On fair attribution of costs under peak-based pricing to cloud tenants

Neda Nasiriani, Cheng Wang, George Kesidis, Bhuvan Urgaonkar, Lydia Y. Chen, Robert Birke

Research output: Contribution to journalArticle

6 Scopus citations

Abstract

The costs incurred by cloud providers towards operating their data centers are often determined in large part by their peak demands. The pricing schemes currently used by cloud providers to recoup these costs from their tenants, however, do not distinguish tenants based on their contributions to the cloud's overall peak demand. Using the concrete example of peak-based pricing as employed by many electric utility companies, we show that this “gap” may lead to unfair attribution of costs to the tenants. Simple enhancements of existing cloud pricing (e.g., analogous to the coincident peak pricing (CPP) used by some electric utilities) do not adequately address these shortcomings and suffer from short-term unfairness and undesirable oscillatory price-vs.demand relationships offered to tenants. To overcome these shortcomings, we define an alternative pricing scheme to more fairly distribute a cloud's costs among its tenants. We demonstrate the efficacy of our scheme under price-sensitive tenant demand response using a combination of (i) extensive empirical evaluation with recent workloads from commercial data centers operated by IBM and (ii) analytical [modeling] through non-cooperative game theory for a special case of tenant demand model.

Original languageEnglish (US)
Article number3
JournalACM Transactions on Modeling and Performance Evaluation of Computing Systems
Volume2
Issue number1
DOIs
StatePublished - Nov 2016

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Software
  • Safety, Risk, Reliability and Quality
  • Media Technology

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