Load and network aware query routing for information integration

Wen Syan Li, Vishal S. Batra, Vijayshankar Raman, Wei Han, K. Selçuk Candan, Inderpal Narang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Current federated systems deploy cost-based query optimization mechanisms; i.e., the optimizer selects a global query plan with the lowest cost to execute. Thus, cost functions influence what remote sources (i.e. equivalent data sources) to access and how federated queries are processed. In most federated systems, the underlying cost model is based on database statistics and query statements; however, the system load of remote sources and the dynamic nature of the network latency in wide area networks are not considered. As a result, federated query processing solutions can not adapt to runtime environment changes, such as network congestion or heavy workloads at remote sources. We present a novel system architecture that deploys a Query Cost Calibrator to calibrate the cost function based on system load and network latency at the remote sources and consequently indirectly "influences" query routing and load distribution in federated information systems.

Original languageEnglish (US)
Title of host publicationProceedings - 21st International Conference on Data Engineering, ICDE 2005
Pages927-938
Number of pages12
DOIs
StatePublished - Dec 12 2005
Event21st International Conference on Data Engineering, ICDE 2005 - Tokyo, Japan
Duration: Apr 5 2005Apr 8 2005

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other21st International Conference on Data Engineering, ICDE 2005
CountryJapan
CityTokyo
Period4/5/054/8/05

    Fingerprint

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

Cite this

Li, W. S., Batra, V. S., Raman, V., Han, W., Candan, K. S., & Narang, I. (2005). Load and network aware query routing for information integration. In Proceedings - 21st International Conference on Data Engineering, ICDE 2005 (pp. 927-938). (Proceedings - International Conference on Data Engineering). https://doi.org/10.1109/ICDE.2005.83