Modeling of Node Energy Consumption for Wireless Sensor Networks

Zhou, Haiying; Luo, Dan-Yan; Yan, Gao; Zuo, Decheng

doi:10.4236/wsn.2011.31003

Cited by 178 publications

(109 citation statements)

References 5 publications

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“…Similar studies in this area have been reported in [45], [46] and [62]. In this work mean energies consumed to transmit and receive data packets from a single state is considered.…”

Section: Energy Computationmentioning

confidence: 58%

A Framework for Energy Based Performability Models for Wireless Sensor Networks

Omondi¹,

Shah²,

Gemikonakli³

et al. 2015

2015 IEEE 29th International Conference on Advanced Information Networking and Applications Workshops

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Abstract-A novel idea of alternating node operations between Active and Sleep modes in Wireless Sensor Network (WSN) has successfully been used to save node power consumption. The idea which started off as a simple implementation of a timer in most protocols has been improved over the years to dynamically change with traffic conditions and the nature of application area. Recently, use of a second low power radio transceiver to triggered Active/Sleep modes has also been made. The idea of Active/Sleep operation modes has also been used to separately model and evaluate performance and availability of WSNs. The advancement in technology and continuous improvements of the existing protocols and application implementation demands continue to pose great challenges to the existing performance and availability models. In this study the need for integrating performance and availability studies of WSNs in the presence of both channel and node failures and repairs is investigated. A framework that outlines and characterizes key models required for integration of performance and availability of WSN is in turn outlined. Possible solution techniques for such models are also highlighted. Finally it is shown that the resulting models may be used to comparatively evaluate energy consumption of the existing motes and WSNs as well as deriving required performance measures.

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“…Similar studies in this area have been reported in [45], [46] and [62]. In this work mean energies consumed to transmit and receive data packets from a single state is considered.…”

Section: Energy Computationmentioning

confidence: 58%

A Framework for Energy Based Performability Models for Wireless Sensor Networks

Omondi¹,

Shah²,

Gemikonakli³

et al. 2015

2015 IEEE 29th International Conference on Advanced Information Networking and Applications Workshops

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show abstract

“…The used simulation are listed in Table I according to the radio basic energy dissipation model [4][5][6]. Last node die 1605 2500…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Many routing protocols have been proposed to improve the performance of the network, in particular the lifetime and energy consumption [2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A Centralized Energy Balancing In Clustering Process for WSN

Salah¹,

Boulouz²

2017

IJCA

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Wireless sensor networks consist of small battery powered. Devices with limited energy resources optimization of energy consumption is one of the most important challenges in WSNs due to the limited energy capacity of the network nodes. Several studies have been done in order to design energy efficient routing mechanism to increase the network lifetime. Clustering is one of the best used methods. This work proposes a centralized routing protocol used a CH selection by considering the remaining energy of sensor node in CH selecting process. Simulation results show that the proposed scheme reduces the energy consumption and prolong the network life-time of network compared to the well-known clustering algorithms LEACH.

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“…In this method, firstly, some points are randomly attributed as clusters' centers, in terms of the required clusters [14]. Then each datum, based on similarity, is attributed to one of clusters.…”

Section: K-means Algorithmmentioning

confidence: 99%

KGAWSN: An Effective Way to Reduce Energy Consumption in Wireless Sensor Networks by K-means and Genetic Algorithms

Delavar¹,

Alirezaie²,

Baradaran³

2012

IJCA

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In this paper, we present a method by which we can significantly reduce energy consumption in sensor networks. In the proposed method, finding an optimum Cluster Head (CH) is performed by Genetic Algorithm (GA) and clustering the network environment is done by k-means algorithm. The results of simulation show that at the end of some certain part of running the proposed algorithm, the number of alive nodes increases, comparing with the same previous methods and this can lead to an increase in sensor network lifetime.

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Modeling of Node Energy Consumption for Wireless Sensor Networks

Cited by 178 publications

References 5 publications

A Framework for Energy Based Performability Models for Wireless Sensor Networks

A Framework for Energy Based Performability Models for Wireless Sensor Networks

A Centralized Energy Balancing In Clustering Process for WSN

KGAWSN: An Effective Way to Reduce Energy Consumption in Wireless Sensor Networks by K-means and Genetic Algorithms

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