4.7 Article

Cost-Aware Traffic Management Under Demand Uncertainty from a Colocation Data Center User's Perspective

Journal

IEEE TRANSACTIONS ON SERVICES COMPUTING
Volume 14, Issue 2, Pages 400-412

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/TSC.2018.2796095

Keywords

Bandwidth; Optimization; IP networks; Uncertainty; Stochastic processes; Degradation; Burstable billing; bandwidth; demand uncertainty; nonlinear mixed-integer programming; surplus maximization

Funding

  1. US National Science Foundation [1319798]
  2. Division Of Computer and Network Systems
  3. Direct For Computer & Info Scie & Enginr [1319798] Funding Source: National Science Foundation

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This paper introduces a cost-aware traffic management approach for colocation data center users under burstable billing, utilizing mathematical expressions to calculate 95th percentile usage and optimization problems to maximize user surplus. The resulting non-convex optimization problem can be efficiently solved or approximated using a convex program. Real-world workload traces show a reduction in IP transit cost by 26 percent and an increase in total surplus by 23 percent compared to current bandwidth allocation practices.
Burstable billing is widely adopted by colocation data center providers to charge their users for data transferring. This paper proposes a cost-aware traffic management approach for a colocation data center user under burstable billing where it is charged based on the 95th percentile bandwidth usage. To do this, we first develop a tractable mathematical expression to calculate the 95th percentile usage of a user. Then, we develop an optimization problem to maximize the user's surplus based on both deterministic and stochastic predictions of the user's demand. We show that the resulted optimization problem, while non-convex by nature, can be efficiently solved or approximated using a convex program. We also show that the proposed approach can also be applied in a more general scenario where the user gets services from multiple service providers. Using real-world workload traces, we show that the proposed approach can reduce a colocation data center user's IP transit cost by 26 percent and increase its total surplus by 23 percent, compared to the current practice of allocating bandwidth on-demand.

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