Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item A game theoretic approach to a self managing MOOC based distributed system(Institute of Electrical and Electronics Engineers Inc., 2014) Sharath, N.; Parikh, S.S.; Chandrasekaran, K.The need to introduce an e learning platform in a campus such as ours is significant. In order to cater to the needs of nearly 7000 active users within the campus, a distributed system that is formulated. This system is required to to be as efficient as possible. This paper gives a topology for the system that is required and introduces self-managing properties that will add to the increased performance of the system in terms of speed, accuracy and security. With the aid of software agents continuously monitoring the progress of the entities in the system, we are able to introduce several self managing properties that govern the performance of the system as a whole. The software agents are modeled to be rational thinkers since every entity has a motive of performing its best. A game is simulated between two non cooperative agents as a case study and it is shown that the decision to move towards Nash Equilibrium serves better than any other random strategy. © 2014 IEEE.Item Information risk analysis in a distributed mooc based software system using an optimized artificial neural network(Association for Computing Machinery acmhelp@acm.org, 2015) Sharath, N.; Parikh, S.S.; Chandrasekaran, K.Information security is of utmost importance to any organization. With the increasing number of attacks on private data, understanding the risk involved with handling and maintaining it is relevant. Although there are various methods to determine the risk associated with a certain organization's data, there is also a need to speed up the process of computation of this risk. This paper discusses the usage of Artificial Neural Networks that bodes well for the non linear nature of the threat vectors that affect risk involved in setting up a distributed MOOC based software system. An optimization to the existing methods is proposed that makes use of the bio inspired, Cuckoo Search Algorithm. With the concept of Levy Flights and Random Walks, this algorithm produces a much faster rate of convergence in calculation of the importance to be given to each threat vector in assessing the security of the software system. © 2015 ACM.