Energy Consumption Optimization in Data Center with Latency Based on Histograms and Discrete-Time MDP

Léa Bayati

2023

Abstract

This article introduces a probabilistic model for managing power dynamically (DPM) in a data center. The model involves switching servers on and off, while considering both the time it takes for the machines to be-come active and the amount of energy they consume. The goal of DPM is to balance energy consumption with Quality of Service (QoS) requirements. To construct the model, job arrivals and service rates are represented using histograms, which are discrete distributions derived from actual traces, empirical data, or measurements of incoming traffic. The data center is modeled as a queue, and the optimization problem is formulated as a discrete-time Markov decision process (MDP) in order to identify the optimal policy. The proposed approach is evaluated using real traffic traces from Google, and different levels of latency are compared.

Paper Citation

in Harvard Style

Bayati L. (2023). Energy Consumption Optimization in Data Center with Latency Based on Histograms and Discrete-Time MDP. In Proceedings of the 12th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-651-4, SciTePress, pages 98-105. DOI: 10.5220/0011846400003491

in Bibtex Style

@conference{smartgreens23,
author={Léa Bayati},
title={Energy Consumption Optimization in Data Center with Latency Based on Histograms and Discrete-Time MDP},
booktitle={Proceedings of the 12th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2023},
pages={98-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011846400003491},
isbn={978-989-758-651-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Energy Consumption Optimization in Data Center with Latency Based on Histograms and Discrete-Time MDP
SN - 978-989-758-651-4
AU - Bayati L.
PY - 2023
SP - 98
EP - 105
DO - 10.5220/0011846400003491
PB - SciTePress