Adaptive rate stream processing for smart grid applications on clouds
Proceedings of the 2nd international workshop on Scientific cloud computing
Dynamic workflow adaptation over adaptive infrastructures
KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
End-to-End QoS on Shared Clouds for Highly Dynamic, Large-Scale Sensing Data Streams
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Revenue-Based resource management on shared clouds for heterogenous bursty data streams
GECON'12 Proceedings of the 9th international conference on Economics of Grids, Clouds, Systems, and Services
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Scientific workflows are commonplace in eScience applications. Yet, the lack of integrated support for data models, including streaming data, structured collections and files, is limiting the ability of workflows to support emerging applications in energy informatics that are stream oriented. This is compounded by the absence of Cloud data services that support reliable and performant streams. In this paper, we propose and present a scientific workflow framework that supports streams as first-class data, and is optimized for performant and reliable execution across desktop and Cloud platforms. The workflow framework features and its empirical evaluation on a private Eucalyptus cloud are presented.