A scheduling algorithm for revenue maximisation for cluster-based Internet services

This paper proposes a new priority scheduling algorithm to maximise site revenue of session-based multi-tier Internet services in a multicluster environment. This research is part of a larger study in support of large-scale online trading systems and, as a result, this case study is chosen as a demonstrator for the techniques presented in this paper. The trading system is partitioned into a number of operations (trade, query etc.), which by their very nature are divided into orders of importance in terms of transactional response. The algorithm in this paper is based on Mean Value Analysis (MVA), which is used for the calculation of performance metrics concerning the queuing networks and workload allocation decision support in the multicluster. In addition to this, the priority assignment is based on combination of three attributes of any given request: (i) the sender class; (ii) the operation and, (Hi) the status of the user´s portfolio (i.e.number of items in the user´s portfolio). A discrete event simulator has been developed to evaluate the performance of the priority scheduling scheme with different combinations of request attributes in various experimental scenarios. Our study aims to develop a dynamic scheduling policy, which takes into account real-time system parameters and optimises the site revenue. Although our priority scheduling algorithm is designed for an online trading system, it can be applied to most e-Commerce systems in which differentiated services are required.