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Improving the performance of online auction sites through closing time rescheduling

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2 Author(s)
Menasce, D. ; Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA ; Akula, V.

The workload of auction sites exhibits some interesting features as indicated in previous work by the authors. Of particular importance to this paper is the fact that over thirty percent of the bids of an auction arrive in the last five percent of the auction's lifetime. This creates a surge in the load seen by auction sites as an auction's closing time approaches. The site's performance is degraded if the site is not able to cope with these load spikes. With performance degradation comes frustrated customers and lost business. To mitigate this problem, we propose that auction sites reschedule auction closing times within a relatively small window centered around the closing time originally proposed by a customer. The scheduler's goal is to more evenly distribute the number of closings of auctions in order to produce a more uniform distribution of the number of bids on the auction site. This paper describes the auction closing time scheduling algorithm, applies it to a trace of auctions and bids obtained from an actual auction site, and uses a simulation model to study the effects of the rescheduled trace on the site's performance. In addition to that, the paper presents an algorithm to obtain a complete knowledge (CK) but nonrealizable schedule. This schedule could be used as a benchmark for comparison with the realizable rescheduled load.

Published in:

Quantitative Evaluation of Systems, 2004. QEST 2004. Proceedings. First International Conference on the

Date of Conference:

27-30 Sept. 2004