Tuplespace-based computing for the semantic web: A survey of the state-of-the-art

  • Authors:

  • Lyndon j. b. Nixon;Elena Simperl;Reto Krummenacher;Francisco Martin-recuerda

  • Affiliations:

  • Freie universitä/t berlin, berlin, germany/ e-mail: nixon@inf.fu-berlin.de;Digital enterprise research institute (deri), universitä/t innsbruck, innsbruck, austria/ e-mail: elena.simperl,reto.krummenacher@deri.at;Digital enterprise research institute (deri), universitä/t innsbruck, innsbruck, austria/ e-mail: elena.simperl,reto.krummenacher@deri.at;Information management group (img), university of manchester, kilburn building, manchester, uk/ e-mail: fmartin-recuerda@cs.man.ac.uk

  • Venue:
  • The Knowledge Engineering Review
  • Year:
  • 2008

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Abstract

Semantic technologies promise to solve many challenging problems of the present Web applications. As they achieve a feasible level of maturity, they become increasingly accepted in various business settings at enterprise level. By contrast, their usability in open environments such as the Web—with respect to issues such as scalability, dynamism and openness—still requires additional investigation. In particular, Semantic Web services have inherited the Web service communication model, which is primarily based on synchronous message exchange technology such as remote procedure call (RPC), thus being incompatible with the REST (REpresentational State Transfer) architectural model of the Web. Recent advances in the field of middleware propose ‘semantic tuplespace computing’ as an instrument for coping with this situation. Arguing that truly Web-compliant Web service communication should be based, analogously to the conventional Web, on shared access to persistently published data instead of message passing, space-based middleware introduces a coordination infrastructure by means of which services can exchange information in a time-and reference-decoupled manner. In this article, we introduce the most important approaches in this newly emerging field. Our objective is to analyze and compare the solutions proposed so far, thus giving an account of the current state-of-the-art, and identifying new directions of research and development.