No abstract

In a cloud computing environment with multiple data centers over a wide area, it is highly likely that each data center would provide the different service quality to users at different locations. It is also required to consider the nodes at the edge of the network (local cloud) which support applications such as IoTs that require low latency and location awareness. The authors proposed the joint multiple resource allocation method in a cloud computing environment that consists of multiple data centers and each data center provides the different network delay. However, the existing method does not take account of cases where requests that require a short network delay occur more than expected. Moreover, the existing method does not take account of service processing time in data centers and therefore cannot provide the optimal resource allocation when it is necessary to take the total processing time (both network delay and service processing time in a data center) into consideration in resource allocation. This paper proposes to enhance the existing joint multiple resource allocation method, so as to provide the following two functions: (1) a function to prevent the degradation in service quality of other request types when requests that require a short network delay occur more than expected, and (2) a function to take account of the total processing time of network delay and service processing time in allocating resources. It is demonstrated by simulation evaluations that the enhanced method can handle up to twice as many requests as the existing method with the same amount of resources, and can cope with the excessive generation of requests from the specific access point.

No abstract

ABSTRACT

The widespread use of cloud computing services is expected to increase the power consumed by ICT equipment in cloud computing environments rapidly.