الفهرس 
Chapter 1: IntroductionOnly 14 pages are availabe for public view
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Abstract
Fog computing is currently one of the most cutting-edge technologies available. It has
been used in a variety of industries, including healthcare and smart grids, because it
brings resources closer to the end users and can be synchronised with cloud computing
in the future. As a result, it is trusted because it allows a big load of requests to access
information quickly.
As a result, it was imperative to utilise this fog technology in the field of education,
particularly e-learning, which has grown to be a hallmark of the modern era.
Additionally, since the burden of supporting an increased number of students across all
study fields fell heavily on cloud computing, it was necessary to establish fog nodes in
education sector as an expand to cloud computing. due to the fact that it avoids latency,
improves performance and response times to user queries, is decentralised, and is
heavily reliant on the location of its users.
In this thesis, an e-learning model based on fog technology will be proposed, as it brings
learning resources more closure to learners in order to overcome the latency and slow
response resulting from the large number of users who access the educational
environment.
As well as in the field of e-learning, there are traditional quizzes, which depend mainly
on multiple choice, as it is not possible to use images or videos quizzes because they
represent a burden on cloud computing. Therefore, a new type of smart quizzing was
proposed in this thesis that allows measuring student capabilities by answering with
drawing. Then match the saved answers during the correction process.
Since fog computing represents the main interface for dealing with users, it is necessary
to protect this environment with a high encryption type to protect the privacy of users
of the e-learning system, as well as to protect the infrastructure of the educational
system. Therefore, it was proposed to apply a highly efficient encryption system that
can secure the educational environment appropriately to maintain privacy.
Finally, it is gratifying that the proposals of this thesis have the opportunity to present
the model in best way that enables the use of fog computing in the field of e-learning.