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Books > Computing & IT > Computer communications & networking
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Grid Economics and Business Models - 6th International Workshop, GECON 2009, Delft, The Netherlands, August 24, 2009, Proceedings (Paperback, 2009 ed.)
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Grid Economics and Business Models - 6th International Workshop, GECON 2009, Delft, The Netherlands, August 24, 2009, Proceedings (Paperback, 2009 ed.)
Series: Computer Communication Networks and Telecommunications, 5745
Expected to ship within 10 - 15 working days
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GECON - Grid Economics and Business Models Cloud computing is seen
by many people as the natural evolution of Grid computing concepts.
Both, for instance, rely on the use of service-based approaches for
pro- sioning compute and data resources. The importance of
understanding business m- els and the economics of distributed
computing systems and services has generally remained unchanged in
the move to Cloud computing. This understanding is nec- sary in
order to build sustainable e-infrastructure and businesses around
this paradigm of sharing Cloud services. Currently, only a handful
of companies have created s- cessful businesses around Cloud
services. Among these, Amazon and Salesforce (with their offerings
of Elastic Compute Cloud and force. com among other offerings) are
the most prominent. Both companies understand how to charge for
their services and how to enable commercial transactions on them.
However, whether a wide-spread adoption of Cloud services will
occur has to seen. One key enabler remains the ability to support
suitable business models and charging schemes that appeal to users
o- sourcing (part of) their internal business functions. The topics
that have been addressed by the authors of accepted papers reflect
the above-described situation and the need for a better
understanding of Grid economics. The topics range from market
mechanisms for trading computing resources, capacity planning,
tools for modeling economic aspects of service-oriented systems,
archit- tures for handling service level agreements, to models for
economically efficient resource allocation.
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