Fog computing is latest addition in the environment of cloud computing which mainly brings cloud resources closer to the client. The main aim of fog computing is to execute the small tasks of smart devices at the edge devices whereas to put away the main intensive and non-sensitive tasks for the remote execution on the cloud. This overcomes the drawback that the cloud had due to the centralised control and problems of executing the small sensitive task at the remote area. In this paper, we provide the algorithm based on the three parameters time, energy consumption, and network usage on the basis of that, scheduling of task can take place between the two, cloud as well as fog, which distributes the load between them. The results we get, show that there is a significant decrease in time approximately 40%, network usage with 40% and significant decrease in energy consumption also on running tasks on fog than cloud . Finally, we assess the achievement of the task through the experimental simulation which shows significant decrease in the parameter values for local tasks at the fog computing.

Cloud computing, Fog computing, Internet of things,Task scheduling

[1] T.Kleiner, “ Internet of Things – From Research and Innovation to Market Deployment”,River Publishers, pp. 355,2014.
[2] M. Ketel, “Fog-Cloud Services for IoT”, In the Proceedings of the 2017 SouthEast Conference on ACM SE, USA, pp.262-264, 2017.
[3] M.Kaur, A.M.Aslam, “Big Data Analytics on IoT:Challenges,Open Research Issues and Tools”, Isroset-Journal (IJSRCSE), Vol.6, No.3, pp. 81–85, 2018.
[4] W. Ramirez, X. M. Bruin, E.M. Tordera, B.B.C. Souza, and A.jukan, “Evaluating the benefits of combined and continuous Fog-to-Cloud architectures”, Computer Communication, Vol.113, pp.43-52, 2017.
[5] M.Patinder, P.Bansal, “Cloud Forensics:An Overall Research Perspective”, IJSRNSC journal, Vol.6, No.2, pp.5-10,2018.
[6] Q. Zhu, B. Si, F. Yang, Y. Ma, “Task offloading decision in fog computing system”, China Communicatins, Vol.14, Issue.11, pp.59-68, 2017.
[7] B. Paharia, K. Bhushan, “Fog Computing as a defensive approach against Distributed Denial of Service (DDoS): a proposed architecture”, 9th International Conference on Computer Communication and Network Technology, India, pp.1-7, 2018.
[8] R. Mahmud, K. Ramamohanarao, R. Buyya, “Latency-Aware Application Module Management for Fog Computing Environments”, ACM Transanction on Internet Technology, Vol.19, No.1, pp.1–21, 2018.
[9] I. Takouna, R. Rojas-Cessa, K. Sachs, and C. Meinel, “Communication-aware and energy-efficient scheduling for parallel applications in virtualized data centers”, In the Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility Cloud Computing UCC, Germany, pp.251–255, 2013.
[10] M.Q. Tran, D.T. Nguyen, V.A. Le, D.H. Nguyen T.V. Pham, “Task Placement on Fog Computing Made Efficient for IoT Application Provision”, Wireless Communication and Mobile Computing, Vol. 2019, pp.1–1, 2019.
[11] M. Taneja, A. Davy, “Resource aware placement of IoT application modules in Fog-Cloud Computing Paradigm”, In the Proceedings of the 2017 IFIP/IEEE Symposium on Integrated Netwwotk and Service Management, Portugal pp.1222–1228, 2017.