Improving the Performance of Online Auctions Through Server-side Activity-based Caching |
| |
Authors: | Daniel A Menascé Vasudeva Akula |
| |
Affiliation: | (1) Department of Computer Science, George Mason University, Fairfax, VA 22030, USA;(2) The Volgenau School of Information Technology and Engineering, George Mason University, Fairfax, VA 22030, USA |
| |
Abstract: | Online auction sites have very specific workloads and user behavior characteristics. Previous studies on workload characterization
conducted by the authors showed that (1) bidding activity on auctions increases considerably after 90% of an auction’s life
time has elapsed, (2) a very large percentage of auctions have a relatively low number of bids and bidders and a very small
percentage of auctions have a high number of bids and bidders, (3) prices rise very fast after an auction has lasted more
than 90% of its life time. Thus, if bidders are not able to successfully bid at the very last moments of an auction because
of site overload, the final price may not be as high as it could be and sellers, and consequently the auction site, may lose
revenue. In this paper, we propose server-side caching strategies in which cache placement and replacement policies are based
on auction-related parameters such as number of bids placed or percent remaining time till closing time. A main-memory auction
cache at the application server can be used to reduce accesses to the back-end database server. Trace-based simulations were
used to evaluate these caching strategies in terms of cache hit ratio and cache efficiency. The performance characteristics
of the best policies were then evaluated through experiments conducted on a benchmark online auction system. |
| |
Keywords: | online auctions server-side caching auction-specific caching trace-based simulations |
本文献已被 SpringerLink 等数据库收录! |
|