scholarly journals An Enhanced PSO-Based Clustering Energy Optimization Algorithm for Wireless Sensor Network

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
C. Vimalarani ◽  
R. Subramanian ◽  
S. N. Sivanandam
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Performance Metrics ◽  
Energy Optimization ◽  
Pso Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Target Area ◽  
Energy Conservation Measures

Wireless Sensor Network (WSN) is a network which formed with a maximum number of sensor nodes which are positioned in an application environment to monitor the physical entities in a target area, for example, temperature monitoring environment, water level, monitoring pressure, and health care, and various military applications. Mostly sensor nodes are equipped with self-supported battery power through which they can perform adequate operations and communication among neighboring nodes. Maximizing the lifetime of the Wireless Sensor networks, energy conservation measures are essential for improving the performance of WSNs. This paper proposes an Enhanced PSO-Based Clustering Energy Optimization (EPSO-CEO) algorithm for Wireless Sensor Network in which clustering and clustering head selection are done by using Particle Swarm Optimization (PSO) algorithm with respect to minimizing the power consumption in WSN. The performance metrics are evaluated and results are compared with competitive clustering algorithm to validate the reduction in energy consumption.

scholarly journals A Novel Secret Location Sharing Scheme for Wireless Sensor Network

2021 ◽  
Vol 19 (3) ◽  
Author(s):  
Monjul Saikia
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Node ◽  
Implementation Process ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Target Area ◽  
Location Sharing ◽  
Sharing Scheme

The wireless sensor network is a collection of sensor nodes that operate collectively to gather sensitive data from a target area. In the process of data collection the location of sensor nodes from where data is originated matters for taking any decision at the base station. Location i.e. the coordinates of a sensor node need to be shared among other nodes in many circumstances such as in key distribution phase, during routing of packets and many more. Secrecy of the location of every sensor node is important in any such cases. Therefore, there must be a location sharing scheme that facilitates the sharing of location among sensor nodes securely. In this paper, we have proposed a novel secure and robust mechanism for location sharing scheme using 2-threshold secret sharing scheme. The implementation process of the proposed model is shown here along with results and analysis.

scholarly journals Comparison of Residual Energy-Based Clustering Algorithms for Wireless Sensor Network

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Asis Kumar Tripathy ◽  
Suchismita Chinara
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Architecture ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness

Wireless sensor network swears an exceptional fine-grained interface between the virtual and physical worlds. The clustering algorithm is a kind of key technique used to reduce energy consumption. Many clustering, power management, and data dissemination protocols have been specifically designed for wireless sensor network (WSN) where energy awareness is an essential design issue. Each clustering algorithm is composed of three phases cluster head (CH) selection, the setup phase, and steady state phase. The hot point in these algorithms is the cluster head selection. The focus, however, has been given to the residual energy-based clustering protocols which might differ depending on the application and network architecture. In this paper, a survey of the state-of-the-art clustering techniques in WSNs has been compared to find the merits and demerits among themselves. It has been assumed that the sensor nodes are randomly distributed and are not mobile, the coordinates of the base station (BS) and the dimensions of the sensor field are known.

scholarly journals Investigation of Parameter Effects on Virtual-Spring-Force Algorithm for Wireless-Sensor-Network Applications

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3082
Author(s):  
Zhiyong Yu ◽  
Rongxin Tang ◽  
Kai Yuan ◽  
Hai Lin ◽  
Xin Qian ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Large Scale ◽  
Central Force ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Target Area ◽  
Node Deployment ◽  
Spring Force

Virtual-force algorithms (VFAs) have been widely studied for accurate node deployment in wireless-sensor-network (WSN) applications. Their main purpose is to achieve the maximum coverage area with the minimum number of sensor nodes in the target area. Recently, we reported a new VFA based on virtual spring force (VFA-SF) and discussed in detail the corresponding efficiency via statistical analysis. The optimized strategy by adding an external central force (VFA-SF-OPT) was presented, which effectively eliminates the coverage hole or twisted structure in the final network distribution. In this paper, the parameter effects on VFA-SF and the VFA-SF-OPT were further investigated: (1) Node velocity dramatically affects the convergence rate of the node-deployment process. (2) A suitable external central force improves equilibrium distance and reduces energy consumption. (3) The effects of VFA-SF and VFA-SF-OPT for different types of obstacles are discussed. Generally, by choosing suitable parameters, both VFA-SF and VFA-SF-OPT can effectively improve node deployment and energy consumption for the whole sensor network. The results give important insight in parameter selection and information fusion in the application of a large-scale WSN.

scholarly journals Data Flow in Wireless Sensor Network Protocol Stack by using Bellman-Ford Routing Algorithm

2017 ◽  
Vol 6 (1) ◽  
pp. 81-87
Author(s):  
Rakesh Kumar Saini ◽  
Ritika Ritika ◽  
Sandip Vijay
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Algorithm ◽  
Fire Detection ◽  
Transport Layer ◽  
Sensor Nodes ◽  
Network Protocol ◽  
Wireless Sensor ◽  
Target Area ◽  
Protocol Stack

Wireless sensor network consists various sensor nodes that are used to monitor any target area like forest fire detection by our army person and monitoring any industrial activity by industry manager. Wireless sensor networks have been deployed in several cities to monitor the concentration of dangerous gases for citizens. In wireless sensor network when sensor nodes communicate from each other then routing protocol are used for communication between protocol layers. Wireless sensor network protocol stack consist five layers such as Application layer, Transport layer, Network layer, MAC Layer, Physical layer. In this paper we study and analysis Bellman-Ford routing algorithm and check the flow of data between these protocol layers. For simulation purpose we are using Qualnet 5.0.2 simulator tool.

scholarly journals Energy Optimization for WSN in Ubiquitous Power Internet of Things

2019 ◽  
Vol 14 (4) ◽  
pp. 503-517 ◽  
Author(s):  
Wei Hu ◽  
Huanhao Li ◽  
Wenhui Yao ◽  
Yawei Hu
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Internet Of Things ◽  
Sensor Network ◽  
Routing Algorithm ◽  
Energy Optimization ◽  
Opportunistic Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Single Node

This paper attempts to solve the problems of uneven energy consumption and premature death of nodes in the traditional routing algorithm of rechargeable wireless sensor network in the ubiquitous power Internet of things. Under the application environment of the UPIoT, a multipath routing algorithm and an opportunistic routing algorithm were put forward to optimize the network energy and ensure the success of information transmission. Inspired by the electromagnetic propagation theory, the author constructed a charging model for a single node in the wireless sensor network (WSN). On this basis, the network energy optimization problem was transformed into the network lifecycle problem, considering the energy consumption of wireless sensor nodes. Meanwhile, the traffic of each link was computed through linear programming to guide the distribution of data traffic in the network. Finally, an energy optimization algorithm was proposed based on opportunistic routing, in a more realistic low power mode. The experimental results show that the two proposed algorithms achieved better energy efficiency, network lifecycle and network reliability than the shortest path routing (SPR) and the expected duty-cycled wakeups minimal routing (EDC). The research findings provide a reference for the data transmission of UPIoT nodes.

scholarly journals Unequal clustering in wireless sensor network: a review

2021 ◽  
Vol 22 (1) ◽  
pp. 419
Author(s):  
Khalid Waleed Al-ani ◽  
Fairuz Bin Abdullah ◽  
Salman Yossuf
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Energy Hole ◽  
Node Location ◽  
Energy Hole Problem

<p><span>In recent time, the applications' diversity of wireless sensor network (WSN) attracts many researchers. WSN comprises of many sensor nodes with limited battery power. Therefore, energy consumption should be controlled to the optimum. Clustering is an efficient solution for energy management in WSN, but clustering does not consider the sink node location. It will cause the energy hole problem in multi-hop routing. Energy hole problem was solved by unequal clustering. A review of various unequal clustering mechanisms is presented in this paper. The comparison between the various mechanisms was based on cluster head election process, cluster properties, simulation parameters and energy efficiency to highlight a more efficient and scalable unequal clustering algorithm for </span>WSN.</p>

scholarly journals TRACKING OF MOVING OBJECT IN WIRELESS SENSOR NETWORK

2015 ◽  
pp. 42-47
Author(s):  
D. CHARANYA ◽  
G. V. UMA
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Base Station ◽  
Moving Object ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Current Location

A Wireless Sensor Network is a collection of sensor nodes distributed into a network to monitor the environmental conditions and send the sensed data to the Base Station. Wireless Sensor Network is one of the rapidly developing area in which energy consumption is the most important aspect to be considered while tracking, monitoring, reporting and visualization of data. An Energy Efficient Prediction-based Clustering algorithm is proposed to track the moving object in wireless sensor network. This algorithm reduces the number of hops between transmitter and receiver nodes and also the number of transmitted packets. In this method, the sensor nodes are statically placed and clustered using LEACH-R algorithm. The Prediction based clustering algorithm is applied where few nodes are selected for tracking which uses the prediction mechanism to predict the next location of the moving object. The Current Location of the target is found using Trilateration algorithm. The Current Location or Predicted Location is sent to active Cluster Head from the leader node or the other node. Based on which node send the message to the Cluster Head, the Predicted or Current Location will be sent to the base station. In real time, the proposed work is applicable in traffic tracking and vehicle tracking. The experiment is carried out using Network Stimulator-2 environment. Simulation result shows that the proposed algorithm gives a better performance and reduces the energy consumption.

scholarly journals An Implementation of Grouping Nodes in Wireless Sensor Network Based on Distance by Using k-Means Clustering

2018 ◽  
Vol 12 (2) ◽  
pp. 97
Author(s):  
Rizqi Fauzil Azhar ◽  
Ahmad Zainudin ◽  
Prima Kristalina ◽  
Bagas Mardiasyah Prakoso ◽  
Niam Tamami
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Efficiency ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Cluster Head ◽  
Channel Modeling ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Observation Area

Wireless Sensor Network (WSN) is a network consisting of several sensor nodes that communicate with each other and work together to collect data from the surrounding environment. One of the WSN problems is the limited available power. Therefore, nodes on WSN need to communicate by using a cluster-based routing protocol. To solve this, the researchers propose a node grouping based on distance by using k-means clustering with a hardware implementation. Cluster formation and member node selection are performed based on the nearest device of the sensor node to the cluster head. The k-means algorithm utilizes Euclidean distance as the main grouping nodes parameter obtained from the conversion of the Received Signal Strength Indication (RSSI) into the distance estimation between nodes. RSSI as the parameter of nearest neighbor nodes uses lognormal shadowing channel modeling method that can be used to get the path loss exponent in an observation area. The estimated distance in the observation area has 27.9% error. The average time required for grouping is 58.54 s. Meanwhile, the average time used to retrieve coordinate data on each cluster to the database is 45.54 s. In the system, the most time-consuming process is the PAN ID change process with an average time of 14.20 s for each change of PAN ID. The grouping nodes in WSN using k-means clustering algorithm can improve the power efficiency by 6.5%.

scholarly journals Energy Map Generation in Wireless Sensor Network using Grey System Theory

2019 ◽  
Vol 8 (12) ◽  
pp. 3821-3826
Keyword(s):  
Wireless Sensor Network ◽  
Energy Level ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Residual Energy ◽  
Grey System Theory ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Status ◽  
Grey System

Wireless sensor nodes are deployed in hostile environment as applications of wireless sensor network. Battery is the source of energy of these sensor nodes. Replacing their batteries is not feasible due to their deployment in hostile area. In the proposed research, main objective is to extend the lifetime of network by predicting the residual energy of sensor nodes. For enhancing the lifetime of the wireless sensor network, it is necessary to keep track of residual energy level. Tracking residual energy status of sensor nodes is helpful in creating the energy map for network. In this paper, an approach to predict the residual energy level and to generate energy map for wireless sensor network is proposed. Proposed algorithm is used with clustering algorithm. Simulation results show that proposed algorithm reduces number of the messages transmitted which intern increases network lifetime.

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