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Colocation Demand Response: Joint Online Mechanisms for Individual Utility and Social Welfare Maximization

机译:代管需求响应:个人效用和社会福利最大化的联合在线机制

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摘要

Data centers with high yet elastic energy demand are ideal candidates for participation in demand response programs. This paper studies emergency demand response (EDR) at multi-tenant colocation data centers (colocations). While the colocation has no direct control over tenants' servers, we design online mechanisms to incentivize and coordinate tenants' energy reduction. Our mechanism is online in nature, aiming to maximize not only social welfare but also tenant utility. Our main proposal is a truthful incentive auction that provides tenants with monetary remuneration for EDR energy reduction, minimizing social cost, which combines seamlessly with an online primal-dual framework for each tenant to schedule their delay-tolerant workloads. The online optimization at each tenant targets its utility maximization, concurrently reporting valuation functions for the tenant to participate in the auction. Our online algorithms achieve long-term performance guarantees in both tenants' utility and social welfare maximization, while fulfilling the EDR requirement with minimal diesel generation. We validate the efficiency of our algorithms through both the theoretical analysis and real-world trace-driven simulations.
机译:具有高弹性需求的数据中心是参与需求响应计划的理想人选。本文研究了多租户托管数据中心(托管)的紧急需求响应(EDR)。虽然托管不能直接控制租户的服务器,但我们设计了在线机制来激励和协调租户的节能。我们的机制本质上是在线的,旨在最大程度地提高社会福利和租户效用。我们的主要建议是进行一次真实的激励拍卖,为租户提供减少EDR能耗的货币报酬,从而最大程度地降低社会成本,并与每个租户无缝结合在线原始对偶框架来安排其延迟容忍的工作量。每个租户的在线优化均以其效用最大化为目标,同时报告租户参与拍卖的评估功能。我们的在线算法在确保租户的效用和社会福利最大化方面实现了长期性能保证,同时以最少的柴油生成量满足了EDR要求。我们通过理论分析和真实世界的跟踪驱动仿真来验证算法的效率。

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