A CYBER RESILIENT HYBRID META-HEURISTIC UNDER DIGITAL PERSONAL DATA PROTECTION UNDER ACT 2023 FOR DYNAMIC LOAD BALANCING MANAGEMENT AND FAULT-TOLERANT SCHEDULING IN MULTI-CLOUD SYSTEMS
TL;DR
A novel approach of secure and fault tolerant hybrid scheduling framework by combining COATI Optimization Algorithm (COATI) and Ant Colony Optimization (ACO) is presented, called Fault-Tolerant Cooperative COATI-ACO (FT-COACO).
Abstract
The problem of efficient task scheduling and load balancing in the multi-cloud system is quite difficult because of variable work load, heterogeneity of VMs and security attacks on cloud system. In this paper, a novel approach of secure and fault tolerant hybrid scheduling framework by combining COATI Optimization Algorithm (COATI) and Ant Colony Optimization (ACO) is presented. The developed algorithm called Fault-Tolerant Cooperative COATI-ACO (FT-COACO) uses COATI for the global search and ACO for optimal local search to better map tasks to VMs. The system uses the concepts of trust aware scheduling, anomaly detection and isolate malicious VMs to provide secure and reliable environment. This framework is evaluated in the multi cloud environment with different virtual machine specification, task sensitivities in the presence and absence of an attack. From the experimentation result for different number of 100 to 500 cloudlets, it is clear that there are improvement over Round Robin such as 15.41% of decrease in make span, 5.56% of decrease in execution cost, 18.14% of increase in throughput and 15.53% of increase in resource utilization, additionally it improved the success rate of task to 0.08% more and score of resilience is found to be 1.0028, showing effective fault tolerant and secure system for cloud.