User-participatory fog computing architecture and its management schemes for improving feasibility

IEEE Access

Volumn 6, Issue , 2018, Pages 20262-20278

  Kim, Won Suk ^a   Chung, Sang Hwa ^a  

^a Pusan National University   (South Korea)

Author keywords

Fog computing; Internet of Things; Optimization; Software defined networking

Indexed keywords

CLOUD COMPUTING; COMPUTER ARCHITECTURE; DISTRIBUTED COMPUTER SYSTEMS; FIRMWARE; FOG; INTEGER PROGRAMMING; INTERNET OF THINGS; NETWORK ARCHITECTURE; NONLINEAR PROGRAMMING; OPTIMIZATION; SOFTWARE DEFINED NETWORKING;

COMPUTING ARCHITECTURE; INTERNET OF THING (IOT); MIXED INTEGER NON-LINEAR PROGRAMMING PROBLEMS; NETWORKING TECHNOLOGY; PLACEMENT OPTIMIZATION; PROPOSED ARCHITECTURES; RESOURCE ALLOCATION PROBLEM; SERVICE PLACEMENTS;

FOG COMPUTING;

EID: 85044055102     PISSN: None     EISSN: 21693536     Source Type: Journal    
DOI: 10.1109/ACCESS.2018.2815629     Document Type: Article

References (37)

1. B. Ahlgren, C. Dannewitz, C. Imbrenda, D. Kutscher, and B. Ohlman, "A survey of information-centric networking," IEEE Commun. Mag., vol. 50, no. 7, pp. 26-36, Jul. 2012.
2. N. McKeown et al., "OpenFlow: Enabling innovation in campus networks," ACM SIGCOMM Comput. Commun. Rev., vol. 38, no. 2, pp. 69-74, Apr. 2008.
3. B. Wang, Z. Qi, R. Ma, H. Guan, and A. V. Vasilakos, "A survey on data center networking for cloud computing," Comput. Netw., vol. 91, pp. 528-547, Nov. 2015.
4. Q. Zhang, L. Cheng, and R. Boutaba, "Cloud computing: State-of-the-art and research challenges," J. Internet Services Appl., vol. 1, no. 1, pp. 7-18, May 2010.
5. L. Wang et al., "Cloud computing: A perspective study," New Generat. Comput., vol. 28, no. 2, pp. 137-146, 2010.
6. S. Khanagha, H. Volberda, and I. Oshri, "Business model renewal and ambidexterity: Structural alteration and strategy formation process during transition to a cloud business model," R&D Manage., vol. 44, no. 3, pp. 322-340, Jun. 2014.
7. K. Ha, Z. Chen, W. Hu, W. Richter, P. Pillai, and M. Satyanarayanan, "Towards wearable cognitive assistance," in Proc. ACM MobiSys, 2014, pp. 68-81.
8. V. Scuotto, A. Ferraris, and S. Bresciani, "Internet of Things: Applications and challenges in smart cities: A case study of IBM smart city projects," Bus. Process Manage. J., vol. 22, no. 2, pp. 357-367, 2016.
9. Y. Shi, G. Ding, H. Wang, H. E. Roman, and S. Lu, "The fog computing service for healthcare," in Proc. 2nd Int. Symp. Future Inf. Commun. Technol. Ubiquitous Healthcare (Ubi-Healthcare), May 2015, pp. 1-5.
10. C. L. P. Chen and C.-Y. Zhang, "Data-intensive applications, challenges, techniques and technologies: A survey on big data," Inf. Sci., vol. 275, pp. 314-347, Aug. 2014.
11. A. Fahad et al., "A survey of clustering algorithms for big data: Taxonomy and empirical analysis," IEEE Trans. Emerg. Topics Comput., vol. 2, no. 3, pp. 267-279, Sep. 2014.
12. R. Deng, R. Lu, C. Lai, T. H. Luan, and H. Liang, "Optimal workload allocation in fog-cloud computing toward balanced delay and power consumption," IEEE Internet Things J., vol. 3, no. 6, pp. 1171-1181, Dec. 2016.
13. L. M. Vaquero and L. Rodero-Merino, "Finding your way in the fog: Towards a comprehensive de-nition of fog computing," ACM SIGCOMM Comput. Commun. Rev., vol. 44, no. 5, pp. 27-32, Oct. 2014.
14. F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, "Fog computing and its role in the Internet of Things," in Proc. ACM MCC, 2012, pp. 13-15.
15. What is Docker. Accessed: May 10, 2017. [Online]. Available: Https://www.docker.com/what-docker
16. T. H. Luan, L. Gao, Z. Li, Y. Xiang, G.Wei, and L. Sun. (Mar. 2016). "Fog computing: Focusing on mobile users at the edge." [Online]. Available: Https://arxiv.org/abs/1502.01815
17. S. Yi, Z. Hao, Z. Qin, and Q. Li, "Fog computing: Platform and applications," in Proc. 3rd IEEE Workshop Hot Topics Web Syst. Technol. (HotWeb), Nov. 2015, pp. 73-78.
18. T. N. Gia, M. Jiang, A.-M. Rahmani, T. Westerlund, P. Liljeberg, and H. Tenhunen, "Fog computing in healthcare Internet of Things: A case study on ECG feature extraction," in Proc. IEEE CIT, Oct. 2015, pp. 356-363.
19. S. Yan, M. Peng, and W. Wang, "User access mode selection in fog computing based radio access networks," in Proc. IEEE ICC, May 2016, pp. 1-6.
20. M. Peng, S. Yan, K. Zhang, and C. Wang, "Fog-computing-based radio access networks: Issues and challenges," IEEE Netw., vol. 30, no. 4, pp. 46-53, Jul. 2016.
21. H. Dubey, J. Yang, N. Constant, A. M. Amiri, Q. Yang, and K. Makodiya, "Fog data: Enhancing telehealth big data through fog computing," in Proc. ASE BD&SI, Oct. 2015, pp. 1-6.
22. T. Nishio, R. Shinkuma, T. Takahashi, and N. B. Mandayam, "Serviceoriented heterogeneous resource sharing for optimizing service latency in mobile cloud," in Proc. ACM MobileCloud, Jul. 2013, pp. 19-26.
23. K. Hong, D. Lillethun, U. Ramachandran, B. Ottenwälder, and B. Koldehofe, "Mobile fog: A programming model for large-scale applications on the Internet of Things," in Proc. ACM MCC, Aug. 2013, pp. 15-20.
24. H. R. Arkian, A. Diyanat, and A. Pourkhalili, "MIST: Fog-based data analytics scheme with cost-ef-cient resource provisioning for IoT crowdsensing applications," J. Netw. Comput. Appl., vol. 82, pp. 152-165, Mar. 2017.
25. S. Sarkar, S. Chatterjee, and S. Misra, "Assessment of the suitability of fog computing in the context of Internet of Things," IEEE Trans. Cloud Comput., vol. 6, no. 1, pp. 46-59, Jan./Mar. 2018.
26. C. T. Do, N. H. Tran, C. Pham, M. G. R. Alam, J. H. Son, and C. S. Hong, "A proximal algorithm for joint resource allocation and minimizing carbon footprint in geo-distributed fog computing," in Proc. IEEE ICOIN, Jan. 2015, pp. 324-329.
27. B. Tang, Z. Chen, G. Hefferman, T. Wei, H. He, and Q. Yang, "A hierarchical distributed fog computing architecture for big data analysis in smart cities," in Proc. ASE BD&SI, Oct. 2015, pp. 1-6.
28. N. K. Giang, M. Blackstock, R. Lea, and V. C. M. Leung, "Developing IoT applications in the fog: A distributed data-ow approach," in Proc. IEEE IOT, Oct. 2015, pp. 155-162.
29. M. Aazam and E.-N. Huh, "Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT," in Proc. IEEE AINA, Mar. 2015, pp. 687-694.
30. M. Aazam and E.-N. Huh, "Fog computing and smart gateway based communication for cloud of things," in Proc. IEEE FiCloud, Aug. 2014, pp. 464-470.
31. S. Yi, C. Li, and Q. Li, "A survey of fog computing: Concepts, applications and issues," in Proc. ACM Mobidata, Jun. 2015, pp. 37-42.
32. Y. Xu, V. Mahendran, and S. Radhakrishnan, "SDN docker: Enabling application auto-docking/undocking in edge switch," in Proc. IEEE SWFAN, Apr. 2016, pp. 1-6.
33. A. Lewis, S. Ghosh, and N.-F. Tzeng, "Run-time energy consumption estimation based on workload in server systems," in Proc. USENIX HotPower, Dec. 2008, pp. 1-5.
34. M. R. Garey and D. S. Johnson, Computers and Intractability; A Guide to the Theory of NP-Completeness. New York, NY, USA: Freeman, 1979, pp. 245-248.
35. P. Mahadevan, P. Sharma, S. Banerjee, and P. Ranganathan, "A power benchmarking framework for network devices," in Proc. Networking, May 2009, pp. 795-808.
36. D. Meisner, B. T. Gold, and T. F.Wenisch, "PowerNap: Eliminating server idle power," in Proc. ACM ASPLOS, Mar. 2009, pp. 205-216.
37. R. Morabito, "Power consumption of virtualization technologies: An empirical investigation," in Proc. IEEE/ACM UCC, Dec. 2015, pp. 522-527.