Energy-Efficient Multi-Granularity Resource Reservations for Multimedia Services

Sun, Joohyung; Cho, Hyeonjoong

doi:10.1007/978-94-007-2792-2_12

Cited by 1 publication

(2 citation statements)

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“…This paper draws upon our previously published work in which we proposed an energy-efficient real-time scheduling algorithm and evaluated it through the simulation experiments [11]. Compared with the previous work, the current work includes two major improvements as follows:…”

Section: Introductionmentioning

confidence: 99%

“…This paper draws upon our previously published work in which we proposed an energy‐efficient real‐time scheduling algorithm and evaluated it through the simulation experiments [11]. Compared with the previous work, the current work includes two major improvements as follows: To maximise the energy efficiency, lpWDA‐MG‐AGG/CON are designed to utilise the early depletion slack , which was ignored in our previous work.…”

Section: Introductionmentioning

confidence: 99%

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Power‐efficient real‐time scheduling based on multi‐granularity resource reservation for multimedia services

Sun

Cho

2017

IET softw.

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Recent advances in mobile technologies have led to improved quality of multimedia services (QoMS) in a variety of mobile devices. Because multimedia has become a major form of content consumption for mobile users, satisfying user expectation on QoMS in energy-restricted mobile devices is critical. This need has motivated us to develop an aggressive and conservative low-power work demand analysis with multi-granularity (lpWDA-MG-AGG/CON) algorithm, designed to minimise power consumption in mobile devices by utilising a dynamic voltage scaling technique while simultaneously ensuring QoMS based on a resource reservation scheme. In addition, the authors analytically showed the schedulability of the proposed scheme under the rate monotonic scheduling policy. For performance evaluation, the authors implemented the two lpWDA-MG algorithms and several existing algorithms in a Linux operating system. Specifically, the authors measured power consumption with a power metre and determined that the proposed algorithms consume about 40% less dynamic power than the other existing algorithms. Moreover, the authors found that the proposed algorithms ensure acceptable QoMS.

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Section: Introductionmentioning

confidence: 99%