TY - GEN
T1 - A brokerage-based approach for cloud service selection
AU - Sundareswaran, Smitha
AU - Squicciarini, Anna
AU - Lin, Dan
PY - 2012
Y1 - 2012
N2 - great opportunities for consumers to find the best service and best pricing, which however raises new challenges on how to select the best service out of the huge pool. It is time-consuming for consumers to collect the necessary information and analyze all service providers to make the decision. This is also a highly demanding task from a computational-perspective, because the same computations may be conducted repeatedly by multiple consumers who have similar requirements. Therefore, in this paper, we propose a novel brokerage-based architecture in the Cloud, where the Cloud brokers is responsible for the service selection. In particular, we design a unique indexing technique for managing the information of a large number of Cloud service providers. We then develop efficient service selection algorithms that rank potential service providers and aggregate them if necessary. We prove the efficiency and effectiveness of our approach through an experimental study with the real and synthetic Cloud data.
AB - great opportunities for consumers to find the best service and best pricing, which however raises new challenges on how to select the best service out of the huge pool. It is time-consuming for consumers to collect the necessary information and analyze all service providers to make the decision. This is also a highly demanding task from a computational-perspective, because the same computations may be conducted repeatedly by multiple consumers who have similar requirements. Therefore, in this paper, we propose a novel brokerage-based architecture in the Cloud, where the Cloud brokers is responsible for the service selection. In particular, we design a unique indexing technique for managing the information of a large number of Cloud service providers. We then develop efficient service selection algorithms that rank potential service providers and aggregate them if necessary. We prove the efficiency and effectiveness of our approach through an experimental study with the real and synthetic Cloud data.
UR - http://www.scopus.com/inward/record.url?scp=84866757807&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84866757807&partnerID=8YFLogxK
U2 - 10.1109/CLOUD.2012.119
DO - 10.1109/CLOUD.2012.119
M3 - Conference contribution
AN - SCOPUS:84866757807
SN - 9780769547558
T3 - Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012
SP - 558
EP - 565
BT - Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012
T2 - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012
Y2 - 24 June 2012 through 29 June 2012
ER -