Optimizing cloud utilization via switching decisions

Author:

Feinberg Eugene1,Zhang Xiaoxuan2

Affiliation:

1. Stony Brook University, Stony Brook, NY

2. IBM T.J. Watson Research Center, Yorktown Heights, NY

Abstract

This paper studies a control problem for optimal switching on and off a cloud computing services modeled by an M=M=1 queue with holding, running and switching costs. The main result is that an average-optimal policy either always runs the system or is an (M; N)- policy defined by two thresholds M and N, such that the system is switched on upon an arrival epoch when the system size accumulates to N and it is switched off upon a departure epoch when the system size decreases to M. We compare the optimal (M; N)-policy with the classical (0; N)-policy and show the non-optimality of it.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference16 articles.

1. Amazon Elastic Compute Cloud User Guide. http://aiweb.techfak.uni-bielefeld.de/content/ bworld-robot-control-software/ December 2012. Online; accessed 03/01/2013. Amazon Elastic Compute Cloud User Guide. http://aiweb.techfak.uni-bielefeld.de/content/ bworld-robot-control-software/ December 2012. Online; accessed 03/01/2013.

2. On Linear Programming in a Markov Decision Problem

3. Reduction of Discounted Continuous-Time MDPs with Unbounded Jump and Reward Rates to Discrete-Time Total-Reward MDPs

4. Google Compute Engine. https://cloud.google.com/products/compute-engine 2013. Google Compute Engine. https://cloud.google.com/products/compute-engine 2013.

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