A Formal Approach to Investigate the Performance of Modern E-commerce Services

Modern E-commerce services are offered in a complex but flexible setup involving multiple websites (e.g., business web portals or price comparison websites) with facilities for determining the quality of products. Though this modern style of service provisioning attracts more customers it also significantly increases load on the web servers that are implementing the E-commerce services. The concern is that overloaded servers will become unresponsive and will drop requests which are beyond their capacity. This paper proposes a formal approach in order to investigate the effects of traffic load and the number of dropped requests on the performance of modern E-commerce services. The proposed approach is based on a class-based priority scheme that classifies E-commerce requests into different classes by taking into account the type of request and the client's behaviour. The proposed model is formally specified, implemented and tested through several experiments. The experimental results show that the proposed approach improves the response time and throughout of high priority requests, and also analyses the consequential effect on dropped (low priority) requests.

[1]  Virgílio A. F. Almeida,et al.  A methodology for workload characterization of E-commerce sites , 1999, EC '99.

[2]  Luís Soares Barbosa,et al.  Architectural Prototyping: From CCS to .Net , 2005, SBMF.

[3]  Irfan-Ullah Awan,et al.  Priority scheduling service for E-commerce web servers , 2008, Inf. Syst. E Bus. Manag..

[4]  Haining Wang,et al.  Profit-aware overload protection in E-commerce Web sites , 2009, J. Netw. Comput. Appl..

[5]  Robin Milner,et al.  Communicating and mobile systems - the Pi-calculus , 1999 .

[6]  B. Gu,et al.  The impact of online user reviews on hotel room sales , 2009 .

[7]  Erich M. Nahum,et al.  A method for transparent admission control and request scheduling in e-commerce web sites , 2004, WWW '04.

[8]  Andy J. Wellings Concurrent and real-time programming in Java , 2004 .

[9]  Joe F. Chicharo,et al.  Performance analysis of QoS mechanisms in IP networks , 2000, Proceedings ISCC 2000. Fifth IEEE Symposium on Computers and Communications.

[10]  Boi Faltings,et al.  Understanding user behavior in online feedback reporting , 2007, EC '07.

[11]  Krithi Ramamritham,et al.  Proxy-based acceleration of dynamically generated content on the world wide web: An approach and implementation , 2004, ACM Trans. Database Syst..

[12]  K. Mark,et al.  Analyzing Customer Behavior Model Graph (CBMG) using Markov Chains , 2007, 2007 11th International Conference on Intelligent Engineering Systems.

[13]  Paul A. Pavlou,et al.  Can online reviews reveal a product's true quality?: empirical findings and analytical modeling of Online word-of-mouth communication , 2006, EC '06.

[14]  Jordi Torres,et al.  Differentiated Quality of Service for e-Commerce Applications through Connection Scheduling based on System-Level Thread Priorities , 2007, 15th EUROMICRO International Conference on Parallel, Distributed and Network-Based Processing (PDP'07).

[15]  Irfan-Ullah Awan,et al.  A class-based scheme for E-commerce web servers: Formal specification and performance evaluation , 2009, J. Netw. Comput. Appl..