A Simple Priority-Based Scheme for Delay-Sensitive Data Transmission Over Wireless Sensor Networks

Background: An information gathering is a typical and important task in agriculture monitoring and military surveillance. In these applications, minimization of energy consumption and maximization of network lifetime have prime importance for green computing. As wireless sensor networks comprise of a large number of sensors with limited battery power and deployed at remote geographical locations for monitoring physical events, therefore it is imperative to have minimum consumption of energy during network coverage. The WSNs help in accurate monitoring of remote environment by collecting data intelligently from the individual sensors. Objective: The paper is motivated from green computing aspect of wireless sensor network and an Energy-efficient Weight-based Coverage Enhancing protocol using Genetic Algorithm (WCEGA) is presented. The WCEGA is designed to achieve continuously monitoring of remote areas for a longer time with least power consumption. Method: The cluster-based algorithm consists two phases: cluster formation and data transmission. In cluster formation, selection of cluster heads and cluster members areas based on energy and coverage efficient parameters. The governing parameters are residual energy, overlapping degree, node density and neighbor’s degree. The data transmission between CHs and sink is based on well-known evolution search algorithm i.e. Genetic Algorithm. Conclusion: The results of WCEGA are compared with other established protocols and shows significant improvement of full coverage and lifetime approximately 40% and 45% respectively.

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Cluster‐based data transmission scheme in wireless sensor networks using black hole and ant colony algorithms

International Journal of Communication Systems ◽

10.1002/dac.4768 ◽

2021 ◽

Author(s):

Seyedsalar Sefati ◽

Mehrdad Abdi ◽

Ali Ghaffari

Keyword(s):

Wireless Sensor Networks ◽

Black Hole ◽

Sensor Networks ◽

Data Transmission ◽

Ant Colony ◽

Wireless Sensor ◽

Transmission Scheme ◽

Ant Colony Algorithms

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

Sustainability ◽

10.3390/su11216171 ◽

2019 ◽

Vol 11 (21) ◽

pp. 6171 ◽

Cited By ~ 2

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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