A novel statistical time-series pattern based interval forecasting strategy for activity durations in workflow systems

Forecasting workflow activity durations is of great importance to support satisfactory QoS in workflow systems. Traditionally, a workflow system is often designed to facilitate the process automation in a specific application domain where activities are of the similar nature. Hence, a particular forecasting strategy is employed by a workflow system and applied uniformly to all its workflow activities. However, with newly emerging requirement to serve as a type of middleware services for high performance computing infrastructures such as grid and cloud computing, more and more workflow systems are designed to be general purpose to support workflow applications from many different domains. Due to such a problem, the forecasting strategies in workflow systems must adapt to different workflow applications which are normally executed repeatedly such as data/computation intensive scientific applications (mainly with longduration activities) and instance intensive business applications (mainl...

• Type: Journal
• Year: 2011
• Where: JSS
• Authors: Xiao Liu, Zhiwei Ni, Dong Yuan, Yuan-Chun Jiang, Zhangjun Wu, Jinjun Chen, Yun Yang
• Keywords: Duration Activities, Intensive Business Applications, JSS 2011, Linear Time Series