Energy-Efficient Policy Based on Cross-Layer Cooperation in Wireless Communication

Zhang, Juan; Jiang, Hong; Jiang, Hesong; Chen, Chunmei

doi:10.1155/2014/831686

Cited by 3 publications

(5 citation statements)

References 20 publications

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“…The probability distribution function (PDF) of SNR φ for Rayleigh fading can be stated as follows [6]:…”

Section: State Transition Probability For Channel Statesmentioning

confidence: 99%

“…The probability distribution function (PDF) of SNR

φ

for Rayleigh fading can be stated as follows [6]:

f_{φ} false(φ_{0} false) = \frac{1}{φ_{0}} e^{(- (φ / φ_{0}))}

where

φ_{0}

is the mean value of the SNR.…”

Section: System Model For Mdpmentioning

confidence: 99%

“…Cross-layer design is a powerful tool to enhance the system performance regarding defined performance metrics. In many of the earlier efforts [6][7][8][9], cross-layer protocols have been developed to decrease the latency in packet delivery and increase overall throughput of the system by efficient packet routing. Cross-layer outperforms traditional layer design approach by addressing the issues of the individual layer in a single protocol stack [10,11].…”

Section: Introductionmentioning

confidence: 99%

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Energy efficient policy selection in wireless sensor network using cross layer approach

Trapasiya¹,

Soni²

2017

IET wirel. sens. syst.

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The authors have addressed the issue of energy saving in packet retransmission by reducing the packet loss in the first attempt. They have formulated the problem as Markov decision process and mapped the system into various states based on system dynamics like channel gain, buffer space, battery energy and harvested energy. In wireless sensor network, adaptive policy management is the best approach to work out with the variation of system states in a dynamically changing environment. The policies are defined regarding various controllable parameters like transmission power, modulation scheme, and transmission rate. The solution is sought regarding best policy selection as per the individual state of the system. They have evaluated the performance of the proposed optimum transreceiver scheme by extensive simulations with existing schemes like optimum energy allocation, adaptive modulation and adaptive power management for the various performance metrics like net bit rate and energy consumption in retransmission of packets for different system states. ReTrans energy consumption in packet retransmission P S probability of symbol error η solar to DC conversion efficiency l size of packet IET Wirel. Sens. Syst.

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“…The probability distribution function (PDF) of SNR φ for Rayleigh fading can be stated as follows [6]:…”

Section: State Transition Probability For Channel Statesmentioning

confidence: 99%

“…The probability distribution function (PDF) of SNR

φ

for Rayleigh fading can be stated as follows [6]:

f_{φ} false(φ_{0} false) = \frac{1}{φ_{0}} e^{(- (φ / φ_{0}))}

where

φ_{0}

is the mean value of the SNR.…”

Section: System Model For Mdpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Energy efficient policy selection in wireless sensor network using cross layer approach

Trapasiya¹,

Soni²

2017

IET wirel. sens. syst.

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show abstract

“…However, the MAB model shows an incomplete description, which is an agent of sequential decision-making problems in many real worlds. To this end, all kinds of related models have recently been studied by Beygelzimer et al [30], In particular, within budget-limited MABs, each action has a different reward and is constrained by the total energy. To solve this problem, Tran-Thanh et al [31] proposed some efficient algorithms which are the unbounded ε-first and KUBE.…”

Section: Related Workmentioning

confidence: 99%

Study of Multi-Armed Bandits for Energy Conservation in Cognitive Radio Sensor Networks

Zhang

Jiang

Huang

et al. 2015

Sensors

Self Cite

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Technological advances have led to the emergence of wireless sensor nodes in wireless networks. Sensor nodes are usually battery powered and hence have strict energy constraints. As a result, energy conservation is very important in the wireless sensor network protocol design and the limited power resources are the biggest challenge in wireless network channels. Link adaptation techniques improve the link quality by adjusting medium access control (MAC) parameters such as frame size, data rate, and sleep time, thereby improving energy efficiency. In this paper we present an adaptive packet size strategy for energy efficient wireless sensor networks. The main goal is to reduce power consumption and extend the whole network life. In order to achieve this goal, the paper introduces the concept of a bounded MAB to find the optimal packet size to transfer by formulating different packet sizes for different arms under the channel condition. At the same time, in achieve fast convergence, we consider the bandwidth evaluation according to ACK. The experiment shows that the packet size is adaptive when the channel quality changes and our algorithm can obtain the optimal packet size. We observe that the MAB packet size adaptation scheme achieves the best energy efficiency across the whole simulation duration in comparison with the fixed frame size scheme, the random packet size and the extended Kalman filter (EKF).

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“…Мультимедийный метод сбора данных рассматривается в работе [18], при этом утверждается, что кластеризация является одним из методов уменьшения потребления энергии узлами БСС. Эвристический алгоритм HE-PDS в работе [19] предлагается дополнить межслоевым взаимодействием (cross-layer cooperation). В работе [20] предлагается энергосберегающая политика планирования пакета, которая учитывает временную корреляцию с соседними узлами при передаче данных.…”

Section: анализ литературных данных и постановка проблемыunclassified

An algorithm for operating and optimizing information flows in wireless sensor networks

Галкин

2014

EEJET

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Energy-Efficient Policy Based on Cross-Layer Cooperation in Wireless Communication

Cited by 3 publications

References 20 publications

Energy efficient policy selection in wireless sensor network using cross layer approach

Energy efficient policy selection in wireless sensor network using cross layer approach

Study of Multi-Armed Bandits for Energy Conservation in Cognitive Radio Sensor Networks

An algorithm for operating and optimizing information flows in wireless sensor networks

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