Accessible from all over the world, the EC became an indispensable element to our society. It allows the use of electronic systems to exchange products, services and information between the different existent users. During these exchanges, it is very important to assure a good quality of service. However, the enormous expansion of the Internet users push its resources to the maximum of its limits, which provoke, in many cases, an important degradation in its performance. Consequently, it is primordial to analyze the capacity of servers in order to handle heavy workloads that are growing considerably as a function of the number of users. It is, therefore, necessary to conduct performance tests before servers' deployment in order to detect any imperfection and predict their behavior under stress. In this context, this paper present a simplified performance evaluation of the “alpha” version of a negotiation platform called Generic Negotiation Platform (GNP) dated on September 2000. This platform is still under development. Many performance factors could be examined in this evaluation. However, we considered only the response time factor because of its important impact on auctions and negotiations applications. We mostly oriented this study to give us an idea about the variation of the average response time of the server as a function of the number of users and the type of different transactions. We also tried to evaluate the effect of the auctions' rules on the server average response time. We limited our study to the close and open auctions at the second price. This study followed the traditional way of doing performance tests. Therefore, we fixed our test objectives and criterion and then create our own scripts. Once the nature of the workload of the server was specified, we created an adequate benchmark to generate requests to the server. Afterwards, the average response time of each considered transaction was collected. In order to interpret these results properly, we calculated the standard deviation and the coefficient of variation of each set of values.
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