Mapping Composition Combining Schema and Data Level Heterogeneity in Peer Data Sharing Systems

Authors

Md. Anisur Rahman, EECS, University of Ottawa, Ottawa, CanadaFollow
Mehedi Masud

Author Country (or Countries)

Canada

Abstract

The mapping semantics that combines the schema-level and the data-level mappings is called bi-level mappings. Bi-level mappings enhance data sharing overcoming the limitations of the non-combined approaches. This paper presents an algorithm for composing two bi-level mappings by using tableaux. Composition of mappings between peers has several computational advantages in a peer data management system, such as yielding more efficient query translation, pruning redundant paths, and better query execution plans. We also present a distributed algorithm for computing direct mapping between two end peers of a series of peers connected by a chain of mappings.

Suggested Reviewers

N/A

Recommended Citation

Anisur Rahman, Md. and Masud, Mehedi (2013) "Mapping Composition Combining Schema and Data Level Heterogeneity in Peer Data Sharing Systems," Applied Mathematics & Information Sciences: Vol. 07: Iss. 1, Article 11.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol07/iss1/11