Grouping genetic algorithm for solving the serverconsolidation problem with conflicts

Authors:
Shubham Agrawal;Sumit Kumar Bose;Srikanth Sundarrajan
Affiliations:
University of Texas at Austin, Austin, TX, USA;Infosys Technologies Ltd, Bangalore, India;Infosys Technologies Ltd, Bangalore, India
Venue:
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Year:
2009

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Abstract

The advent of virtualization technologies encourages organizations to undertake server consolidation exercises for improving the overall server utilization and for minimizing the capacity redundancy within data-centers. Identifying complimentary workload patterns is a key to the success of server consolidation exercises and for enabling multi-tenancy within data-centers. Existing works either do not consider incompatibility constraints or performs poorly on the disjointed conflict graphs. The algorithm proposed in the current work overcomes the limitations posed by the existing solutions. The current work models the server consolidation problem as a vector packing problem with conflicts (VPC) and tries to minimize the number of servers used for hosting applications within datacenters and maximizes the packing efficiency of the servers utilized. This paper solves the problem using techniques inspired from grouping genetic algorithm (GGA) - a variant of the traditional Genetic Algorithm (GA). The algorithm is tested over varying scenarios which show encouraging results.