Energy Efficient Data Gathering Technique Based on Optimal Mobile Sink Node Selection for Improved Network Life Time in Wireless Sensor Network (WSN)

Ashween, R; Ramakrishnan, B.; Joe, M. Milton

doi:10.1007/s11277-020-07309-y

Cited by 18 publications

(15 citation statements)

References 39 publications

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“…It frequently regarded players' approaches and advantages and their methodologies. Gaming theory is increasingly employed in WSNs, with applications primarily in power generation, authentication protocols, transmission power, data collecting, and other areas [13][14][15][16][17]. The applicability of behavioral economics to WSN energy efficiency has produced very impressive outcomes in recent years.…”

Section: Related Workmentioning

confidence: 99%

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Energy Efficient Networks Using Ant Colony Optimization with Game Theory Clustering

Gunigari¹,

Chitra²

2023

Intelligent Automation &Amp; Soft Computing

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Real-time applications based on Wireless Sensor Network (WSN) technologies quickly lead to the growth of an intelligent environment. Sensor nodes play an essential role in distributing information from networking and its transfer to the sinks. The ability of dynamical technologies and related techniques to be aided by data collection and analysis across the Internet of Things (IoT) network is widely recognized. Sensor nodes are low-power devices with low power devices, storage, and quantitative processing capabilities. The existing system uses the Artificial Immune System-Particle Swarm Optimization method to minimize the energy and improve the network's lifespan. In the proposed system, a hybrid Energy Efficient and Reliable Ant Colony Optimization (ACO) based on the Routing protocol (E-RARP) and game theory-based energy-efficient clustering algorithm (GEC) were used. E-RARP is a new Energy Efficient, and Reliable ACO-based Routing Protocol for Wireless Sensor Networks. The suggested protocol provides communications dependability and high-quality channels of communication to improve energy. For wireless sensor networks, a game theory-based energy-efficient clustering technique (GEC) is used, in which each sensor node is treated as a player on the team. The sensor node can choose beneficial methods for itself, determined by the length of idle playback time in the active phase, and then decide whether or not to rest. The proposed E-RARP-GEC improves the network's lifetime and data transmission; it also takes a minimum amount of energy compared with the existing algorithms.

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Section: Related Workmentioning

confidence: 99%

“…Numerous researchers and academics have undertaken numerous studies to optimize overall network energy consumption [6][7][8][9][10]. Following thorough reviews of relevant literature, it was discovered that research had been undertaken on the power usage of IoT devices during the inactive monitoring period.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Networks Using Ant Colony Optimization with Game Theory Clustering

Gunigari¹,

Chitra²

2023

Intelligent Automation &Amp; Soft Computing

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“…When there is no energy harvesting, the sensor node enters sleep mode to prolong its lifetime. In [10], the main purpose of the research was to design an energy embedded routing protocol based on an optimal update of the mobile sink. Furthermore, the mobile sink node is optimized to improve the network lifetime.…”

Section: Related Workmentioning

confidence: 99%

“…To ensure the continuous work of WSNs, reducing the energy consumption of sensor nodes is the most effective way to prolong the lifetime of a sensor network [6]. Many experts and scholars have conducted several studies to optimize the energy consumption of sensor nodes to a certain extent [7][8][9][10][11]. After an extensive literature review, it was found that there has been little research on the energy consumption of sensor nodes in the idle listening stage.…”

Section: Introductionmentioning

confidence: 99%

Game Theory-Based Energy-Efficient Clustering Algorithm for Wireless Sensor Networks

Xiao

Huang

Gan

et al. 2022

Sensors

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Energy efficiency is one of the critical challenges in wireless sensor networks (WSNs). WSNs collect and transmit data through sensor nodes. However, the energy carried by the sensor nodes is limited. The sensor nodes need to save energy as much as possible to prolong the network lifetime. This paper proposes a game theory-based energy-efficient clustering algorithm (GEC) for wireless sensor networks, where each sensor node is regarded as a player in the game. According to the length of idle listening time in the active state, the sensor node can adopt favorable strategies for itself, and then decide whether to sleep or not. In order to avoid the selfish behavior of sensor nodes, a penalty mechanism is introduced to force the sensor nodes to adopt cooperative strategies in future operations. The simulation results show that the use of game theory can effectively save the energy consumption of the sensor network and increase the amount of network data transmission, so as to achieve the purpose of prolonging the network lifetime.

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“…In [20], the author present a efficient approach towards privacy preservation is presented by considering different parameters of mobile node in secure routing. In [21], proposed an energy-aware QoS-guaranteed workflow management mechanism.…”

Section: Related Workmentioning

confidence: 99%

Mobility Aware Displacement Approximation Technique Based LSS and Privacy Preservation for Effective Data Routing in WSN with IoT Devices

Rajasekar¹,

Palanisamy²,

Saranya³

2021

Preprint

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The Location based Service Selection (LSS) in WSN has been well studied. Towards effective LSS, an efficient Mobility Aware Displacement Approximation (MADA-LSS) based approach is presented in this article. The model monitors the mobility of mobile device and predict the possible location at different future time stamp. According to the future time stamp, the list of service locations are identified at different possible locations. According to the possible locations and service set, the method discover set of routes to reach each of the service points. For each of the route, the method estimates Data Arrival Rate (DAR), Data Claim Rate (DCR) and Data Rate Support Measure (DRSM) for both Access Point as well as route identified. Also, the method ranks the service points according to DRSM value and estimates the Trusted Handover Measure (THM) for the routes according to IoT (Internet of Things) devices of any route. By considering both THM and DSRM values an optimal service point as well as route has been selected to perform data transmission. Also, the privacy preservation is performed by using the same set of displacement approximation scheme which selects optimal encryption based on mobility parameters and time complexity and security of different encryption schemes. The proposed method improves the performance of LSS and secure routing.

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Energy Efficient Data Gathering Technique Based on Optimal Mobile Sink Node Selection for Improved Network Life Time in Wireless Sensor Network (WSN)

Cited by 18 publications

References 39 publications

Energy Efficient Networks Using Ant Colony Optimization with Game Theory Clustering

Energy Efficient Networks Using Ant Colony Optimization with Game Theory Clustering

Game Theory-Based Energy-Efficient Clustering Algorithm for Wireless Sensor Networks

Mobility Aware Displacement Approximation Technique Based LSS and Privacy Preservation for Effective Data Routing in WSN with IoT Devices

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