Issues and challenges of scheduling and protection algorithms for proficient parallel data processing in cloud

In topical years one of the Cloud Services, Infrastructure-as-a-Service (IaaS) provides a compute resources for demand in various applications like Parallel Data Processing. Major Cloud computing companies have started to integrate frameworks for, making it easy for customers to access these services and to deploy their programs. However, the processing frameworks which are currently used have been designed for static, identical cluster setups and ignore the particular nature of a cloud. Consequently, the allocated compute resources may be insufficient for big parts of the submitted job and unnecessarily increase processing time and cost. However, the current algorithm does not consider the schedule and security during the job execution. In this paper we have focused on the issues and challenges of the scheduling & protection algorithm for proficient parallel data processing in real time cloud computing services. Our Algorithm contains all the concrete information required to schedule and execute the received job on the cloud. Each Execution is by default assigned to its own Execution Instance. The code is lightweight and portable; it makes a great random number generator for both Encryption and Decryption is designed to run data processing on a large number of jobs, and provide a high efficacy in real time cloud services.