On the Use of Genetic Algorithms in Database Client Clustering
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
| Hi-index | 0.00 |
Client-server computing has become the dominant platform in engineering and manufacturing environments. Typically, a large number of designers simultaneously work in order to draft new systems and components. Database servers supporting such activities often become the bottleneck as the number of users increases. This adversely affects the scalability of such client-server databases. To this end, data caching techniques have been introduced to ease resource contention at the server sites. In this paper, we present an aggregate caching configuration based on static clustering of client sites. We compare the aggregate caching configuration with a conventional flat configuration. Through experimentation, we show that the aggregate caching configuration can offer significant performance gains in terms of response time.