A web service-based multi-disciplinary collaborative simulation platform for complicated product development

In a ubiquitous computing environment, computer-aided engineering (CAE) software packages can be encapsulated as a service and be accessible through networks, which is essential to small and medium enterprises (SMEs) for complex product design with limited computing resources. In this paper, a web service-based platform for the multi-disciplinary collaborative simulation (MDCSS) is proposed, which is a software-sharing environment. In MDCSS, although the CAE software packages reside in their remote application program servers, they are registered in the service center to be accessible according to the computing requests. Given the increasing CAE services with the same function, a quality of service (QoS)-aware scheduling method with real-time and countable parameters is proposed to adaptively select the most efficient web service among alternatives. Through an additional layer and an application broker for service scheduling, MDCSS allows allocating services automatically, keeping load balance, and minimizing human intervention. This platform is reusable, scalable, and efficient for implementation, which enables the end user to invoke the remote CAE software ubiquitously in a “pay-as-you-use” fashion.

[1]  Hsien-Chie Cheng,et al.  A web-based distributed problem-solving environment for engineering applications , 2006, Adv. Eng. Softw..

[2]  C. V. Ramamoorthy,et al.  Knowledge and Data Engineering , 1989, IEEE Trans. Knowl. Data Eng..

[3]  Jianwen Su,et al.  Web service discovery based on behavior signatures , 2005, 2005 IEEE International Conference on Services Computing (SCC'05) Vol-1.

[4]  I-Ling Yen,et al.  QoS-Driven Service Composition with Reconfigurable Services , 2013, IEEE Transactions on Services Computing.

[5]  Woongsup Kim,et al.  WSCPC: An architecture using semantic web services for collaborative product commerce , 2006, Comput. Ind..

[6]  Bensheng Yun.  A New Framework for Web Service Discovery Based on Behavior , 2010, 2010 IEEE Asia-Pacific Services Computing Conference.

[7]  David Ruiz,et al.  Improving semantic web services discovery using SPARQL-based repository filtering , 2012, J. Web Semant..

[8]  Shuping Ran,et al.  A model for web services discovery with QoS , 2003, SECO.

[9]  Paul A. Fishwick.  Web-based simulation: some personal observations , 1996, Winter Simulation Conference.

[10]  Brahim Medjahed,et al.  A Query Rewriting Approach for Web Service Composition , 2010, IEEE Transactions on Services Computing.

[11]  Yue-Shan Chang,et al.  A relaxable service selection algorithm for QoS-based web service composition , 2011, Inf. Softw. Technol..

[12]  Maria Luisa Villani,et al.  A framework for QoS-aware binding and re-binding of composite web services , 2008, J. Syst. Softw..

[13]  Chuan-Jun Su,et al.  Enabling successful Collaboration 2.0: A REST-based Web Service and Web 2.0 technology oriented information platform for collaborative product development , 2012, Comput. Ind..

[14]  Liang Chen,et al.  Selecting skyline services for QoS-aware composition by upgrading MapReduce paradigm , 2012, Cluster Computing.

[15]  Dimitris Plexousakis,et al.  Mixed-Integer Programming for QoS-Based Web Service Matchmaking , 2009, IEEE Transactions on Services Computing.

[16]  Wenbin Wang,et al.  An improved Particle Swarm Optimization Algorithm for QoS-aware Web Service Selection in Service Oriented Communication , 2010, Int. J. Comput. Intell. Syst..

[17]  A. Senthil Kumar,et al.  Development of a distributed collaborative design framework within peer-to-peer environment , 2008, Comput. Aided Des..

[18]  Xiuting Wei,et al.  Special section: CSCWD2006 web service-oriented manufacturing resource applications for networked product development , 2008, Adv. Eng. Informatics.

[19]  Ray Y. Zhong,et al.  Establishing production service system and information collaboration platform for mold and die products , 2011 .

[20]  Yanchun Zhang,et al.  Web services discovery and rank: An information retrieval approach , 2010, Future Gener. Comput. Syst..

[21]  Hidekazu Tsuji,et al.  A new QoS ontology and its QoS-based ranking algorithm for Web services , 2009, Simul. Model. Pract. Theory.

[22]  Anne H. H. Ngu,et al.  QoS computation and policing in dynamic web service selection , 2004, WWW Alt. '04.

[23]  Georgios Meditskos,et al.  Structural and Role-Oriented Web Service Discovery with Taxonomies in OWL-S , 2010, IEEE Transactions on Knowledge and Data Engineering.

[24]  Hui Xiong,et al.  Semantics-Based Automated Service Discovery , 2012, IEEE Transactions on Services Computing.

[25]  Emiliano Casalicchio,et al.  Static and dynamic scheduling algorithms for scalable Web server farm , 2001, Proceedings Ninth Euromicro Workshop on Parallel and Distributed Processing.

[26]  Andreas Tolk,et al.  Using Web Services to Integrate Heterogeneous Simulations in a Grid Environment , 2004, International Conference on Conceptual Structures.

[27]  Mike P. Papazoglou,et al.  Service oriented architectures: approaches, technologies and research issues , 2007, The VLDB Journal.

[28]  Hyeon Soo Kim,et al.  An e-Engineering Framework Based on Service-Oriented Architecture and Agent Technologies , 2007, 2007 11th International Conference on Computer Supported Cooperative Work in Design.

[29]  Andrea Zisman,et al.  Discovering Services during Service-Based System Design Using UML , 2010, IEEE Transactions on Software Engineering.

[30]  Lei Ren,et al.  A methodology towards virtualisation-based high performance simulation platform supporting multidisciplinary design of complex products , 2012, Enterp. Inf. Syst..

[31]  Filip De Turck,et al.  SALSA: QoS-aware load balancing for autonomous service brokering , 2010, J. Syst. Softw..

[32]  Yu Zhuang,et al.  A remote CAE collaborative design system for complex product based on design resource unit , 2011 .

[33]  Timothy W. Finin,et al.  Automating Cloud Services Life Cycle through Semantic Technologies , 2014, IEEE Transactions on Services Computing.

[34]  Tao Yu,et al.  Efficient algorithms for Web services selection with end-to-end QoS constraints , 2007, TWEB.

[35]  Christos Makris,et al.  Efficient and adaptive discovery techniques of Web Services handling large data sets , 2006, J. Syst. Softw..

[36]  Shiwei Tang,et al.  Web Service Composition Using Markov Decision Processes , 2005, WAIM.

[37]  Nitel Muhtaroglu,et al.  Design and implementation of a cloud computing service for finite element analysis , 2013, Adv. Eng. Softw..