Market Driven Multi-Resource Allocation

Liran Funaro, Ph.D. Thesis Seminar
Monday, 12.8.2019, 16:00
Room 301 Taub Bld.
Prof. Assaf Schuster and Dr. Orna Agmon Ben-Yehuda

Suboptimal resource utilization among public and private cloud providers prevents them from maximizing their economic potential. Long-term allocated resources are often idle when they might have been subleased for a short period. Alternatively, arbitrary resource overcommitment may lead to unpredictable client performance. We propose a mechanism for fixed availability (traditional) resource allocation alongside stochastic resource allocation in the form of shares. We show its benefit for private and public cloud providers and for a wide range of clients. Our simulations show that our mechanism can increase server consolidation by 5.6 times on average compared with selling only fixed performance resources, and by 1.7 times compared with burstable instances, which is the most prevalent flexible allocation method. Our mechanism also yields better performance (i.e., higher revenues) or a lower cost than burstable instances for a wide range of clients, making it more profitable for them.

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