Trading Storage for Computation: An Analysis of the Process and its Integration with Cloud Computing

School of Computing & Mathematics
ITC571
Emerging Technologies &
Innovation
Research
Seminar Presentation
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School of Computing & Mathematics
Introduction
Trading storage for computation is referred to the process
in which empty storage space is utilized for increasing the
efficiency of computation of numerical calculations.
In this system, the storage space is saved by removing
the results of the calculations and instead, the inputs,
outputs, processes and data are saved.
This system is mainly useful for the systems that use
small volumes of input data but generate huge volumes of
data that is only for temporary use and will not be used or
accessed later.

School of Computing & Mathematics
Literature Review
According to Joshi, Liu and Soljanin (2014), the
combination of cloud computing and tradeoff
storage has been benefitting trans coding in real
life scenario as well as video layer encoding and
decoding.
The authors based their work on wireless
technologies like WCDMA and LTE and set out to
evaluate the requirements for implementing trade
off technology for efficient and effective
computation purposes.

School of Computing & Mathematics
Literature Review
As per McEvoy and Correll (2015), the trading storage for computing
process has been significantly benefitted by the integration with
cloud computing because cloud computing is an easily accessible
technology with very less complexity.
They have reported that the cloud computing holistic view is essentially
useful for selecting the specific results that is to be stored for future
accessibility and removing every other results that will lose
relevance after some time.