Trading virtual machines to stabilize revenue in public clouds

Abstract

By obtaining virtual machines (VMs) from infrastructure providers (InPs) according to the demand in public cloud services, service providers (SPs) can elastically provide network services to users. As the charging methods of VMs, reserved instance (RI) and on-demand instance (ODI) are widely used. For InPs, RI is more desirable than ODI thanks to easiness of estimating long-term revenue, risk aversion of occurring idle VM resources, and reduction of charging cost. In this paper, to improve the ratio of RI in VMs prepared by an InP, we propose VM trading methods in which idle RI of SPs with VM demand falling below the amount of contracted RI are applied to SPs with VM demand exceeding the amount of contracted RI. As the VM trading mechanisms, we investigate two approaches: RI with self-help effort (RISE) and RI with mutual aid (RIMA). Through numerical evaluation using the demand pattern of commercial VoD service, we show that the proposed VM trading methods decrease the number of VMs required for ODI by about 50% to 100% and increase the ratio of RI by about 10% to 70%.