TY - GEN
T1 - Concurrent placement, capacity provisioning, and request flow control for a distributed cloud infrastructure
AU - Chen, Shuang
AU - Wang, Yanzhi
AU - Pedram, Massoud
PY - 2014
Y1 - 2014
N2 - Cloud computing and storage have attracted a lot of attention due to the ever increasing demand for reliable and cost-effective access to vast resources and services available on the Internet. Cloud services are typically hosted in a set of geographically distributed data centers, which we will call the cloud infrastructure. To minimize the total cost of ownership of this cloud infrastructure (which accounts for both the upfront capital cost and the operational cost of the infrastructure resources), the infrastructure owners/operators must do a careful planning of data center locations in the targeted service area (for example the US territories), data center capacity provisioning (i.e., the total CPU cycles per second that can be provided in each data center). In addition, they must have flow control policies that will distribute the incoming user requests to the available resources in the cloud infrastructure. This paper presents an approach for solving the unified problem of data center placement and provisioning, and request flow control in one shot. The solution technique is based on mathematical programming. Experimental results, using Google cluster data and placement/provisioning of up to eight data center sites demonstrate the cost savings of the proposed problem formulation and solution approach.
AB - Cloud computing and storage have attracted a lot of attention due to the ever increasing demand for reliable and cost-effective access to vast resources and services available on the Internet. Cloud services are typically hosted in a set of geographically distributed data centers, which we will call the cloud infrastructure. To minimize the total cost of ownership of this cloud infrastructure (which accounts for both the upfront capital cost and the operational cost of the infrastructure resources), the infrastructure owners/operators must do a careful planning of data center locations in the targeted service area (for example the US territories), data center capacity provisioning (i.e., the total CPU cycles per second that can be provided in each data center). In addition, they must have flow control policies that will distribute the incoming user requests to the available resources in the cloud infrastructure. This paper presents an approach for solving the unified problem of data center placement and provisioning, and request flow control in one shot. The solution technique is based on mathematical programming. Experimental results, using Google cluster data and placement/provisioning of up to eight data center sites demonstrate the cost savings of the proposed problem formulation and solution approach.
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U2 - 10.7873/DATE2014.292
DO - 10.7873/DATE2014.292
M3 - Conference contribution
AN - SCOPUS:84903835570
SN - 9783981537024
T3 - Proceedings -Design, Automation and Test in Europe, DATE
BT - Proceedings - Design, Automation and Test in Europe, DATE 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th Design, Automation and Test in Europe, DATE 2014
Y2 - 24 March 2014 through 28 March 2014
ER -