TY - GEN
T1 - Competitive Strategies for Online Cloud Resource Allocation with Discounts
T2 - 35th IEEE International Conference on Distributed Computing Systems, ICDCS 2015
AU - Hu, Xinhui
AU - Ludwig, Arne
AU - Richa, Andrea
AU - Schmid, Stefan
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/22
Y1 - 2015/7/22
N2 - Cloud computing heralded an era where resources can be scaled up and down elastically and in an online manner. This paper initiates the study of cost-effective cloud resource allocation algorithms under price discounts, using a competitive analysis approach. We show that for a single resource, the online resource renting problem can be seen as a 2-dimensional variant of the classic online parking permit problem, and we formally introduce the PPP⊃ problem accordingly. Our main contribution is an online algorithm for PPP⊃ which achieves a deterministic competitive ratio of k (under a certain set of assumptions), where k is the number of resource bundles. This is almost optimal, as we also prove a lower bound of k/3 for any deterministic online algorithm. Our online algorithm makes use of an optimal offline algorithm, which may be of independent interest since it is the first optimal offline algorithm for the 1D and 2D versions of the parking permit problem. Finally, we show that our algorithms and results also generalize to multiple resources (i.e., Multi-dimensional parking permit problems).
AB - Cloud computing heralded an era where resources can be scaled up and down elastically and in an online manner. This paper initiates the study of cost-effective cloud resource allocation algorithms under price discounts, using a competitive analysis approach. We show that for a single resource, the online resource renting problem can be seen as a 2-dimensional variant of the classic online parking permit problem, and we formally introduce the PPP⊃ problem accordingly. Our main contribution is an online algorithm for PPP⊃ which achieves a deterministic competitive ratio of k (under a certain set of assumptions), where k is the number of resource bundles. This is almost optimal, as we also prove a lower bound of k/3 for any deterministic online algorithm. Our online algorithm makes use of an optimal offline algorithm, which may be of independent interest since it is the first optimal offline algorithm for the 1D and 2D versions of the parking permit problem. Finally, we show that our algorithms and results also generalize to multiple resources (i.e., Multi-dimensional parking permit problems).
KW - Cloud Computing
KW - Competitive Analysis
KW - Online Algorithm
KW - Resource Allocation
UR - http://www.scopus.com/inward/record.url?scp=84944328986&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84944328986&partnerID=8YFLogxK
U2 - 10.1109/ICDCS.2015.18
DO - 10.1109/ICDCS.2015.18
M3 - Conference contribution
AN - SCOPUS:84944328986
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 93
EP - 102
BT - Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems, ICDCS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 June 2015 through 2 July 2015
ER -