Journal Article

Workflow scheduling and optimization using evaluationary method and deep learning algorithm in cloud

Murugan, A., Lalitha, S. P.

2024

Overview

Cloud environment is used for its high efficient utilization of bandwidth and its high processing speed. In 5G mobile communication environment, most of users sends and receives more number of highly occupied multimedia information. Hence, It is important to handle such cloud environment with minimal bandwidth and maximize speed. Therefore, it is mandatory to have proper schedule for processing of multimedia videos over the cloud environment. In this paper, Workflow Scheduling and Optimization Algorithm (WSOA) using deep learning model is proposed for the processing of multimedia video. The frames in each multimedia video are separated and processed individually. The Gabor transform is applied on each spatial frame to convert them into time–frequency frame. From this time–frequency frame, various frame parameters and features such as Local Binary Pattern (LBP), Local Ternary Pattern (LTP) and statistical features are computed to form the feature set. This feature set is scrutinized using Evolutionary Approach as Genetic Algorithm (GA) and the final optimized feature set is classified by the proposed Convolutional Neural Networks (CNN) architecture which produces the priority results.

• Publisher: Springer US,Springer Nature B.V
• Subject: 5G mobile communication / Algorithms / Artificial neural networks / Bandwidths / Computer Communication Networks / Computer Science / Data Structures and Information Theory / Deep learning / Evolutionary algorithms / Gabor transformation / Genetic algorithms / Machine learning / Multimedia / Multimedia Information Systems / Optimization / Scheduling / Special Purpose and Application-Based Systems / Time-frequency analysis / Workflow