Efficient Bin Packing Algorithms for Resource Provisioning in the Cloud

We consider the Infrastructure as a Service (IaaS) model for cloud service providers. This model can be abstracted as a form of online bin packing problem where bins represent physical machines and items represent virtual machines with dynamic load. The input to the problem is a sequence of operations each involving an insertion, deletion or updating the size of an item. The goal is to use live migration to achieve packings with a small number of active bins. Reducing the number of bins is critical for green computing and saving on energy costs. We introduce an algorithm, named HarmonicMix, that supports all operations and moves at most ten items per operation. The algorithm achieves a competitive ratio of 4/3, implying that the number of active bins at any stage of the algorithm is at most 4/3 times more than any offline algorithm that uses infinite migration. This is an improvement over a recent result of Song et al. [12] who introduced an algorithm, named VISBP, with a competitive ratio of 3/2. Our experiments indicate a considerable advantage for HarmonicMix over VISBP with respect to average-case performance. HarmonicMix is simple and runs as fast as classic bin packing algorithms such as Best Fit and First Fit; this makes the algorithm suitable for practical purposes.