Virtualizing Software and Humans for Elastic Processes in Multiple Clouds- a Service Management Perspective
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Abstract
There is a growing trend of combining human-based computation with machine-based com- putation to solve complex problems which cannot be answered with machine-based computation alone. From the computing perspective, integrating machine-based computing elements with human-based computing elements and provisioning them under the same model will facilitate the resource elasticity required by complex applications. Although certain works investigate tech- niques for integrating human-based computing elements with machine-based computing elements, existing computing models for such integrated computing systems are very limited. In fact, the ar- chitectures, interconnections, non-functional parameters of human-based computing elements are very different from that of contemporary machine-based counterparts. Human-based computing elements are built based on social and bio concepts, thus their architectures, interconnects and non- functional parameters are extremely complex and dynamic, compared with that of machine-based computing elements. In this paper, we examine fundamental issues in virtualizing human-based computing elements and machine-based computing elements using service-oriented computing concepts in order to create highly scalable computing systems of hybrid services to support the elasticity of software and people in complex applications. We will outline our Vienna Elastic Com- puting Model which aims at introducing techniques and frameworks to support multi-dimensional elastic processes atop hybrid cloud systems of software-based and human-based services. This paper will analyze several service management issues in order to support the virtualization of machine-based and human-based computing elements to support such elastic processes.
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How to Cite
Dustdar, S. ., & Truong, H.-L. (2012). Virtualizing Software and Humans for Elastic Processes in Multiple Clouds- a Service Management Perspective. International Journal of Next-Generation Computing, 3(2), 109–126. https://doi.org/10.47164/ijngc.v3i2.29
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