Possibilities of Performance Modelling with UML
Performance Engineering, State of the Art and Current Trends
Resource Allocation for Session-Based Two-Dimensional Service Differentiation on e-Commerce Servers
IEEE Transactions on Parallel and Distributed Systems
Provisioning servers in the application tier for e-commerce systems
ACM Transactions on Internet Technology (TOIT)
Cost-based admission control for Internet Commerce QoS enhancement
Electronic Commerce Research and Applications
An intelligent Quality of Service brokering model for e-commerce
Expert Systems with Applications: An International Journal
WISE'07 Proceedings of the 8th international conference on Web information systems engineering
Journal of Network and Computer Applications
Regression-based resource provisioning for session slowdown guarantee in multi-tier Internet servers
Journal of Parallel and Distributed Computing
Proceedings of the Symposium on Theory of Modeling & Simulation - DEVS Integrative M&S Symposium
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Quality of service of e-commerce sites has been usually managed by the allocation of resources such as processors, disks, and network bandwidth, and by tracking conventional performance metrics such as response time, throughput, and availability. However, the metrics that are of utmost importance to the management of a Web store are revenue and profits. Thus, resource management schemes for e-commerce servers should be geared towards optimizing business metrics as opposed to conventional performance metrics. This paper introduces a state transition graph called Customer Behavior Model Graph (CBMG) to describe a customer session. It then presents a family of priority-based resource management policies for e-commerce servers. Priorities change dynamically as a function of the state a customer is in and as a function of the amount of money the customer has accumulated in his/her shopping cart. A detailed simulation model was developed to assess the gain of adaptive policies with respect to policies that are oblivious to economic considerations. Simulation results show that the adaptive priority scheme suggested here can increase, during peak periods, business-oriented metrics such as revenue/sec by as much as 43% over the non priority case.