Hardness of Approximation and Greedy Algorithms for the Adaptation Problem in Virtual Environments

  • Authors:

  • A. I. Sundararaj;M. Sanghi;J. R. Lange;P. A. Dinda

  • Affiliations:

  • Department of Electrical Engineering and Computer Science, Northwestern University. ais@cs.northwest;-;-;-

  • Venue:
  • ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
  • Year:
  • 2006

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Abstract

Over the past decade, wide-area distributed computing has emerged as a powerful computing paradigm. Virtual machines greatly simplify wide-area distributed computing by lowering the abstraction to benefit both resource users and providers. A virtual execution environment consisting of virtual machines (VMs) interconnected with virtual networks provides opportunities to dynamically optimize, at run-time, the performance of existing, unmodified distributed applications without any user or programmer intervention. We have formalized the adaptation problem in virtual execution environments and shown that it is NP-hard to both, solve and approximate within a factor of m1/2-δfor any δ 0, where m is the number of edges in the virtual overlay graph. We also designed and evaluated greedy adaptation algorithms and found them to work well in practice.