Open AccessPower‐aware speed scaling in multiprocessor systems
Author(s) -
Singh Pawan
Publication year - 2018
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2016.0365
Subject(s) - multiprocessing , computer science , schedule , scheduling (production processes) , multiprocessor scheduling , energy consumption , dynamic voltage scaling , parallel computing , scaling , real time computing , dynamic priority scheduling , mathematical optimization , rate monotonic scheduling , operating system , engineering , mathematics , geometry , electrical engineering
A huge consumption of energy in the data centres has become a motivation for improvement in computing capability and energy conservation. The dynamic speed scaling and job scheduling are efficient methods to improve the energy efficiency of processors. In this study, an online non‐clairvoyant scheduling algorithm arrival time‐algorithm (At‐ALG) is proposed with an objective to scale the speed of processors and schedule the jobs in a multiprocessor system to minimise the total magnitude‐based/weighted flow time plus energy consumed. The traditional power function Power=Speed ω is adopted, where ω > 1 is a constant. At‐ALG is analysed, against an offline adversary, using the potential function analysis. The magnitude/weight/priority of jobs in At‐ALG are generated using their processed time (waiting time plus executed time) and speed of any processor depends on the number of active jobs plus sum of processed time of active jobs. At‐ALG is O ( 1 ) ‐competitive with no resource augmentation.