Simulation, verification and automated composition of web services
Proceedings of the 11th international conference on World Wide Web
Damia: a data mashup fabric for intranet applications
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Wishful search: interactive composition of data mashups
Proceedings of the 17th international conference on World Wide Web
SPADE: the system s declarative stream processing engine
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
A tag-based approach for the design and composition of information processing applications
Proceedings of the 23rd ACM SIGPLAN conference on Object-oriented programming systems languages and applications
SODA: an optimizing scheduler for large-scale stream-based distributed computer systems
Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware
Toward an integrative software infrastructure for water management in the smarter planet
IBM Journal of Research and Development
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Flow-based applications extract data from one or more sources, process them using one or more components, and finally produce useful results for end-users. One of the challenges in many organizations is that the components may be available on multiple legacy and new platforms, that may use different models for information processing and exchange. In this paper, we present MARIO, a middleware that supports the assembly and deployment of information processing flows that can potentially span multiple platforms. The middleware uses a generic application model, where each component is associated with platform-independent assembly and platform-specific deployment information. This enables the assembly of multi-platform flows, while hiding the details of the platforms from the assembly process. During deployment, a multi-platform flow is broken into one or more single-platform sub-flows. MARIO handles the deployment of the sub-flows in each platform, as well as the instantiation of bridging components that enable communication across different platforms. We describe our experiences in using our middleware in a real-world case study.