An efficient transceiver optimization based routing technique for wireless sensor network

Kakhandki, Arun L.; Hublikar, Shivaraj; Kumar, Priyatam

doi:10.1109/cesys.2016.7889828

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…for selective hop selection that minimizes energy consumption per bit and maximizes network lifetime [74] . The authors used the first node death criterion for network lifetime performance and assumed only node device power consumption for the optimization strategy.…”

Section: Kakhandki Et Al Evaluated a Dynamic Mac And Transceiver Opti...mentioning

confidence: 99%

On Wireless Sensor Network Models: A Cross-Layer Systematic Review

Ojeda

Méndez

Fajardo

et al. 2023

JSAN

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Wireless sensor networks (WSNs) have been adopted in many fields of application, such as industrial, civil, smart cities, health, and the surveillance domain, to name a few. Fateway and sensor nodes conform to WSN, and each node integrates processor, communication, sensor, and power supply modules, sending and receiving information of a covered area across a propagation medium. Given the increasing complexity of a WSN system, and in an effort to understand, comprehend and analyze an entire WSN, different metrics are used to characterize the performance of the network. To reduce the complexity of the WSN architecture, different approaches and techniques are implemented to capture (model) the properties and behavior of particular aspects of the system. Based on these WSN models, many research works propose solutions to the problem of abstracting and exporting network functionalities and capabilities to the final user. Modeling an entire WSN is a difficult task for researchers since they must consider all of the constraints that affect network metrics, devices and system administration, holistically, and the models developed in different research works are currently focused only on a specific network layer (physical, link, or transport layer), making the estimation of the WSN behavior a very difficult task. In this context, we present a systematic and comprehensive review focused on identifying the existing WSN models, classified into three main areas (node, network, and system-level) and their corresponding challenges. This review summarizes and analyzes the available literature, which allows for the general understanding of WSN modeling in a holistic view, using a proposed taxonomy and consolidating the research trends and open challenges in the area.

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Section: Kakhandki Et Al Evaluated a Dynamic Mac And Transceiver Opti...mentioning

confidence: 99%

On Wireless Sensor Network Models: A Cross-Layer Systematic Review

Ojeda

Méndez

Fajardo

et al. 2023

JSAN

View full text Add to dashboard Cite

show abstract

“…The crucial factor is to save the energy which in turn increases lifetime ratio. The Sensing points whose distance is lesser with respect to sink Sensing Point they have more energy consumption and leads to lowest lifetime ratio [19].…”

Section: Literaure Surveymentioning

confidence: 99%

An Energy Efficient and Lifetime Ratio Improvement Methods Based on Energy Balancing

L¹,

M²

2019

IJEAT

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WSN consist of set of Sensing points which are responsible for collecting the detected information and then send the packets towards control centre which is responsible for processing of data. The applications of WSN include environmental data analysis, defence data collection and information. The survey of algorithms is done for the improvement of lifetime ratio. Four different algorithms namely Random, Random-CGT, EGT-Random and GTEB algorithms. The four algorithms are compared and then it is proved GTEB exhibits best behaviour with respect to energy consumed, number of non-holes, number of holes, Non-Hole to Hole ratio, residual energy, overhead and throughput.

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An efficient transceiver optimization based routing technique for wireless sensor network

Cited by 2 publications

References 11 publications

On Wireless Sensor Network Models: A Cross-Layer Systematic Review

On Wireless Sensor Network Models: A Cross-Layer Systematic Review

An Energy Efficient and Lifetime Ratio Improvement Methods Based on Energy Balancing

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