High-density model for server allocation and placement

  • Authors:
  • Craig W. Cameron;Steven H. Low;David X. Wei

  • Affiliations:
  • Caltech, Pasadena, CA;Caltech, Pasadena, CA;Caltech, Pasadena, CA

  • Venue:
  • SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
  • Year:
  • 2002

Quantified Score

Hi-index 0.02

Visualization

Abstract

It is well known that optimal server placement is NP-hard. We present an approximate model for the case when both clients and servers are dense, and propose a simple server allocation and placement algorithm based on high-rate vector quantization theory. The key idea is to regard the location of a request as a random variable with probability density that is proportional to the demand at that location, and the problem of server placement as source coding, i.e., to optimally map a source value (request location) to a code-word (server location) to minimize distortion (network cost). This view has led to a joint server allocation and placement algorithm that has a time-complexity that is linear in the number of clients. Simulations are presented to illustrate its performance.