Managing server clusters on intermittent power
Document Type
Article
Publication Date
1-1-2015
Abstract
Reducing the energy footprint of data centers continues to receive significant attention due to both its financial and environmental impact. There are numerous methods that limit the impact of both factors, such as expanding the use of renewable energy or participating in automated demand-response programs. To take advantage of these methods, servers and applications must gracefully handle intermittent constraints in their power supply. In this paper, we propose blinking-metered transitions between a high-power active state and a low-power inactive state-as the primary abstraction for conforming to intermittent power constraints. We design Blink, an application-independent hardware-software platform for developing and evaluating blinking applications, and define multiple types of blinking policies.We then use Blink to design both a blinking version of memcached (BlinkCache) and a multimedia cache (GreenCache) to demonstrate how application characteristics affect the design of blink-aware distributed applications. Our results show that for BlinkCache, a load-proportional blinking policy combines the advantages of both activation and synchronous blinking for realistic Zipf-like popularity distributions and wind/solar power signals by achieving near optimal hit rates (within 15% of an activation policy), while also providing fairer access to the cache (within 2% of a synchronous policy) for equally popular objects. In contrast, for GreenCache, due to multimedia workload patterns, we find that a staggered load proportional blinking policy with replication of the first chunk of each video reduces the buffering time at all power levels, as compared to activation or load-proportional blinking policies.
Recommended Citation
Sharma, Navin; Krishnappa, Dilip; Barker, Sean; Irwin, David; and Shenoy, Prashant, "Managing server clusters on intermittent power" (2015). Computer Science Faculty Publications. 3.
https://digitalcommons.bowdoin.edu/computer-science-faculty-publications/3