Computation and Storage in the Cloud is the first comprehensive
and systematic work investigating the issue of computation and
storage trade-off in the cloud in order to reduce the overall
application cost. Scientific applications are usually computation
and data intensive, where complex computation tasks take a long
time for execution and the generated datasets are often terabytes
or petabytes in size. Storing valuable generated application
datasets can save their regeneration cost when they are reused, not
to mention the waiting time caused by regeneration. However, the
large size of the scientific datasets is a big challenge for their
storage. By proposing innovative concepts, theorems and algorithms,
this book will help bring the cost down dramatically for both cloud
users and service providers to run computation and data intensive
scientific applications in the cloud. Covers cost models and
benchmarking that explain the necessary tradeoffs for both cloud
providers and usersDescribes several novel strategies for storing
application datasets in the cloudIncludes real-world case studies
of scientific research applications
Covers cost models and benchmarking that explain the necessary
tradeoffs for both cloud providers and users
Describes several novel strategies for storing application
datasets in the cloud
Includes real-world case studies of scientific research
applications
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