Remote data access from disparate sources across a widearea network such as the Internet is problematic due to the unpredictable nature of the communications medium and the lack of knowledge about the load and potential delays at remote sites. Traditional, static, query processing approaches break down in this environment because they are unable to adapt in response to unexpected delays. Query scrambling has been proposed to address this problem. Scrambling modifies query execution plans on-the-fly when delays are encountered during runtime. In its original formulation, scramblingwas based on simple heuristics, which althoughproviding good performance in many cases, were also shown to be susceptible to problems resulting from bad scrambling decisions. In this paper we address these shortcomings by investigatingways to exploit query optimization technology to aid in making intelligent scrambling choices. We propose three different approaches to using query optimization for scrambling...
Tolga Urhan, Michael J. Franklin, Laurent Amsaleg