Benchmarking XML processors for applications in grid web services

  • Authors:
  • Michael R. Head;Madhusudhan Govindaraju;Robert van Engelen;Wei Zhang

  • Affiliations:
  • State University of New York (SUNY) at Binghamton;State University of New York (SUNY) at Binghamton;Florida State University;Florida State University

  • Venue:
  • Proceedings of the 2006 ACM/IEEE conference on Supercomputing
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

Web services based specifications have emerged as the underlying architecture for core grid services and standards, such as WSRF. XML is inextricably inter-twined with Web services based specifications, and as a result the design and implementation of XML processing tools plays a significant role in grid applications. These applications use XML in a wide variety of ways, including workflow specifications, WS-Security based documents, service descriptions in WSDL, and on-the-wire format in SOAP-based communication. The application characteristics also vary widely in the use of XML messages in their performance, memory, size, and processing requirements. Numerous XML processing tools exist today, each of which is optimized for specific features. To make the right decisions, grid application and middleware developers must thus understand the complex dependencies between XML features and the application. We propose a standard benchmark suite for quantifying, comparing, and contrasting the performance of XML processors under a wide range of representative use cases. The benchmarks are defined by a set of XML schemas and conforming documents. To demonstrate the utility of the benchmarks and to provide a snapshot of the current XML implementation landscape, we report the performance of many different XML implementations, on the benchmarks, and draw conclusions about their current performance characteristics. We also present a brief analysis on the current shortcomings and required critical design changes for multi-threaded XML processing tools to run efficiently on emerging multi-core architectures.1