Fault tolerant prediction and scheduling in cloud computing using optimization algorithms

Abstract

In cloud computing (CC), resources are allocated and offered to the clients transparently in an on-demand way. Failures can happen in CC environment and the cloud resources are adaptable to fluctuations in the performance delivery. Task execution failure becomes common in the CC environment. Therefore, fault-tolerant scheduling techniques in CC environment are essential for handling performance differences, resource fluxes, and failures. Recently, several intelligent scheduling approaches have been developed for scheduling tasks in CC with no consideration of fault tolerant characteristics. Recently, the count of intelligent scheduling approaches is utilized for addressing task scheduling problems from the cloud without much attention to fault tolerance. Larger the system, the further failure can possible to take place that eventually outcomes in the worse reliability of method that is extremely undesirable for the time-critical application. To manage the reliability, service providers can identify the failure features of CC nodes for optimum handling of the failure, utilizing fault-tolerance-aware approaches at the time of scheduling the application tasks. newlineWith the advent of dramatic growth in the computing industry, the role of cloud based system that consist of a very huge proposition of computing nodes which is capable of offering numerous services in live environment. In spite of the nature of nodes which is wired and wireless chances of falling into failure is more. The failure of nodes will lead to interruption and destruction of services which can be called as service down time. Here arises the question about the Cloud Service Provider (CSP) in terms of Quality of Service (QoS), which is a major headache for the Cloud Service Vendors. In order to overcome newline newline