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Kauia, HI, USA
Jan. 4, 2006 to Jan. 7, 2006
ISBN: 0-7695-2507-5
pp: 30a
Eleanna Kafeza , Athens University of Economics and Business
Dickson K. W. Chiu , Dickson Computer Systems
Kamalakar Karlapalem , International Institute of Information Technology
ABSTRACT
Large enterprises in application domains such as finance, banking, travel services, and hospital management use business processes for their day-to-day business. An integral part of these business processes are the nested processes (composed as multiple levels of sub-activities, and/or tasks). A task is an atomic unit of work, such as a database transaction, human input, validation of data, and approval of a quote. Processes are assigned for execution to agents (including software objects, humans, and web-services), and their execution involves multiple agents. Each agent at any point of time has an input queue with a set of processes that need to be executed. Although existing process management systems provide functionality for scheduling and executing processes, they are inadequate to guarantee the response time. The main issue is that execution of processes does not always occur as scheduled. In order to improve the response time, some of the processes have to execute urgently. In this paper, we label during the execution of business processes, some of them as urgent processes according to the urgency level of the associated alert and provide scheduling algorithms to facilitate earlier of completion of their execution. This labeling is dynamic and on-line so that other concurrently executing processes are not unduly affected. We discuss the effectiveness of these algorithms in improving the response time of the chosen urgent processes.
INDEX TERMS
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CITATION
Eleanna Kafeza, Dickson K. W. Chiu, Kamalakar Karlapalem, "Improving the Response Time of Business Processes: An Alert-Based Analytical Approach", HICSS, 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences, Proceedings of the 39th Annual Hawaii International Conference on System Sciences 2006, pp. 30a, doi:10.1109/HICSS.2006.218
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