Connectivity-Guaranteed Hybrid Topology Management Scheme for Improving the Operational Lifetime of 3-Dimensional Wireless Sensor Networks

2010 ◽  
Vol 6 (1) ◽  
pp. 547368 ◽  
Author(s):  
A. Jawahar ◽  
S. Radha ◽  
S. Vadivelan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Network ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Topology Management ◽  
3 Dimensional ◽  
Hybrid Topology ◽  
Management Scheme

The battery of limited energy operates wireless sensor nodes, it is important to increase the lifetime of the wireless sensor network. The aim of our work is to design a hybrid topology management scheme for improving the lifetime of the wireless sensor networks with guaranteed connectivity. The sensing range of the sensor node is smaller than the radio range and hence there is a large number of nodes within the coverage area of a node. Hence the network connectivity can be maintained with less number of nodes. By using this fact, we can save energy by switching off the transceiver, which consumes most of the energy. On the other hand, the sensor node spends most of the time in monitoring state and the transceiver is idle. In the idle state the transceiver consumes almost the same energy as in receiving state. Hence putting the transceiver in the sleep mode when it is idle can save the significant energy. We have designed a hybrid topology management scheme for 3-Dimensional sensor networks by making use of these facts. Our hybrid scheme improves the lifetime of the 3-Dimensional sensor network by a factor of 19.

Optimization of Clustering in Wireless Sensor Networks Using Genetic Algorithm

2020 ◽  
pp. 822-836
Author(s):  
Pritee Parwekar ◽  
Sireesha Rodda
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Network ◽  
Sensor Node ◽  
Fitness Function ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Communication Distance ◽  
Selection Of

The energy of a sensor node is a major factor for life of a network in wireless sensor network. The depletion of the sensor energy is dependent on the communication range from the sink. Clustering is mainly used to prolong the life of a network with energy consumption. This paper proposes optimization of clustering using genetic algorithm which will help to minimize the communication distance. The cluster overhead and the active and sleep mode of a sensor is also considered while calculating the fitness function to form the cluster. This approach helps to prolong the network life of sensor network. The proposed work is tested for different number of nodes and is helping to find the correct solution for the selection of cluster heads.

Optimization of Clustering in Wireless Sensor Networks Using Genetic Algorithm

2017 ◽  
Vol 8 (4) ◽  
pp. 84-98 ◽  
Author(s):  
Pritee Parwekar ◽  
Sireesha Rodda
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Network ◽  
Sensor Node ◽  
Fitness Function ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Communication Distance ◽  
Selection Of

The energy of a sensor node is a major factor for life of a network in wireless sensor network. The depletion of the sensor energy is dependent on the communication range from the sink. Clustering is mainly used to prolong the life of a network with energy consumption. This paper proposes optimization of clustering using genetic algorithm which will help to minimize the communication distance. The cluster overhead and the active and sleep mode of a sensor is also considered while calculating the fitness function to form the cluster. This approach helps to prolong the network life of sensor network. The proposed work is tested for different number of nodes and is helping to find the correct solution for the selection of cluster heads.

scholarly journals Performance of BAT Algorithm on Localization of Wireless Sensor Network

2013 ◽  
Vol 6 (3) ◽  
pp. 351-358 ◽  
Author(s):  
Sonia Goyal ◽  
Manjeet Singh Patterh
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Sensor Node ◽  
Geographical Location ◽  
Bat Algorithm ◽  
Wireless Sensor ◽  
Localization Problem ◽  
Large Numbers

Many applications of wireless sensor networks (WSN) require information about the geographical location of each sensor node. Devices that form WSN are expected to be remotely deployed in large numbers in a sensing field, and to self -organize to perform sensing and acting task. The goal of localization is to assign geographical coordinates to each device with unknown position in the deployment area. Recently, the popular strategy is to apply optimization algorithms to solve the localization problem. In this paper, the bat algorithm is implemented to estimate the sensor‟s position.

Key Management Scheme Using Time-Based Deployment for Wireless Sensor Networks

2010 ◽  
Vol 21 (3) ◽  
pp. 516-527 ◽  
Author(s):  
Ting YUAN ◽  
Jian-Qing MA ◽  
Yi-Ping ZHONG ◽  
Shi-Yong ZHANG
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Key Management ◽  
Wireless Sensor ◽  
Management Scheme ◽  
Key Management Scheme

A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Sensor Node ◽  
Large Scale ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Mobile Anchor ◽  
Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

scholarly journals A Data-Based Fault-Detection Model for Wireless Sensor Networks

2019 ◽  
Vol 11 (21) ◽  
pp. 6171 ◽  
Author(s):  
Jangsik Bae ◽  
Meonghun Lee ◽  
Changsun Shin
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Data Transmission ◽  
Sensor Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensors And Actuators ◽  
Detection Model ◽  
Management Platform

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime.

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