Erich P. Stuntebeck, John S. Davis II, et al.
HotMobile 2008
Autonomic Computing lays out a vision of information technology in which systems manage themselves based on policies. As a result, policies are the new currency of interaction between people and computers, creating a new paradigm for interaction with autonomic systems. In this paradigm, interaction shifts (1) from low-level to high-level monitoring and control, and (2) from manually performing actions to delegating tasks to automation. In this paper, we report an experimental study comparing and contrasting manual interaction to policy-based interaction to manage a simulated e-commerce website. In this study, we investigated issues related to human expertise and policy representation. Our results suggest that effective policy-based interaction depends both on the level of detail of the policies and on the experience of the system supervisor. Our results show an overall benefit of policy-based interaction, as measured by business and technology-oriented metrics. Performance was significantly better with policy-based interaction following expertise gained through manual interaction. Performance with manual interaction was marginally worse after policy-based interaction, suggesting the classic out-of-the-loop problem. In addition, highly detailed policy representations marginally improved performance for technology-oriented metrics but did not yield significant differences for business-oriented metrics. ©2006 IEEE.
Erich P. Stuntebeck, John S. Davis II, et al.
HotMobile 2008
Raymond Wu, Jie Lu
ITA Conference 2007
Pradip Bose
VTS 1998
Sumeer Bhola, Mark Astley, et al.
ICAC 2006