Heterogeneous Resource Reservation

Given a large variety of resources and billing contracts offered by today’s cloud providers, the application owner faces a non-trivial challenge optimizing their selection for application workloads.

A number of works exist that deal either with either billing contracts selection optimization or resource types selection. We argue that the largest cost savings to elastic workloads result from jointly optimizing heterogeneous resources and billing contracts selection. To this end, we introduce a novel cloud control and management framework and formulate a novel optimization problem called Heterogeneous Resource Reservation (HRR).

We evaluate our solution through a thorough simulation study using publicly available cloud workload data as well as internal anonymous customer data. For this data we demonstrate that dramatic cost savings are attainable through our proposed approach.

By: Ofer Biran, David Breithand, Dean Lorenz, Michael Masin, Eran Raichstein, Avi Weit, Ilyas Iyoob

Published in: H-0331 in 2018


This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.


Questions about this service can be mailed to reports@us.ibm.com .