Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Neural networks for pattern recognition
Neural networks for pattern recognition
Machine Learning - Special issue on learning with probabilistic representations
Capacity planning for Web performance: metrics, models, and methods
Capacity planning for Web performance: metrics, models, and methods
Distributional clustering of English words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Data analysis with bayesian networks: a bootstrap approach
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
The Journal of Supercomputing
Parameter inference of queueing models for IT systems using end-to-end measurements
Performance Evaluation
Automatic request categorization in internet services
ACM SIGMETRICS Performance Evaluation Review
| Hi-index | 0.00 |
In order for current e-Businesses to mature from hastily assembled systems and applications, formal processes must be put in place for planning and budgeting, pricing and costing, and for establishing quality of service and service--level assurances. There are many challenges that e-Businesses face in formalizing these processes. The most important problem is to bridge the semantic disconnect between business objectives and the information system performance objectives. Next, the characterization of the e-Business infrastructure is extremely complex, given the variety of applications and system configurations at a web site and the traffic it receives. Finally, e-Businesses need to associate and apply traditional economic factors, such as depreciation and usage to applications, operating systems, and databases. In this paper, we propose an approach for defining and quantifying effective e-Business capacity that allows us to translate quality of service objectives into the number of users that a web site can support. This approach is based on inducing online models using machine learning and statistical pattern recognition techniques. As a consequence, the approach is flexible: it adapts to any site configuration and environment. The concept of e-Business capacity allows us to naturally answer planning and operational questions about the information system infrastructure needed to support the e-Business. The questions range from indicating which performance measures in the system are "important" to simulating "if-then" scenarios