Providing an Effective Heuristic Algorithm to Improve the Scheduling Jobs in Cloud Environment

Cloud computing is a hardware and software infrastructure that provides affordable, reliable, comprehensive, and affordable access to computing abilities of others. Cloud computing has emerged as a new approach to solving large-scale problems in the fields of science, engineering, and commerce. A cloud computing is associated with a set of resources on a large scale. Computational clouds have emerged as a new approach to solving large-scale problems in the fields of science, engineering, and commerce. Cloud computing is a hardware and software infrastructure that provides affordable, reliable, comprehensive, and affordable access to computing abilities of others. A cloud computing is associated with a set of resources on a large scale. The algorithms provided so far have improved the problem of scheduling and managing resources in cloud computing in a direction and the structure and form of this problem have not yet been resolved. Each of these solutions provides hypotheses and eliminates issues from the cloud timing definition, such as cost, quality of service, architectures, and others, but ultimately improves on it and schedules In cloud computing, it has been pushed forward in some ways. The purpose of this thesis is to provide a method that optimizes resource management and cloud scheduling in at least one direction. The main focus of the research is on the time criterion, the deadline for doing things and receiving the response from the cloud parameters can be examined. From a more general perspective, the aim of the research is to get the answer as quickly as possible from cloud computing. Always the execution time of an algorithm is one of the challenges for that algorithm. By comparing the implementation time of the proposed algorithm and the Min-min algorithm, we conclude that the operating time of the Min-min algorithm is three times the proposed execution time of the algorithm. We were able to provide a new algorithm for this scheduling, while its total completion time was as high as the current Heuristic algorithm examined, but the execution time is 66% better than that.

کلیدواژه ها:

Heuristic Algorithm ، Improved Jobs Scheduling ، Cloud Environments ، System Status