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4
Adaptive Execution of Scientific
Workflow A
pplications on Clouds
Rodrigo N. Calheiros, Henry Kasim, Terence Hung, Xiaorong Li, Sifei Lu,
Long Wang, Henry Palit, Gary Lee, Tuan Ngo, and Rajkumar Buyya
CONTENTS
Summary ................................................................................................................ 73
4.1 Introduction .................................................................................................. 74
4.2 Workflow Applications ............................................................................... 75
4.3 Requirements for Adaptive Execution of Workflows on Clouds .......... 76
4.4 Case Study .................................................................................................... 79
4.5 System Architecture .................................................................................... 83
4.6 Discussion and Lessons Learned .............................................................. 84
4.7 Related Work ................................................................................................ 85
4.8 Conclusions and Future Work ................................................................... 86
References ............................................................................................................... 87
Summary
Many e-science applications can be modeled as workflow applications. In this
programming model, scientific applications are described as a set of tasks
that have dependencies between them. Clouds are natural candidates for
hosting such applications. This is because some of their core characteristics,
such as rapid elasticity, resource pooling, and pay per use, are well suited to
the nature of scientific applications that experience variable demand, spikes
in resource (i.e., of the central processing unit [CPU] or disk) utilization, and
sometimes, urgency for generation of results. As current workflow manage-
ment systems (WfMSs) cannot support efficient and automated execution of
workflow in clouds that support adaptive execution, fault tolerance, and data
privacy, in this chapter we detail the requirements of a WfMS that supports
these requirements, its architecture, and an application scenario involving
simulation of Singapore's public transport system.
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