Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Online auction sites have very specific workloads and user behavior characteristics. Previous studies on workload characterization conducted by the authors shod 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. ,  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 re used to evaluate these caching strategies in terms of cache hit ratio and cache efficiency.
['D. Menasce', 'Vasudeva Akula']
I am writing a research paper on a idea Server-side caching strategies for online auction sites
[{"from": "human", "value": "I am writing a research paper on a idea Server-side caching strategies for online auction sites"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Online auction sites have very specific workloads and user behavior characteristics. Previous studies on workload characterization conducted by the authors shod 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. ,  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 re used to evaluate these caching strategies in terms of cache hit ratio and cache efficiency."}]