A Novel Technique for Job Scheduling Algorithm in Real- Time Virtual Cloud Environment

In real-time scenario, job allocation for individuals is the most important process of scheduling work. The cloud environment is enhancing rapidly and the consumers requests for better services and good results are also increasing. Meanwhile, there are some immense issues that are associated with job scheduling such as response time, deadline exception, and scalability. To overcome these problems, this research work proposed three enhanced real-time scheduling algorithms namely, Unfair Semi Greedy (USG), Earliest Dead-line First (EDF), and Earliest Dead-line until Zero Laxity (EDZL). This study enhances the previous research using real-time scheduling algorithm and resolving the scalability issues. With the addition of resource table, records of working virtual machines (VM's) updating simultaneously and as a result the response time of jobs has improved a lot, and a clear decrease in the average deadline exception can be observed. When the resource table updated dynamically, the efficiency of scheduling work is also improved. In the USG Algorithm, deadline-exception is found to be at minimum level. The EDZL and USG produce the least response-time, but the deadline-exception is found in increasing numbers in some cases.