skip to main content
research-article

Network Service Description and Discovery for High-Performance Ubiquitous and Pervasive Grids

Published:01 February 2011Publication History
Skip Abstract Section

Abstract

Ubiquitous and pervasive Grid computing is an emerging computing paradigm that will have a significant impact on the next-generation information infrastructure. Communication networks form a significant integrant of ubiquitous and pervasive Grids and must be utilized effectively by the Grids. The notion of Grid network service may greatly facilitate integrating networking systems into the Grid architecture, and network service description and discovery play a crucial role in the network-Grid integration. Current service description and discovery technologies must be enhanced to meet the special requirements of network service description and discovery for high-performance ubiquitous and pervasive Grids. Network service description needs a model for service provisioning capability and network service discovery must be able to select those networks that meet certain performance requirements. The wide variety of networking systems in ubiquitous and pervasive Grids require general and flexible network service description and discovery approaches that are applicable to heterogeneous networks. The research presented in this article aims at developing network service description and discovery technologies for high-performance ubiquitous and pervasive Grid computing. The main contributions of this article include a general model for describing service capabilities of various networking systems, a service discovery technology for selecting network services that meet the performance requirements specified by Grid applications, and a resource allocation scheme for Grid network services to provide networking performance guarantees. The developed model and technologies are general and flexible; thus are applicable to the wide variety of heterogeneous networks in ubiquitous and pervasive Grid computing environments.

References

  1. Al-Marsri, E. and Mahmoud, Q. H. 2007. QoS-Based discovery and ranking of Web services. In Proceedings of the 16th IEEE International Conference on Computer Communications and Networks.Google ScholarGoogle Scholar
  2. Ambrosi, E., Bianchi, M., Gaibisso, C., Gambosi, G., and Lombardi, F. 2005. A system for predicting the run-time behavior of Web services. In Proceedings of the International Conference on Services Systems and Services Management.Google ScholarGoogle Scholar
  3. Badia, L., Miozzo, M., Rossi, M., and Zorzi, M. 2007. Routing schemes in heterogeneous wireless networks based on access advertisment and backward utilities for qos support. IEEE Comm. Mag. 45, 2, 67--73. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Barzilai, T. P., Kandlur, D. D., Mehra, A., and Saha, D. 1998. Design and implementation of an rsvp-based quality of service architecture for an integrated service internet. IEEE J. Select. Areas Comm. 3, 397--413. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Boudec, J. L. and Thiran, P. 2001. Network Calculus: A Theory of Deterministic Queueing Systems for the Internet. Springer. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Butto, M., Cavallero, E., and Tonietti, A. 1991. Effectiveness of the leaky bucket policing mechanisms in ATM networks. IEEE J. Select. Areas Comm. 9, 4, 335--342.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Camarillo, G. and Garcia-Martin, M. A. 2008. The 3G IP Multimedia Subsystem (IMS) 3rd Ed. Wiley.Google ScholarGoogle Scholar
  8. Chen, L. and Heinzelman, W. B. 2007. A survey of routing protocols that support qos in mobile ad hoc networks. IEEE Netw. Mag. 21, 6, 30--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Chen, Y., Mao, W., and Li, X. 2008. Federation framework for service discovery in ubiquitous computing. In Proceedings of the 11th International Conference on Communication Technology.Google ScholarGoogle Scholar
  10. Derbal, Y. M. 2005. Probabilistic resource state estimation in networked environments: The case of computational Grids. In Proceedings of the 3rd Annual Communication Networks and Services Research Conference. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Frank, K., Suraci, V., and Mitic, J. 2008. Personalizable service discovery in pervasive systems. In Proceedings of the 4th International Conference on Networking and Services. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Gu, X., Shi, H., and Ye, J. 2008. A hierarchical service discovery framework for ubiquitous computing. In Proceedings of the 3rd International Conference on Pervasive Computing and Applications.Google ScholarGoogle Scholar
  13. IETF. 1998. An architecture for differentiated services. ietf rfc 2475.Google ScholarGoogle Scholar
  14. ITU-T. 2008. Resources and admission control functions in the next generation networks. https://www.itu.int/ITU/worksem/ngn/200604/presentation/s3_lu.pdf.Google ScholarGoogle Scholar
  15. Kind, A., Dimitropoulos, X., Denazis, S., and Claise, B. 2008. Advanced network monitoring brings life to the wareness plane. IEEE Comm. Mag. 46, 10, 140--146. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Lacour, S., Perez, C., and Priola, T. 2004. Network topology description model for Grid application deployment. In Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Li, M., Yu, B., Rana, O., and Wang, Z. 2008. Grid service discovery with rough sets. IEEE Trans. Knowl. Data Engin. 20, 6, 851--862. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Ng, T. S. E. and Zhang, H. 2002. Predicting internet network distance with coordinates-based approaches. In Proceedings of the IEEE Conference on Computer Communications.Google ScholarGoogle Scholar
  19. OASIS. 2005. OASIS specification: Universal description, discovery and integration (UDDI) version 3.0.2.Google ScholarGoogle Scholar
  20. OGF. 2005. Open grid forum GHPN-RG working draft: Grid network services (GNS). May. www.ogf.org.Google ScholarGoogle Scholar
  21. OGF. 2008. Open grid forum GHPN-RG working draft: Grid user network interface (GUNI). February. www.ogf.org.Google ScholarGoogle Scholar
  22. OGF. 2009. Open grid forum NMC-WG working draft: An extensible protocol for network measurement and control. May. www.ogf.org.Google ScholarGoogle Scholar
  23. Park, K.-L. and Yoon, U. H. 2009. Personalized service discovery in ubiquitous computing environments. IEEE Pervas. Comput. 8, 1, 58--65. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Prasad, R., Murray, M., Dovrolis, C., and Claffy, K. 2003. Bandwidth estimation: Metrics, measurement techniques, and tools. IEEE Netw. Mag. 17, 6, 27--35. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Sivavakeesar, S., Gonzalez, O. F., and Pavlou, G. 2006. Service discovery strategies in ubiquitous communication environments. IEEE Comm. Mag. 44, 9, 106--113. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Stiliadis, D. and Varma, A. 1998. Latency-Rate servers: A general model for analysis of traffic scheduling algorithms. IEEE/ACM Trans. Netw. 6, 5, 611--624. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. van der Ham, J., Grosso, P., van der Pol, R., Toonk, A., and de Laat, C. 2007. Using the network description lanaguage in optical networks. In Proceedings of the 10th IFIP/IEEE International Symposium on Integrated Network Management.Google ScholarGoogle Scholar
  28. W3C. 2006. World wide web consortium (W3C) recommendation: Web service description language (WSDL) version 2. March. http://www.w3.org/TR/wsdl20-primer/.Google ScholarGoogle Scholar
  29. Wan, C., Ullrich, C., Chen, L., Huang, R., Luo, J., and Shi, A. 2008. On solving QoS-aware service selection problem with service composition. In Proceedings of the 7th Internatinal Conference on Grid and Cooperative Computing. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Wang, J., Zhou, M., and Zhou, H. 2004. Providing network monitoring service for Grid computing. In Proceedings of the 10th IEEE International Workshop on Future Trends of Distributed Computing Systems. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Yang, K., Wu, Y., and Chen, H.-H. 2007. Qos-aware routing in emerging heterogeneous wireless networks. IEEE Comm. Mag. 45, 2, 74--80. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Yildirim, E., Suslu, I. H., and Kosar, T. 2008. Which network measurement tool is right for you? A multidimensional comparison study. In Proceedings of the 9th IEEE/ACM International Conference on Grid Computing. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Yousaf, M. and Welzl, M. 2005. A reliable network measurement and prediction architecture for Grid scheduling. In Proceedings of the IEEE/IFIP Workshop on Autonomic Grid Networking and Management.Google ScholarGoogle Scholar
  34. Yu, T. and Lin, K.-J. 2004. The design of QoS broker algorithms for QoS-capable Web services. Int. J. Web Serv. Res. 1, 4, 33--50.Google ScholarGoogle ScholarCross RefCross Ref
  35. Yu, T. and Lin, K.-J. 2005. Service selection algorithm for Web services with end-to-end QoS constraints. J. Inf. Syst. E-Bus. Manag. 3, 2.Google ScholarGoogle Scholar
  36. Zhao, D., Yu, Q., and Li, W. 2007. Service description based on CW for pervasive service discovery. In Proceedings of the 4th International Conference on Fuzzy Logic and Knowledge Discovery. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Network Service Description and Discovery for High-Performance Ubiquitous and Pervasive Grids

        Recommendations

        Reviews

        Harekrishna Misra

        The premise for grid computing is resource sharing with the intensive use of Internet protocols. The architecture for grid computing has leveraged the benefits of various evolutionary architectures, including client-service and distributed architectures. The basic purpose of this architecture is to use the inherent strengths of networks, the Internet, databases, and storage, and to provide better services. The benefit of grid architecture is the extension of services with optimized cost and without compromising security and quality of service (QoS). This paper discusses network service descriptions and discovery for high-performance grids across heterogeneous networks. It is an interesting paper that presents a model to describe service capabilities and service discovery technology for selecting network and resource allocation schemes. This model, therefore, is contemporary in terms of offering approaches and solutions for providing enhanced QoS with flexibility. The author supports the developed model with algorithms, and examines two cases to validate the results obtained through the application of this model. There is scope for improvement, however, in establishing certain claims. Pervasiveness and ubiquitous features of a networked environment are quite instrumental in enhancing QoS. In this model, the author does not comprehensively present these two features. First of all, the paper could have included two separate sections to discuss pervasive and ubiquitous features of networks with the support of literature and algorithms. Through the cases discussed, the author could have validated deliveries of the model involving these features. With regard to the cases, the author does not discuss whether the simulations were done in an intranet environment. A comparative assessment of the results obtained through the application of Internet bandwidth with multiple service providers and the intranet environment in a campus network could have provided better insights. Benchmarking the results could have supported the findings more succinctly. Still, this paper is quite current and will benefit researchers who are interested in this evolving area. Online Computing Reviews Service

        Access critical reviews of Computing literature here

        Become a reviewer for Computing Reviews.

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in

        Full Access

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader
        About Cookies On This Site

        We use cookies to ensure that we give you the best experience on our website.

        Learn more

        Got it!