Online auction sites have very specific workloads and user behavior characteristics. Previous studies on workload characterization conducted by the authors showed that i) bidding activity on auctions increases considerably after 90% of an auction's life time has elapsed, ii) 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, iii) 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 ...
Daniel A. Menascé, Vasudeva Akula