Synchronization analysis for decentralizing composite Web services

Web Services are emerging as the standard mechanism for making information and software available programmatically via the Internet, and as building blocks for applications. A composite web service may be built using multiple component web services. Once its specification has been developed, the composite service may be orchestrated either using a centralized engine or in a decentralized fashion. Decentralized orchestration improves scalability and concurrency. Dynamic binding coupled with decentralized orchestration adds high availability and fault tolerance to the system. In this paper, we categorize different forms of concurrency and provide an algorithm to identify these forms in a composite service specification. We also consider the impact of dynamic binding and faults on synchronization constructs.

[1]  Franco Zambonelli,et al.  Coordination middleware for XML-centric applications , 2002, SAC '02.

[2]  Vijayalakshmi Atluri,et al.  A Chinese wall security model for decentralized workflow systems , 2001, CCS '01.

[3]  Thomas R. Gross,et al.  Decoupling synchronization and data transfer in message passing systems of parallel computers , 1995, ICS '95.

[4]  V. Sarkar,et al.  Automatic partitioning of a program dependence graph into parallel tasks , 1991, IBM J. Res. Dev..

[5]  Eric A. Brewer,et al.  Cluster-based scalable network services , 1997, SOSP.

[6]  Karl J. Ottenstein,et al.  The program dependence graph in a software development environment , 1984 .

[7]  Kwang-Hoon Kim,et al.  Workflow performance and scalability analysis using the layered queuing modeling methodology , 2001, GROUP '01.

[8]  Alfred V. Aho,et al.  Compilers: Principles, Techniques, and Tools , 1986, Addison-Wesley series in computer science / World student series edition.

[9]  Peter Scheuermann,et al.  Selection algorithms for replicated Web servers , 1998, PERV.

[10]  Willy Zwaenepoel,et al.  Scalable Content-aware Request Distribution in Cluster-based Network Servers , 2000, USENIX ATC, General Track.

[11]  David E. Culler,et al.  Scalable, distributed data structures for internet service construction , 2000, OSDI.

[12]  Jason Nieh,et al.  Virtual-Time Round-Robin: An O(1) Proportional Share Scheduler , 2001, USENIX Annual Technical Conference, General Track.

[13]  Anand R. Tripathi,et al.  Distributed Collaborations Using Network Mobile Agents , 2000, ASA/MA.

[14]  Franco Zambonelli,et al.  Mobile-Agent Coordination Models for Internet Applications , 2000, Computer.

[15]  Nenad Medvidovic,et al.  Towards a taxonomy of software connectors , 2000, Proceedings of the 2000 International Conference on Software Engineering. ICSE 2000 the New Millennium.

[16]  Erich M. Nahum,et al.  Locality-aware request distribution in cluster-based network servers , 1998, ASPLOS VIII.

[17]  Amin Vahdat,et al.  The costs and limits of availability for replicated services , 2001, TOCS.