BibTeX:

@article{IJIRSTV1I7063,
     title={A survey on Improving performance of Real Time Scheduling for Cloud Systems},
     author={Rekha A Kulkarni and Dr. Suhas H Patil},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={7},
     pages={171--173},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I7063.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Cloud computing provides a distributed computing environment in which there is a pool of virtual, dynamically scale-able heterogeneous computing and storage platforms. The computing power and the storage are provided as Services on demand to external user over the internet. Cloud computing aims at making computing as a service whereby shared resources, software, and information are provided to users who are requesting the service as a utility over a network. One of the key technology which plays an important role in Cloud data-center is resource scheduling. Real time processing on the cloud systems requires to satisfy timing constraints of real time systems. In the scenario of time dependent application deadline misses are undesirable. One of the challenging scheduling problems in Cloud data center is to consider allocation and migration of re-configurable virtual machines (VMs) and integrating features of hosting physical machines. While using the facilities provided by cloud environment in the area of real time processing the challenge is that of meeting the deadlines. A real-time scheduler must ensure that processes meet deadlines, regardless of system load or inherent delays caused by the various components of the cloud environment. One solution to this is by selecting the scheduling policy at run time. In this paper the various Real time scheduling algorithms have performance of real time scheduling policies in cloud system with the dynamic selection of scheduling algorithms with the help of fuzzy logic.

Cloud Computing, Real Time Scheduling , Fuzzy Logic, Performance, Multi Core