Improved Centralized XML Query Processing Using Distributed Query Workload
Year: 2021
Type: article
Abstract: eXtensible Markup Language (XML) is used widely to transfer data among a wide variety of systems.Due to an increase in query workloads and management of larger datasets, centralized processing is no longer feasible for XML query processing.To address this issue, we propose a technique that improves XML query processing through query workload distribution.An effective distributed XML query processing can be affected by several criteria such as indexing, fragmentation, distribution strategy, and well as the query handling in the distributed servers.However, we believe that an efficient labeling mechanism and an inexpensive centralized query processors or a pruning method at dedicated servers contribute greatly to the overall performance of a distributed query processor.In this paper, we present an effective centralized pruning technique that is adopted into our proposed distributed XML query processing technique to process XML queries robustly.Experimental evaluations showed that the proposed distributed query processor superseded the performance of centralized query processor.
Source: IEEE Access
Authors: Samini Subramaniam, Su-Cheng Haw, Lay-Ki Soon
Institutions: Multimedia University, Monash University Malaysia
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,750
Funder: Telekom Malaysia Berhad
OpenAlex ID: W3130041283