Profit maximization resource allocation in cloud computing with performance guarantee

Meixuan Li, Yu-E Sun, He Huang, Jing Yuan, Yang Du, Yu Bao, Yonglong Luo · 2017

With the advent of virtualization technologies, cloud computing resource allocation issue plays an important role. However, the existing studies have not fully considered the heterogeneous demands from different cloud tenants. To tackle this, we design a more flexible cloud resource allocation mechanism which can maximize the profit of the cloud provider and support three general types of resource requirements from the cloud tenants. In this work, the jobs from tenants will bid for the usage of VMs in 3 types: 1) fixed time intervals, 2) time window intervals and 3) Time window slice intervals. We proved that the proposed approximation allocation mechanism has an approximation factor which approaches 1.58 when cmcloses to infinity.

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