Bin Packing with Linear Usage Costs
Hadrien Cambazard, Deepak Mehta, Barry O'Sullivan, Helmut Simonis

TL;DR
This paper introduces a variant of bin packing that incorporates linear usage costs to model energy consumption in data centres, providing new bounds and constraints for efficient virtual machine placement.
Contribution
It extends classical bin packing to include linear costs, develops LP-based lower bounds, and enhances the global constraint with cost information for better energy-efficient management.
Findings
LP-based lower bounds improve solution quality
Extended global constraint effectively models energy costs
Method enhances virtual machine placement efficiency
Abstract
Bin packing is a well studied problem involved in many applications. The classical bin packing problem is about minimising the number of bins and ignores how the bins are utilised. We focus in this paper, on a variant of bin packing that is at the heart of efficient management of data centres. In this context, servers can be viewed as bins and virtual machines as items. The efficient management of a data-centre involves minimising energy costs while ensuring service quality. The assignment of virtual machines on servers and how these servers are utilised has a huge impact on the energy consumption. We focus on a bin packing problem where linear costs are associated to the use of bins to model the energy consumption. We study lower bounds based on Linear Programming and extend the bin packing global constraint with cost information.
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Taxonomy
TopicsOptimization and Packing Problems · Advanced Manufacturing and Logistics Optimization · Manufacturing Process and Optimization
