Efficient Algorithms for Selecting Optimal Data Collection Locations in Business Process Management

摘要：

The flexibility and dynamism of service-oriented architecture (SOA) makes it critical to monitor and manage services behaviors at runtime for performance assurance. In this paper, two efficient evidence channel selection (ECS) algorithms are designed to select service run-time data collection locations for business process management. The design of ESC algorithms are based on the classic facilities location problems: k-median and Set-Covering. The performance study shows that these ECS algorithms significantly reduce data collection cost and achieve better diagnosis correctness compared to random ECS selection.

作者: Yue Zhang Kwei-Jay Lin

作者单位: Department of Electrical Engineering and Computer Science University of California, Irvine Irvine, CA 92697, USA

会议类型: 国际会议

会议名称: AiR08，EM2108，SOAIC08，SIOKM08，BIMA08，DKEEE08(2008IEEE国际电子商务工程学术会议)

会议地点: 西安

会议语种:英文

页码: 747-752

在线出版日期: 2008-10-22（万方平台首次上网日期，不代表论文的发表时间）