@inproceedings{9c4277228b4a421ab95f80803a5fef28,
title = "STOCHASTIC MODELING AND OPTIMIZATION FOR POWER AND PERFORMANCE CONTROL IN DVFS SYSTEMS",
abstract = "The paper addresses the problem of performance-energy trade-off in DVFS (Dynamic Voltage Frequency Scaling) systems. We propose a stochastic hybrid model between hysteresis models and server block models. We provide a closed form for the steady-state distribution probability and we establish a”st” type order to compare the performance measures. The fast computation of power and performance measures leads to a multi-objective optimization analysis in two forms: a scalarization method and a Pareto based method. For the two approaches, we propose fast and efficient approximate algorithms that construct progressively an optimal solution. To discuss results, the model is used to simulate a physical server hosting several VMs (Virtual Machines) where we investigate optimal thresholds for the performance-energy trade-off.",
keywords = "DVFS, Markov Chain, Multi-Objective Optimization, Performance, Power consumption analysis, Stochastic modeling",
author = "\{El Mahjoub\}, \{Youssef Ait\} and \{Le Corre\}, L{\'e}o and Hind Castel-Taleb",
note = "Publisher Copyright: {\textcopyright} ECMS Enrico Vicario, Romeo Bandinelli, Virginia Fani, Michele Mastroianni (Editors) 2023.; 37th ECMS International Conference on Modelling and Simulation, ECMS 2023 ; Conference date: 20-06-2023 Through 23-06-2023",
year = "2023",
month = jan,
day = "1",
language = "English",
series = "Proceedings - European Council for Modelling and Simulation, ECMS",
publisher = "European Council for Modelling and Simulation",
pages = "497--506",
editor = "Enrico Vicario and Romeo Bandinelli and Virginia Fani and Michele Mastroianni",
booktitle = "Proceedings of the 37th ECMS International Conference on Modelling and Simulation, ECMS 2023",
}