S
Schahram Dustdar
Researcher at Vienna University of Technology
Publications - 919
Citations - 32707
Schahram Dustdar is an academic researcher from Vienna University of Technology. The author has contributed to research in topics: Cloud computing & Web service. The author has an hindex of 70, co-authored 804 publications receiving 28237 citations. Previous affiliations of Schahram Dustdar include London School of Economics and Political Science & Danske Bank.
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Social-Network-Sourced Big Data Analytics
TL;DR: Leveraging the social network paradigm could enable a level of collaboration to help solve big data processing challenges and use personal ad hoc clouds comprising individuals in social networks to address such challenges.
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A service computing manifesto: the next 10 years
Athman Bouguettaya,Munindar P. Singh,Michael N. Huhns,Quan Z. Sheng,Hai Dong,Qi Yu,Azadeh Ghari Neiat,Sajib Mistry,Boualem Benatallah,Brahim Medjahed,Mourad Ouzzani,Fabio Casati,Xumin Liu,Hongbing Wang,Dimitrios Georgakopoulos,Liang Chen,Surya Nepal,Zaki Malik,Abdelkarim Erradi,Yan Wang,Brian Blake,Schahram Dustdar,Frank Leymann,Mike P. Papazoglou +23 more
TL;DR: Mapping out the challenges and strategies for the widespread adoption of service computing shows clear trends in adoption and a clear road map for the future direction is proposed.
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The view-based approach to dynamic inter-organizational workflow cooperation
TL;DR: The approach allows for partial visibility of workflows and their resources, thus providing powerful ways for inter-organizational workflow configuration, and provides workflow participants with the freedom to change their work-flows without changing their roles in the cooperation.
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A survey on self-healing systems: approaches and systems
Harald Psaier,Schahram Dustdar +1 more
TL;DR: This survey identifies self-healing systems’ fundamental principles based on the principles of autonomic computing and self-adapting system research and summarizes the approaches’ common and individual characteristics.
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Principles of Elastic Processes
TL;DR: In this article, the authors introduce elastic processes, which are based on explicitly modeling resources, cost, and quality, and show how they improve on the state-of-the-art.