A hybrid approach for scheduling applications in cloud computing environment

Cloud computing plays an important role in our daily life. It has direct and positive impact on share and update data, knowledge, storage and scientific resources between various regions. Cloud computing performance heavily based on job scheduling algorithms that are utilized for queue waiting in modern scientific applications. The researchers are considered cloud computing a popular platform for new enforcements. These scheduling algorithms help in design efficient queue lists in cloud as well as they play vital role in reducing waiting for processing time in cloud computing. A novel job scheduling is proposed in this paper to enhance performance of cloud computing and reduce delay time in queue waiting for jobs. The proposed algorithm tries to avoid some significant challenges that throttle from developing applications of cloud computing. However, a smart scheduling technique is proposed in our paper to improve performance processing in cloud applications. Our experimental result of the proposed job scheduling algorithm shows that the proposed schemes possess outstanding enhancing rates with a reduction in waiting time for jobs in queue list

A Novel Decentralized Fuzzy Based Approach for Grid Job

In this paper with the aid of fuzzy theory we present a new method for scheduling on Grid system. Grid computing is a technology to meet the growing computational requires. In fact grid computing is one of the most popular types of distributed system. Its aim is to produce an enormous, autonomous and effective virtual machine, and it is produced by collecting different nodes with the aim of sharing their data and computational power. This paper follows the identification of grid scheduling with the help of fuzzy theory and seeking to present a new method for grid scheduling with respect to exiting obstacles. In our method we use the intermediate load of nodes of each clusters, the average of computing power which determines the node premiership and job premiership as the input parameters of fuzzy system, and regarding to the output value of fuzzy system the suitable nodes determines. We evaluate the performance of our method with some grid scheduling methods. The results of the experiments show the efficiency of the proposed method in term of makespan and Standard deviation of the load of cluster