Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/22197
Title: Robust Dynamic CPU Resource Provisioning in Virtualized Servers
Authors: Makridis, Evagoras 
Deliparaschos, Kyriakos M. 
Kalyvianaki, Evangelia 
Zolotas, Argyrios C. 
Charalambous, Themistoklis 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Resource provisioning;Virtualized servers;CPU allocation;CPU usage;RUBiS;Robust prediction;H∞ filter;MCC-KF;Kalman filter
Issue Date: 2020
Source: IEEE Transactions on Services Computing, 2020
Journal: IEEE Transactions on Services Computing 
Abstract: We present robust dynamic resource allocation mechanisms to allocate application resources meeting Service Level Objectives (SLOs) agreed between cloud providers and customers. In fact, two filter-based robust controllers, i.e. H∞ filter and Maximum Correntropy Criterion Kalman filter (MCC-KF), are proposed. The controllers are self-adaptive, with process noise variances and covariances calculated using previous measurements within a time window. In the allocation process, a bounded client mean response time (mRT) is maintained. Both controllers are deployed and evaluated on an experimental testbed hosting the RUBiS (Rice University Bidding System) auction benchmark web site. The proposed controllers offer improved performance under abrupt workload changes, shown via rigorous comparison with current state-of-the-art. On our experimental setup, the Single-Input-Single-Output (SISO) controllers can operate on the same server where the resource allocation is performed; while Multi-Input-Multi-Output (MIMO) controllers are on a separate server where all the data are collected for decision making. SISO controllers take decisions not dependent to other system states (servers), albeit MIMO controllers are characterized by increased communication overhead and potential delays. While SISO controllers offer improved performance over MIMO ones, the latter enable a more informed decision making framework for resource allocation problem of multi-tier applications.
URI: https://ktisis.cut.ac.cy/handle/10488/22197
ISSN: 1939-1374
DOI: 10.1109/TSC.2020.2966972
Rights: © IEEE
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Article
Affiliation : Aalto University 
Cyprus University of Technology 
Cambridge University 
Cranfield University 
Appears in Collections:Άρθρα/Articles

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