CALL FOR PAPERS
Workshop on Data Intensive Services based Application
In conjunction with
The 29th International Conference on Software Engineering and Knowledge Engineering (SEKE2017)
Service-oriented architecture (SOA) is a widely accepted and engaged paradigm for the realization of business processes that incorporate several distributed, loosely coupled partners. Today, Web services and the Business Process Execution Language for Web Services (BPEL4WS, BPEL for short) are the established technologies to implement such a service-oriented architecture. The functionality provided by business applications is enclosed within Web service software components. Those Web services can be invoked by application programs or by other Web services via Internet without explicitly binding them. On top of that, BPEL has been established as the de-facto standard for implementing business processes based on Web services.
Aside from business processes, the service-oriented approach using Web services and BPEL is also of great interest for the implementation of data-intensive processes such as, for example, those found in the area of data analytics. Over the recent years, data generated by humanities, scientific activities, as well as commercial applications from a diverse range of fields have been increasing exponentially. Data volumes of applications in the fields of sciences and engineering, finance, media, online information resources, etc. are expected to double every two years over the next decade and further. There is no doubt in the industry and research community that the importance of data intensive computing has been raising and will continue to be the foremost fields of research. As a result, the data intensive services based applications have become the most kind of application in SOA. Also, it has become a hot issue in the academia and industry. Potentially, this could have a significant impact on the on-going researches for services and data intensive computing.
Generally, we define the notion of a data-intensive services based application as a collection of related structured activities or tasks (services) that produce a specific result; huge data sets have to be exchanged between several loosely coupled services in such a data-intensive application. In this case, many new challenges are proposed, for example, the exchange of massive data. Although the preferred XML-based SOAP protocol can meet the communication between Web services, it is not efficient enough in those scenario settings. DISA2017 focuses on the challenges imposed by data-intensive services based applications, and on the different state-of-the-art solutions proposed to overcome these challenges. The aim of DISA2017 is to encourage academic researchers and industry practitioners to present and discuss all methods and technologies related to research and experiences in a broad spectrum of data-intensive services based applications.
The topics of the workshop include but not limited to:
Data intensive services representation
- Modeling of data intensive services
- Reference models for data intensive services
- Semantic models for data intensive services
- Logistics ontologies / ontologies for data intensive services
- Integrating data intensive services models with Web service models
- Repositories and dictionaries for data intensive services
- data intensive service data integration
Data intensive services based application building, management and coordination
- data intensive service design and engineering
- data intensive service composition, orchestration and choreography
- data intensive service runtime management and monitoring
- Services for managing decentralized data intensive services
- data intensive service quality aspects and their management
- Negotiation protocols for data intensive services
- Market-based coordination of data intensive services, i.e., auctions, exchanges
- Modeling, simulation and optimization of data intensive services
- Verification of data intensive services
- Transactional safeguarding of data intensive services
- Service-oriented architectures for the setup and enactment of data intensive services
- Mashups and data intensive services
- Agents for the lifecycle management of data intensive services
- Performance aspects of data intensive application
SLA Management
- Languages for describing SLAs for data intensive services along and across value chains
- Semantic annotation of SLA for data intensive services
- SLA negotiation for data intensive services
- SLA monitoring for data intensive services
- Integrating data intensive services into SLA management infrastructures
Case studies and demos
- Industry-specific case studies on service-oriented computing
- Innovative research prototypes and demonstrators
- Empirical research on service-oriented computing
Submission:
Papers must be written in English. An electronic version (Postscript, pdf, or MS Word format) of the full paper should be submitted to the Data Intensive Services based Application Track using the following URL: https://www.easychair.org/conferences/?conf=seke2017 (submission website will be open after January 1, 2017). Please use Internet Explorer as the browser. Manuscript must include a 200-word abstract and no more than 6 pages of 2-column formatted Manuscript for Conference Proceedings (include figures and references but exclude copyright form).
Organizer:
Dr. Honghao Gao,Shanghai University, China
Co-Organizers:
Prof. Ying Li, Zhejiang University, China
Prof. Yuyu Yin, Hangzhou Dianzi University, China
Workshop Program Committee (Tentative):
Abdelrahman Osman Elfaki, University of Tabuk, Saudi Arabia
Ajay Kattepur, Tata Consultancy Services, India
Alex Norta, Tallinn University of Technology, Estonia
Amit Dvir, Budapest University of Technology and Economics, Hungary
Antonella Longo, Univ. of Salento,Italy
Chengzhong Xu, Wayne State University, USA
Guoray Cai, Pennsylvania State University, USA
Honghao Gao, Shanghai University, China
Hong-Linh Truong, Vienna University of Technology, Austria
Huaikou Miao, Shanghai University, China
HuiYuan Zheng, Macquarie University, Australia
Jiangchuan Liu, Simon Fraser University, Canada
Jiannong Cao, Hong Kong Polytechnic University, HK
Jianwei Yin, Zhejiang University, China
JianWei Yin, Zhejiang University, China
Jianwen Su, University of California, USA
Jian Zhao, Institute for Infocomm Research, Singapore
Jia Zhang, Northern Illinois University, USA
JiLin Zhang, Hangzhou Dianzi University, China
Jingyu Zhang, University of Sydney, Australia
Joe Tekli, Lebanese American University (LAU),Lebanon
Jue Wang, Supercomputing Center of CAS, China
Klaus-Dieter Schewe, Information Science Research Centre, New Zealand
Kumiko Tadano, NEC, Japan
Lai Xu, Bournemouth University,UK
Lei Liu, Karlsruhe Institute of Technology, Germany
Li Kuang, Hangzhou Normal University, China
Limin Shen, Yanshan University, China
Marco Comerio, University of Milano-Bicocca,Italy
Nanjangud C Narendra, MS Ramaiah University of Applied Sciences, India
Nianjun Joe Zhou, IBM T. J. Watson Res. Center, USA
Peng Di, The University of New South Wales, Australia
Peng Di, University of New South Wales
Qiang Duan, Pennsylvania State University,USA
Qing Wu, Hangzhou Dianzi University, China
Robert Lagerstrom, KTH - Royal Institute of Technology, Sweden
Rong N, IBM Res.,USA
Shuiguang Deng, ZheJiang University, China
Stephan Reiff-Marganiec, University of Leicester, UK
Stephen Wang, Toshiba Telecommunications Research Laboratory Europe, UK
Wan Tang, South-Central University for Nationalities, China
Wei Wang, Institute of Communications and Navigation, German Aerospace Center, Germany
Xiaofei Zhang, Hong Kong University of Science and Technology, Hong Kong
XiaoFei Zhang, The Hong Kong University of Science & Technology, China
Yi Wang, Macquarie University, Australia
Yucong Duan, Hainan University, China
YuYu Yin, Hangzhou Dianzi University, China
Zhou Su, Waseda University, Japan
For Inquiries Please Contact:
Dr. Honghao Gao,Shanghai University, China
gaohonghao@shu.edu.cn