FogWorkflowSim

A Toolkit for Modeling and Simulation of workflow scheduling in Internet of Things, Edge and Fog Computing Environments

Developer

• Developer organization:

1. School of Information Technology, Deakin University, Geelong, Australia
2. CCIS laboratory, School of Computer Science and Technology, Anhui University, Hefei, China

• Developer member: Xiao Liu, Xuejun Li, Lingmin Fan, Lina Gong, Jia Xu.

FogWorkflowSim User Tutorial

Access from https://github.com/CCIS-AHU/FogWorkflowSim/tree/master/usertutorial

IMPORTANT

Please check the improv branch for latest changes. Master branch has been left intact until complete testing.

How to run FogWorkflowSim ?

• Create a Java project in Eclipse.
• Inside the project directory, initialize an empty Git repository with the following command

git init

• Add the Git repository of FogWorkflowSim as the origin remote.

git remote add origin https://github.com/CCIS_AHU/FogWorkflowSim

• Pull the contents of the repository to your machine.

git pull origin master

• Run the example files (e.g. MainUI.java) to get started.

References

1. S.C. Li, L.D. Xu and S.S. Zhao, "5G Internet of Things: A Survey," J. Industrial Information Integration, vol. 10, no. 1, pp. 1-9, Jun. 2018.
2. Y.B. Li, M. Chen, W.Y. Dai and M.K. Qiu, "Energy Optimization with Dynamic Task Scheduling Mobile Cloud Computing," J. IEEE Systems Journal, vol. 11, no. 1, pp. 96-105, Jun. 2017.
3. M. Chiang, S. Ha, C. I, F. Risso and T. Zhang, "Clarifying Fog Computing and Networking: 10 Questions and Answers," J. IEEE Communications Magazine, vol. 55, no. 4, pp. 18-20, Apr. 2017.
4. G.H.S. Carvalho, I. Woungang, A. Anpalagan, M. Jaseemuddin and E. Hossain, "Intercloud and HetNet for Mobile Cloud Computing in 5G Systems: Design Issues, Challenges, and Optimization," J. IEEE Network, vol. 31, no. 3, pp. 80-89, May 2017.
5. P.F. Hu, S. Dhelim, H.S. Ning and T. Qiu, "Survey on Fog Computing: Architecture, Key Technologies, Applications and Open Issues," J. Journal of Network and Computer Applications, vol. 98, no. 11, pp. 27-42, Nov. 2017.
6. A. Ouaddah, H. Mousannif, A.A. Elkalam and A.A. Ouahman, "Access Control in the Internet of Things: Big Challenges and New Opportunities," J. Computer Networks, vol. 112, no. 1, pp. 237-262, Jan. 2017.
7. C. Perera, Y.R. Qin, J.C. Estrella, S. Reiff-Marganiec and A.V. Vasilakos, "Fog Computing for Sustainable Smart Cities: A Survey," J. ACM Computing Surveys, vol. 50, no. 3, pp. 1-43, Oct. 2017.
8. T. Chen, Q. Ling, Y.N. Shen and G.B. Giannakis, "Heterogeneous Online Learning for “Thing-Adaptive” Fog Computing in IoT," J. IEEE Internet of Things Journal, preprint, 26 Jul. 2018, doi:10.1109/JIOT.2018.2860281.
9. M. Chiang, S. Ha, C. I, F. Risso and T. Zhang, "Fog Computing and Networking: Part 1 [Guest Editorial]," J. IEEE Communications Magazine, vol. 55, no. 4, pp. 16-17, Apr. 2017.
10. Y. Ku, D. Lin, C. Lee, P. Hsieh, H. Wei, C. Chou and A. Pang, "5G Radio Access Network Design with the Fog Paradigm: Confluence of Communications and Computing," J. IEEE Communications Magazine, vol. 55, no. 4, pp. 46-52, Apr. 2017.
11. C. Mouradian, D. Naboulsi, S. Yangui, R.H. Glitho, M.J. Morrow and P.A. Polakos, "A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges," J. IEEE Communications Surveys & Tutorials, vol. 20, no. 1, pp. 416-464, Nov. 2017.
12. A.A. Mutlag, M.K.A. Ghani, N. Arunkumar, M.A. Mohammed and O. Mohd, "Enabling Technologies for Fog Computing in Healthcare IoT Systems," J. Future Generation Computer Systems, vol. 90, no. 1, pp. 62-78, Jan. 2019.
13. H.Q. Zhang, Y.R. Zhang, Y.N. Gu, D. Niyato and Z. Han, "A Hierarchical Game Framework for Resource Management in Fog Computing," J. IEEE Communications Magazine, vol. 55, no. 8, pp. 52-57, Aug. 2017.
14. N. Iotti, M. Picone, S. Cirani and G. Ferrari, "Improving Quality of Experience in Future Wireless Access Networks Through Fog Computing," J. IEEE Internet Computing, vol. 2017, no. 2, pp. 26-33, Mar. 2017.
15. M. Aazam, S. Zeadally and K.A. Harras, "Offloading in Fog Computing for IoT: Review, Enabling Technologies, and Research Opportunities," J. Future Generation Computer Systems, vol. 87, no. 10, pp. 278-289, Oct. 2018.
16. M. Mukherjee, L. Shu and D. Wang, "Survey of Fog Computing: Fundamental, Network Applications, and Research Challenges," J. IEEE Communications Surveys & Tutorials, vol. 20, no. 3, pp. 1826-1857, Mar. 2018.
17. M. Aazam, S. Zeadally and K.A. Harras, "Fog Computing Architecture, Evaluation, and Future Research Directions," J. IEEE Communications Magazine, vol. 56, no. 5, pp. 46-52, May 2018.
18. L.Q. Liu, Z. Chang, X.J. Guo, S.W. Mao and T. Ristaniemi, "Multiobjective Optimization for Computation Offloading in Fog Computing," J. IEEE Internet of Things Journal, vol. 5, no. 1, pp. 283-294, Dec. 2018.
19. J.B. Du, L.Q. Zhao, J. Feng and X.L. Chu, "Computation Offloading and Resource Allocation in Mixed Fog/Cloud Computing Systems with Min-Max Fairness Guarantee," IEEE Trans. Communications, vol. 66, no. 4, pp. 1594-1608, Dec. 2018, doi:10.1109/TCOMM.2017.2787700.
20. C.M. Wang, C.C. Liang, F.R. Yu, Q.B. Chen and L. Tang, "Computation Offloading and Resource Allocation in Wireless Cellular Networks with Mobile Edge Computing," IEEE Trans. Wireless Communications, vol. 16, no. 8, pp. 4924-4938, May 2017, doi:10.1109/TWC.2017.2703901.
21. C.S. You, K.B. Huang, H. Chae and B. Kim, "Energy-Efficient Resource Allocation for Mobile-Edge Computation Offloading," IEEE Trans. Wireless Communications, vol. 16, no. 3, pp. 1397-1411, Dec. 2017, doi:10.1109/TWC.2016.2633522.
22. H. Yim, D. Seo, H. Jung, M. Back, I. Kim and K. Lee, "Description and Classification for Facilitating Interoperability of Heterogeneous Data/Events/Services in the Internet of Things," J. Neurocomputing, vol. 256, no. 9, pp. 13-22, Sep. 2017.
23. F. Marozzo, D. Talia and P. Trunfio, "A Workflow Management System for Scalable Data Mining on Clouds," IEEE Trans. Services Computing, vol. 11, no. 3, pp. 480-492, Jul. 2018, doi:10.1109/TSC.2016.2589243.
24. R.N. Calheiros, R. Ranjan, A. Beloglazov, C.A.F.D. Rose and R. Buyya, "CloudSim: a Toolkit for Modeling and Simulation of Cloud Computing Environments and Evaluation of Resource Provisioning Algorithms," J. Software: Practice and experience, vol. 41, no. 1, pp. 23-50, Aug. 2011.
25. H. Gupta, A.V. Dastjerdi, S.K. Ghosh and R. Buyya, "iFogSim: A Toolkit for Modeling and Simulation of Resource Management Techniques in the Internet of Things, Edge and Fog computing environments," J. Software: Practice and Experience, vol. 47, no. 9, pp. 1275-1296, Jun. 2017.
26. J. Yan, Y. Yang and G.K. Raikundalia, "Towards incompletely specified process support in swindew–a peer-to-peer based workflow system," Proc. International Conf on Computer Supported Cooperative Work in Design, pp. 328-338, May 2004, doi:10.1007/11568421_33.
27. D. Cao, X. Liu and Y. Yang, "Novel client-cloud architecture for scalable instance-intensive workflow systems," Proc. International Conf. on Web Information Systems Engineering, pp. 270-284, Oct. 2013, doi:10.1007/978-3-642-41154-0_20.
28. W.W. Chen and E. Deelman, "WorkflowSim: A Toolkit for Simulating Scientific Workflows in Distributed Environments," Proc. IEEE International Conf. on E-science, pp. 1-8, Jan. 2012, doi:10.1109/eScience.2012.6404430.
29. C. Sonmez, A. Ozgovde and C. Ersoy, "Edgecloudsim: An Environment for Performance Evaluation of Edge Computing Systems," IEEE Trans. Emerging Telecommunications Technologies, vol. 29, no. 11, pp. 1-17, Aug. 2018, doi:10.1002/ett.3493.
30. G. Juve. "WorkflowGenerator," Pegasus, https://confluence.pegasus.isi.edu/display/pegasus/WorkflowGenerator.html. 2018.
31. P. Mach and Z. Becvar, "Mobile Edge Computing: A Survey on Architecture and Computation Offloading," J. IEEE Communications Surveys & Tutorials, vol. 19, no. 3, pp. 1628-1656, Mar. 2017.
32. B.G. Batista, N.B. Morais, B.T. Kuehne, R.M.D. Frinhani, D.M.L. Filho and M.L.M. Peixoto, "Heuristic Performance Evaluation for Load Balancing in Cloud," Proc. IEEE International Conf. on High Performance Computing & Simulation, pp. 593-600, Nov. 2018, doi:10.1109/HPCS.2018.00099.
33. L. Chen, S.H. Liu, B.C. Li and B. Li, "Scheduling Jobs Across Geo-Distributed Datacenters with Max-Min Fairness," IEEE Trans. Network Science and Engineering, preprint, 25 Jan. 2018, doi:10.1109/TNSE.2018.2795580.
34. A.B.M.B. Alam, M. Zulkernine and A. Haque, "A Reliability-Based Resource Allocation Approach for Cloud Computing," Proc. IEEE seventh International Symposium on Cloud and Service Computing, pp. 249-252, Mar. 2017, doi:10.1109/SC2.2017.46.
35. H.H. Yang, Y. Wang and T.Q.S. Quek, "Response Analysis of Random Scheduling and Round Robin in Small Cell Networks," J. IEEE Wireless Communications Letters, vol. 7, no. 6, pp. 978-981, Jun. 2018.
36. A. Verma and S. Kaushal, "A Hybrid Multi-Objective Particle Swarm Optimization for Scientific Workflow Scheduling," J. Parallel Computing, vol. 62, no. 6, pp. 1-19, Jun. 2017.
37. N. Netjinda, B. Sirinaovakul and T. Achalakul, "Cost Optimal Scheduling in IaaS for Dependent Workload with Particle Swarm Optimization," J. The Journal of Supercomputing, vol. 68, no. 3, pp. 1579-1603, Jun. 2014.
38. H. Hallawi, J. Mehnen and H.M. He, "Multi-Capacity Combinatorial Ordering GA in Application to Cloud Resources Allocation and Efficient Virtual Machines Consolidation," J. Future Generation Computer Systems, vol. 69, no. 4, pp. 1-10, Apr. 2017.
39. S.W. Cao, X.F. Tao, Y.Z. Hou and Q.M. Cui, "An Energy-Optimal Offloading Algorithm of Mobile Computing based on HetNets," Proc. IEEE International Conf. on Connected Vehicles and Expo, pp. 254-258, Apr. 2015.