
Vol 13 (07) ◽  
pp. 57
Author(s):  
Min Wang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Inner Product ◽  
Localization Algorithm ◽  
Product Matrix ◽  
Ranging Error ◽  
Location Algorithm ◽  
The Impact

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-ansi-language: EN-US; mso-fareast-font-family: 宋体; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">For exploring wireless sensor network - a self-organized network, a new node location algorithm based on statistical uncorrelated vector (SUV) model, namely SUV location algorithm, is proposed. The algorithm, by translating the node coordinate, simplifies the solution to double center coordinate matrix, and gets the coordinate inner product matrix; then it uses statistical uncorrelated vectors to reconstruct the coordinates of the inner product matrix and remove the correlation of inner matrix of coordinates caused by the ranging error, so as to reduce the impact of ranging error on subsequent positioning accuracy. The experimental results show that the proposed algorithm does not consider the network traffic, bust still has good performance in localization. At last, it is concluded that reducing the amount of communication of sensor nodes is beneficial to prolong the service life of the sensor nodes, thus increasing the lifetime of the whole network.</span>

Design and Research of Low-Energy Consumption Sensor Nodes in a Smart-Scene System

2013 ◽  
Vol 705 ◽  
pp. 352-358
Author(s):  
Chun Xiao Fan ◽  
Ran Li ◽  
Jun Wei Zou ◽  
Ye Qiao Wang
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Management ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Dynamic Power Management ◽  
Depth Analysis ◽  
Low Energy Consumption ◽  
Reduce Energy Consumption

This paper introduces an application of wireless sensor network based on the ZigBee -- the Smart-Scene system. In-depth analysis of factors of invalid power consumption, a functional separated sink node is designed and a DPM (Dynamic Power Management) schema of dynamic node based on event-driven is proposed. The schema is used in Smart-Scene system and the experimental results indicate it is high feasibility and reduce energy consumption. This method will become an effective solution for wireless sensor network.

scholarly journals Wireless Sensor Network Localization Based On A Mobile Beacon And Tsvm

2014 ◽  
Vol 14 (5) ◽  
pp. 98-107 ◽  
Author(s):  
Jiang Xu ◽  
Huanyan Qian ◽  
Huan Dai ◽  
Jianxin Zhu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Support Vector ◽  
Localization Algorithm ◽  
Sensor Network Localization ◽  
Network Localization ◽  
Gps Devices ◽  
Mobile Beacon

Abstract In this paper a new wireless sensor network localization algorithm, based on a mobile beacon and TSVM (Transductive Support Vector Machines) is proposed, which is referred to as MTSVM. The new algorithm takes advantage of a mobile beacon to generate virtual beacon nodes and then utilizes the beacon vector produced by the communication between the nodes to transform the problem of localization into one of classification. TSVM helps to minimize the error of classification of unknown fixed nodes (unlabeled samples). An auxiliary mobile beacon is designed to save the large volumes of expensive sensor nodes with GPS devices. As shown by the simulation test, the algorithm achieves good localization performance.

scholarly journals A Novel Clustering Approach in Wireless Sensor Network Using Genetic Algorithm and Fuzzy Logic

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Fatemehzahra Gholami Tirkolaei ◽  
Faramarz E. Seraji
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Main Challenge ◽  
Clustering Approach ◽  
Reduce Energy Consumption ◽  
Reduction Of Energy Consumption

<p>Wireless sensor network consists of hundred or thousand sensor nodes that are connected together and work simultaneously to perform some special tasks. The restricted energy of sensor nodes is the main challenge in wireless sensor network as node energy depletion causes node death. Therefore, some techniques should be exerted to reduce energy consumption in these networks. One of the techniques to reduce energy consumptions most effectively is the use of clustering in wireless sensor networks.</p><p>There are various methods for clustering process, among which LEACH is the most common and popular one. In this method, clusters are formed in a probabilistic manner. Among clustering strategies, applying evolutional algorithm and fuzzy logic simultaneously are rarely taken into account. The main attention of previous works was energy consumption and less attention was paid to delay.</p><p>In the present proposed method, clusters are constructed by an evolutional algorithm and a fuzzy system such that in addition to a reduction of energy consumption, considerable reduction of delay is also obtained. The simulation results clearly reveal the superiority of the proposed method over other reported approaches.</p>

scholarly journals Automatic Remote Farm Irrigation System with WSN and Weather Forecasting

2022 ◽  
Vol 2161 (1) ◽  
pp. 012075
Author(s):  
Aditya Sai Kilaru ◽  
Prem Madishetty ◽  
Harsha Vardhan Naidu Yamala ◽  
C V Giriraja
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Weather Forecasting ◽  
Irrigation System ◽  
Weather Prediction ◽  
Cost Effective ◽  
Reliable Data ◽  
Sensor Nodes ◽  
Wireless Sensor

Abstract The paper showcases the system used for automating agriculture using wireless sensor network (WSN) and weather prediction. WSN, is more efficient than IoT as it avoids connecting all the sensor nodes directly to Internet, thus reducing the traffic over Internet and energy consumption of the sensor network. The system consists of a clustered tree topology to increase the range of operation, connectivity and easily connect new nodes dynamically. The sensor nodes being the leaves, local gateways being the branches and the global gateway being the root node. The system is implemented using cost effective micro-controllers, robust communication modules and reliable data showcasing platforms. Our implementation uses weather prediction to minimize the water needed for irrigation. Thereby minimizing cost and increasing efficient usage of resources.

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