Title: Optimising QoS in adaptive real-time systems with energy constraint varying CPU frequency

Authors: Ríad Nassiffe; Eduardo Camponogara; George Lima; Daniel Mossé

Addresses: Department of Automation and System Engineering (DAS), Federal University of Santa Catarina (UFSC), Florianópolis, SC, Brazil ' Department of Automation and System Engineering (DAS), Federal University of Santa Catarina (UFSC), Florianópolis, SC, Brazil ' Department of Computer Science (DCC), Federal University of Bahia (UFBA), Salvador, BA, Brazil ' Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, USA

Abstract: The life time of some real-time systems is determined by batteries, thus necessitating a mechanism for energy management. These systems must consider not only schedulability constraints to ensure temporal correctness, but also their energy limitations to accomplish their considered mission. Moreover, it is still desired that the system provides services with the best possible quality. This work presents a problem of selecting the frequency for each task to fulfil the system goal, while considering issues of schedulability and energy consumption. The problem is formulated in mathematical programming and solved with a convex-optimisation algorithm. It is assumed that CPU frequency can be selected continuously within a given range. The system reconfiguration scheme assumes the earliest deadline first (EDF) policy, with soft and hard real-time tasks managed by some bandwidth reservation scheme. The effectiveness of the proposed solution is shown through numerical and simulation analysis.

Keywords: energy savings; optimisation; quality of service; QoS; real-time systems; energy management; CPU frequency; system lifetime; scheduling; energy consumption; system reconfiguration; earliest deadline first; EDF; bandwidth reservation; simulation.

DOI: 10.1504/IJES.2016.080380

International Journal of Embedded Systems, 2016 Vol.8 No.5/6, pp.368 - 379

Received: 05 Jan 2014
Accepted: 24 Apr 2014

Published online: 17 Nov 2016 *

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