TY - GEN
T1 - A performance prediction scheme for computation-intensive applications on cloud
AU - Zhang, Hongli
AU - Li, Panpan
AU - Zhou, Zhigang
AU - Du, Xiaojiang
AU - Zhang, Weizhe
PY - 2013
Y1 - 2013
N2 - As cloud computing services are gaining popularity, many organizations are considering migrating their large-scale computing applications to cloud. Different cloud service providers (CSPs) may have different computing platforms and billing methods. Most cloud customers don't know which CSP is more suitable for their applications and how much computing resource should be purchased. To address this issue, in this paper, we present a performance prediction scheme that allows a cloud customer to accurately predict computing resource (e.g., running time) for an application. The proposed scheme identifies application's control flow and scaling blocks, constructs a miniature version program to run in local machines, and then replays it in cloud to get the performance ratio between local and cloud. Our real-network experiments show that the scheme can achieve high prediction accuracy with low overhead.
AB - As cloud computing services are gaining popularity, many organizations are considering migrating their large-scale computing applications to cloud. Different cloud service providers (CSPs) may have different computing platforms and billing methods. Most cloud customers don't know which CSP is more suitable for their applications and how much computing resource should be purchased. To address this issue, in this paper, we present a performance prediction scheme that allows a cloud customer to accurately predict computing resource (e.g., running time) for an application. The proposed scheme identifies application's control flow and scaling blocks, constructs a miniature version program to run in local machines, and then replays it in cloud to get the performance ratio between local and cloud. Our real-network experiments show that the scheme can achieve high prediction accuracy with low overhead.
KW - Cloud computing
KW - cost
KW - performance prediction
UR - http://www.scopus.com/inward/record.url?scp=84891370574&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84891370574&partnerID=8YFLogxK
U2 - 10.1109/ICC.2013.6654810
DO - 10.1109/ICC.2013.6654810
M3 - Conference contribution
AN - SCOPUS:84891370574
SN - 9781467331227
T3 - IEEE International Conference on Communications
SP - 1957
EP - 1961
BT - 2013 IEEE International Conference on Communications, ICC 2013
T2 - 2013 IEEE International Conference on Communications, ICC 2013
Y2 - 9 June 2013 through 13 June 2013
ER -