Global cost diversity aware dispatch algorithm for heterogeneous data centers (abstracts only)

Abstract

Large, Internet based companies service user requests from multiple data centers located across the globe. These data centers often house a heterogeneous computing infrastructure and draw electricity from the local electricity market.Reducing the electricity costs of operating these data centers is a challenging problem, and in this work, we propose a novel solution which exploits both the data center heterogeneity and global electricity market diversity to reduce data center operating cost. We evaluate our solution in our test-bed that simulates a heterogeneous data center, using real-world request workload and real-world electricity prices. We show that our strategies achieve cost and energy saving of at least 21% over a naive load balancing scheme that distributes requests evenly across data centers, and outperform existing solutions which either do not exploit the electricity market diversity or do not exploit data center hardware diversity.

Predictive Electricity Cost Minimization Through Energy Buffering in Data Centers

“…The optimized job migrations might reduce the electricity cost by the reduction of the bandwidth costs of migration of the application's state and data. Sankaranarayanan et al [21] propose a solution to reduce the operating costs via even distribution of workload across data centers. In [22] Kayaaslan et al propose an optimization framework for throughput-intensive applications like web search engines.…”