TY - JOUR
T1 - Pricing-based strategies for autonomic control of web servers for time-varying request arrivals
AU - Chen, Yiyu
AU - Das, Amitayu
AU - Gautam, Natarajan
AU - Wang, Qian
AU - Sivasubramaniam, Anand
N1 - Funding Information:
Anand Sivasubramaniam received his B.Tech. in Computer Science from the Indian Institute of Technology, Madras, in 1989, and the M.S. and Ph.D. degrees in Computer Science from the Georgia Institute of Technology in 1991 and 1995, respectively. He has been on the faculty at The Pennsylvania State University since Fall 1995 where he is currently a Professor. Anand's research interests are in computer architecture, operating systems, performance evaluation, and applications for both high performance computer systems and embedded systems. Anand's research has been funded by NSF through several grants, including the CAREER award, and from industries including IBM, Microsoft and Unisys Corp. He has several publications in leading journals and conferences, and is on the editorial board of IEEE Transactions on Computers and IEEE Transactions on Parallel and Distributed Systems. He is a recipient of the 2002 and 2004 IBM Faculty Award. Anand is a member of the IEEE, IEEE Computer Society, and ACM.
Funding Information:
This research is partially supported by NSF Grant ACI-0325056 “Data-driven Autonomic Performance Modulation for Servers”.
PY - 2004/10
Y1 - 2004/10
N2 - This paper considers a web service that receives requests from customers at various rates at different times. The objective is to build an autonomic system that is tuned to different settings based on the varying conditions, both internally and externally. The authors have developed revenue-based pricing as well as admission control strategies, taking into account quality of service issues such as slow down and fairness aspects. Three heuristics are developed in this paper to address the pricing and admission control problem. The three heuristics are: (1) static pricing combined with queue-length-threshold-based admission control; (2) dynamic optimal pricing with no admission control; and (3) static pricing with nonnegative-profit-based admission control. These three strategies are benchmarked against a fourth strategy (called - do nothing) with no pricing and no admission control. The paper evaluates and compares their performance, implementability and computational complexity. The conclusion is that the web server revenue can be significantly increased by appropriately turning away customers via pricing or admission control mechanisms, and this can be done autonomically in the web server.
AB - This paper considers a web service that receives requests from customers at various rates at different times. The objective is to build an autonomic system that is tuned to different settings based on the varying conditions, both internally and externally. The authors have developed revenue-based pricing as well as admission control strategies, taking into account quality of service issues such as slow down and fairness aspects. Three heuristics are developed in this paper to address the pricing and admission control problem. The three heuristics are: (1) static pricing combined with queue-length-threshold-based admission control; (2) dynamic optimal pricing with no admission control; and (3) static pricing with nonnegative-profit-based admission control. These three strategies are benchmarked against a fourth strategy (called - do nothing) with no pricing and no admission control. The paper evaluates and compares their performance, implementability and computational complexity. The conclusion is that the web server revenue can be significantly increased by appropriately turning away customers via pricing or admission control mechanisms, and this can be done autonomically in the web server.
UR - https://www.scopus.com/pages/publications/9944220501
UR - https://www.scopus.com/pages/publications/9944220501#tab=citedBy
U2 - 10.1016/j.engappai.2004.09.001
DO - 10.1016/j.engappai.2004.09.001
M3 - Article
AN - SCOPUS:9944220501
SN - 0952-1976
VL - 17
SP - 841
EP - 854
JO - Engineering Applications of Artificial Intelligence
JF - Engineering Applications of Artificial Intelligence
IS - 7
ER -