Multi-objective temporal bin packing problem: An application in cloud computing

•We tackle the virtual machine placement, an extension of the temporal bin-packing.•An optimization model minimizing the number of servers and fire-ups is proposed.•Proposed heuristic and column generation algorithms provide strong upper/lower bounds.•We observe that the number of fire-ups decreases...

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Bibliographic Details
Published in:Computers & operations research Vol. 121; p. 104959
Main Authors: Aydın, Nurşen, Muter, İbrahim, İlker Birbil, Ş.
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.09.2020
Pergamon Press Inc
Subjects:
Algorithms
Bin packing
Cloud computing
Column generation
Exact methods
Heuristic
Heuristic methods
Heuristics
Integer programming
Lower bounds
Operations research
Packing problem
Performance evaluation
Servers
Virtual environments
Bin packing
Cloud computing
Exact methods
Column generation
Heuristics
ISSN:0305-0548, 1873-765X, 0305-0548
Online Access:Get full text
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Summary:•We tackle the virtual machine placement, an extension of the temporal bin-packing.•An optimization model minimizing the number of servers and fire-ups is proposed.•Proposed heuristic and column generation algorithms provide strong upper/lower bounds.•We observe that the number of fire-ups decreases with the number of servers. Improving energy efficiency and lowering operational costs are the main challenges faced in systems with multiple servers. One prevalent objective in such systems is to minimize the number of servers required to process a given set of tasks under server capacity constraints. This objective leads to the well-known bin packing problem. In this study, we consider a generalization of this problem with a time dimension, where the tasks are to be performed with predefined start and end times. This new dimension brings about new performance considerations, one of which is the uninterrupted utilization of servers. This study is motivated by the problem of energy efficient assignment of virtual machines to physical servers in a cloud computing service. We address the virtual machine placement problem and present a binary integer programming model to develop different assignment policies. By analyzing the structural properties of the problem, we propose an efficient heuristic method based on solving smaller versions of the original problem iteratively. Moreover, we design a column generation algorithm that yields a lower bound on the objective value, which can be utilized to evaluate the performance of the heuristic algorithm. Our numerical study indicates that the proposed heuristic is capable of solving large-scale instances in a short time with small optimality gaps.
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2020.104959