Abstract
CPU Scheduling is the process of allocating CPU time to various processes of different kinds. There are many existing algorithms that schedule waiting processes, but each of those algorithms achieve good results in only one of the many useful features of a scheduler. Some important features of a scheduling algorithm are to reduce the waiting time, to give a fair share of CPU time to all the processes and to give preference to higher priority processes; Shortest Job First, Round Robin and Priority scheduling algorithms do them respectively. The proposed work combines all these desired properties into one algorithm, by making use of convolution neural network architecture. Using CNN architecture is advantageous because the data is controllable in the hidden layers. The data in the hidden layers could be both understood and manipulated; hence a more powerful neural network could be designed. In comparison to these common algorithms the proposed work achieves 66% better performance, when all the above mentioned desired properties are taken into consideration.
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Chennur, B.G., Shastry, N., Monish, S., Hegde, V.V., Agarwal, P., Arya, A. (2023). Optimal Scheduling of Processing Unit Using Convolutional Neural Network Architecture. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 544. Springer, Cham. https://doi.org/10.1007/978-3-031-16075-2_33
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