JOURNAL ARTICLE

Online dynamic capacity provisioning in data centers

Abstract

Power consumption imposes a significant cost for implementing cloud services, yet much of that power is used to maintain excess service capacity during periods of low load. In this work, we study how to avoid such waste via an online dynamic capacity provisioning. We overview recent results showing that the optimal offline algorithm for dynamic capacity provisioning has a simple structure when viewed in reverse time, and this structure can be exploited to develop a new 'lazy' online algorithm which is 3-competitive. Additionally, we analyze the performance of the more traditional approach of receding horizon control and introduce a new variant with a significantly improved worst-case performance guarantee.

Keywords:
Provisioning Computer science Cloud computing Online algorithm Dynamic demand Competitive analysis Simple (philosophy) Distributed computing Power consumption Capacity planning Service (business) Time horizon Work (physics) Power (physics) Computer network Mathematical optimization Algorithm Upper and lower bounds Engineering Business Operating system

Metrics

24
Cited By
5.98
FWCI (Field Weighted Citation Impact)
25
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
Optimization and Search Problems
Physical Sciences →  Computer Science →  Computer Networks and Communications
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications

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