Cross-Layer Optimization of Radio Sleep Intervals to Increase Thin Client Energy Efficiency

Simoens, Pieter; Ali, Farhan Azmat; Vankeirsbilck, Bert; Deboosere, Lien; Turck, Filip De; Dhoedt, Bart; Demeester, Piet; Torrea-Duran, Rodolfo

doi:10.1109/lcomm.2010.100810.101450

Cited by 10 publications

(2 citation statements)

References 20 publications

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“…This sleep mode is interrupted at regular intervals to transmit user events by using Idle Time Reduction Algorithm (ITRA). Researchers have used crosslayer optimization to reduce WNIC energy consumption by up to 52 percent [8]. …”

Section: Cross-layer Identification Of Wnic Sleep Intervalsmentioning

confidence: 99%

Mitigating wireless network interface card energy consumption in mobile devices

Prasad¹,

Koneri²,

Shivakumar³

2013

National Conference on Challenges in Research &Amp; Technology in the Coming Decades (CRT 2013)

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Growing interest towards pervasive and mobile computing is encouraging the extension of popular Internet services to mobile users. Network accesses by mobile devices are done through wireless network interface card (WNIC) which might result in a significant energy drain from the device battery. In this paper we proposed two approaches two mitigate WNIC energy consumption on mobile devices. Cross layer identification of WNIC sleep intervals and energy efficient multimedia streaming protocol, are discussed throughout the paper for energy optimization of mobile devices.

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Section: Cross-layer Identification Of Wnic Sleep Intervalsmentioning

confidence: 99%

Mitigating wireless network interface card energy consumption in mobile devices

Prasad¹,

Koneri²,

Shivakumar³

2013

National Conference on Challenges in Research &Amp; Technology in the Coming Decades (CRT 2013)

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“…Recently, interference mitigation techniques have been adapted to work in systems that employ multiple-input and multiple-output (MIMO) transmissions [9,10]. Another important topic is sleep modes [11][12][13]. These traditionally allow the system to actively alter its energy consumption by turning on and off its radio frequency (RF) front end depending on traffic conditions and transmission requests.…”

Section: Introductionmentioning

confidence: 99%

Resource allocation for energy efficient cellular systems

Videv

Thompson

Haas

et al. 2012

J Wireless Com Network

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The need for more throughput in wireless cellular networks has been increasing in recent years. It has led to an increase in operational costs due to higher energy use as operators deploy more cell sites or increase transmission power at existing ones to satisfy demand. Energy costs are a major expense, and reducing them is a priority. This article presents a scheduler which aims to solve the problem of energy efficient resource allocation in orthogonal frequency division multiple access (OFDMA) cellular systems. The suggested approach is to make the resource scheduling process also consider energy costs as well as allow it to manipulate these by exploiting time/frequency vs energy efficiency trade-offs that are present in the system. The energy efficient score-based scheduler (EESBS) is a novel scheduler which takes energy costs into account when allocating resource blocks (RBs) to users. This allows it to promote energy efficiency in the system alongside throughput and fairness maximization. One of the means it has to manipulate users' expended energy is the bandwidth expanded mode (BEM). BEM is a technique that allows the scheduler to decrease a user's energy consumption by allocating it more RBs and maintaining a constant data rate. This is possible when the energy consumption is dominated by the energy used for data communication as opposed to control channel overhead transmission. Time compression mode (TCoM) is a technique that is complementary to BEM. It allows for energy savings through a reduction of the number of allocated RBs to a user when the energy consumption is dominated by the transmission of signaling traffic. Both BEM and TCoM need to be employed by an energy-aware scheduler like EESBS in order to extract the maximum performance gains. A realistic framework modeling future cellular systems is established to test the performance of the proposed techniques. Within this framework, EESBS generates an average energy saving of 29% over a frequency selective proportional fair (FsPF) benchmark. EESBS coupled with BEM or TCoM achieves a saving of 38% over the same benchmark. These savings are achieved with no detriment to user satisfaction in terms of achieved data rate.

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