ENHANCING CLOUD TASK SCHEDULING WITH A ROBUST SECURITY APPROACH AND OPTIMIZED HYBRID POA

Project Code :TCMAPY1278

Objective

The objective of this research is to develop and evaluate a novel task scheduling approach for cloud computing environments that integrates the Polymorphic Advanced Encryption Standard (P-AES) to enhance both scheduling efficiency and security. The primary goals are to: 1) optimize task scheduling by effectively distributing tasks across available resources while considering factors such as network bandwidth, make span, and cost, and 2) incorporate P-AES to secure the scheduling process against potential vulnerabilities. By achieving these objectives, the research aims to improve overall performance and security in cloud computing, providing a comprehensive solution for effective task management.

Abstract

Cloud computing (CC) provides dynamic and scalable resources essential for optimizing task scheduling (TS) to boost performance. Effective TS in CC involves allocating tasks across available resources while considering network bandwidth, make span, and cost. This research presents a novel method for optimizing TS in cloud environments by employing the Polymorphic Advanced Encryption Standard (P-AES) algorithm to improve security during scheduling. The study assesses the performance of the proposed algorithm using various metrics. By integrating P-AES, the approach ensures a secure and efficient scheduling process, offering a fresh perspective on task management in cloud computing. This method contributes to enhancing cloud services by merging improved performance with robust security measures.

Index Terms: Polymorphic Advanced Encryption Standard, cloud computing, security, task scheduling.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W CONFIGURATION:

Processor                                 - I3/Intel Processor

Hard Disk                                - 160GB

Key Board                              - Standard Windows Keyboard

Mouse                                     - Two or Three Button Mouse

Monitor                                   - SVGA

RAM                                       - 8GB

S/W CONFIGURATION:

β€’      Operating System                   :  Windows 7/8/10

β€’      Server side Script                    :  HTML, CSS, Bootstrap & JS

β€’      Programming Language         :  Python

β€’      Libraries                                  :  Flask or Django, Pandas, Mysql.connector, Os, Smtplib, Numpy

β€’      IDE/Workbench                      :  PyCharm

β€’      Technology                             :  Python 3.6+

β€’      Server Deployment                 :  Xampp Server

Demo Video