On Application Behavior Extraction and Prediction to Support and Improve Process Scheduling Decisions
Evgueni Dodonov, Rodrigo Fernandes de Mello · IGI Global eBooks · 2010
The knowledge of application behavior allows predicting their expected workload and future operations. Such knowledge can be used to support, improve and optimize scheduling decisions by distributing data accesses and minimizing communication overheads. Different techniques can be used to obtain such knowledge, varying from simple source code analysis, sequential access pattern extraction, history-based approaches and on-line behavior extraction methods. The extracted behavior can be later classified into different groups, representing process execution states, and then used to predict future process events. This chapter describes different approaches, strategies and methods for application behavior extraction and classification, and also how this information can be used to predict new events, focusing on distributed process scheduling.