Water-constrained geographic load balancing in data centers

Mohammad A. Islam, Shaolei Ren, Gang Quan, Muhammad Zeeshan Shakir, Athanasios V. Vasilakos

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)
30 Downloads (Pure)


Spreading across many parts of the world and presently hard striking California, extended droughts could even potentially threaten reliable electricity production and local water supplies, both of which are critical for data center operation. While numerous efforts have been dedicated to reducing data centers' energy consumption, the enormity of data centers' water footprints is largely neglected and, if still left unchecked, may handicap service availability during droughts. In this paper, we propose a water-aware workload management algorithm, called WATCH (WATer-constrained workload sCHeduling in data centers), which caps data centers' long-term water consumption by exploiting spatio-temporal diversities of water efficiency and dynamically dispatching workloads among distributed data centers. We demonstrate the effectiveness of WATCH both analytically and empirically using simulations: based on only online information, WATCH can result in a provably-low operational cost while successfully capping water consumption under a desired level. Our results also show that WATCH can cut water consumption by 20 percent while only incurring a negligible cost increase even compared to state-of-the-art cost-minimizing but water-oblivious solution. Sensitivity studies are conducted to validate WATCH under various settings.
Original languageEnglish
Pages (from-to)208-220
Number of pages13
JournalIEEE Transactions on Cloud Computing
Issue number2
Early online date8 Jul 2015
Publication statusPublished - 1 Apr 2017
Externally publishedYes


  • data center
  • geographical load balancing
  • resource management
  • sustainable IT
  • water footprint


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