Performance evaluation of traditional and heuristic scheduling with renaissance system model in cloud computing

Abstract

Cloud Computing is a computing utility, which enables the sharing of services over the internet. Cloud is a new large group of interconnected computers, which stores information and run application. Cloud computing is a shared group of configurable computing resources, on-demand network access provided by the service provider. The main objective of cloud computing is data sharing. Since all users can share the data that have been stored in the cloud there is a possibility of breaking information. To prevent the information leakage, cloud security is used. Cloud security is an approach of protecting the data in the cloud computing environment. The scheduling of a task workflow in a distributed computing platform is a well-known Non-deterministic Polynomial (NP)-hard problem. The problem is more complex and challenging when the virtualized clusters are used to execute a large number of tasks in a cloud computing platform. Therefore, many heuristics have been proposed from low level execution of tasks in multiple processors to high level execution of tasks. In this research, the max-min algorithm , min-min algorithm, Invasive Weed Optimization (IWO) algorithm and Genetic Algorithm (GA) based scheduling are newlineevaluated. The max-min algorithm is used in distributed environment which newlinebegins with a set of unscheduled tasks and then the expected execution matrix newlineand expected completion time of each task on the available resources are calculated. The min-min algorithm is simple and is still a basis of present cloud scheduling algorithm. newline newline