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|Title:||COST BASED JOB SCHEDULING IN FOG COMPUTING|
|Abstract:||Fog Computing is coming up as a big revolution in the field of distributed computing by making available the resources and services nearer to the edge devices. It acts as an intermediary layer between the client and cloud server and aims at reducing the load on the cloud servers by dealing with the client’s requests nearer to the edge devices. It has proven to be successful in solving latency issues of high priority and sensitive tasks by processing and analyzing the data rapidly and efficiently. The main issue is not data rather how to manage, store, access and utilize this data so as to ensure efficient and quick responsive overall system. This is where fog computing comes into action. The main objective of fog computing is to make the same system more competent by reducing the interaction with the cloud server for data storage and retrieval. In order to achieve this goal, in fog computing, data is tried and kept closer to the end user. Fog Servers (FS) are set nearer to the edge devices. These servers are equipped with the capability to store, process and analyze data. The client, instead of sending his request all the way to the centralized Cloud Server (CS) now sends it to its nearest fog server thus reducing the overall computation time and latency. For fog computing to work successfully, it is important to deal with the problem of Job Scheduling. In my work I have proposed a dynamic Job Scheduling algorithm that will aim at maintaining the cost factor as minimum as possible, along with completing the task within the given deadline. The results of the proposed algorithm are compared with some of the famous Job Scheduling algorithms and results are represented graphically.|
|Appears in Collections:||M.E./M.Tech. Computer Engineering|
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|Cost Based Job Scheduling Thesis.pdf||1.4 MB||Adobe PDF||View/Open|
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