Joint Multiple Resource Allocation Method for Cloud Computing Services with Different QOS to Users at Multiple Locations

Abstract

In a cloud computing environment, it is necessary to simultaneously allocate both processing ability and network bandwidth needed to access it. The authors proposed the joint multiple resource allocation method in a cloud computing environment that consists of multiple data centers with different QoS (Quality of Service). This paper proposes to enhance the existing joint multiple resource allocation method, so that it can handle multiple heterogeneous resource-attributes. Resource-attributes of bandwidth, for example, are network delay time, packet loss probability, etc. The basic idea is to identify the key resource-attribute first which has the most impact on resource allocation and to select the resources which provide the lowest QoS for the key resource-attribute as it satisfies required Quality of Service. It is demonstrated by simulation evaluations that the enhanced method (Method A) can reduce the total amount of resources up to 30%, compared with the existing method. It is also highly likely that each data center provides the different network delay to users at multiple locations.This paper proposes the further enhancement ofMethod A in order to handle the case where each data center provides the different network delay to users at multiple locations.