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Fog computing: from architecture to edge computing and big data processing

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Abstract

Cloud computing plays a vital role in processing a large amount of data. However, with the arrival of the Internet of Things, huge data are generated from these devices. Thus, there is the need for bringing characteristics of cloud closer to the request generator, so that processing of these huge data takes place at one-hop distance closer to that end user. This led to the emergence of fog computing with the aim to provide storage and computation at the edge of the network that reduces network traffic and overcomes many cloud computing drawbacks. Fog computing technology helps to overcome challenges of big data processing. The paper discusses the taxonomy of fog computing, how this is different from cloud computing and edge computing technologies, its applications, emerging key technologies (i.e., communication technologies and storage technologies) and various challenges involved in fog technology.

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References

  1. Enokido T, Doulikun D, Takizawa M (2017) An energy-aware load balancing algorithm to perform computation type application processes in a cluster of servers. Int J Web Grid Serv 13(2):145. https://doi.org/10.1504/IJWGS.2017.10004125. URL http://www.inderscience.com/link.php?id=10004125

  2. Liu Z, Li J, Wang Y, Li X, Chen S (2017) HGL: a hybrid global-local load balancing routing scheme for the Internet of Things through satellite networks. Int J Distrib Sens Netw 13(3):155014771769258. https://doi.org/10.1177/1550147717692586. URL http://journals.sagepub.com/doi/10.1177/1550147717692586

  3. Muck TR, Ghaderi Z, Dutt ND, Bozorgzadeh E (2017) Exploiting heterogeneity for aging-aware load balancing in mobile platforms. IEEE Trans Multiscale Comput Syst 3(1):25–35. https://doi.org/10.1109/TMSCS.2016.2627541. URL http://ieeexplore.ieee.org/document/7740903/

  4. Jiang F, Liu Y, Wang B, Wang X (2017) A relay-aided device-to-device-based load balancing scheme for multitier heterogeneous networks. IEEE Internet Things J 4(5):1537–1551. https://doi.org/10.1109/JIOT.2017.2677975. URL http://ieeexplore.ieee.org/document/7870597/

  5. Cisco Fog Computing Solutions: Unleash the Power of the Internet of Things (2015) URL https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-solutions.pdf

  6. Stojmenovic I, Wen S (2014) The fog computing paradigm: scenarios and security issues. In: 2014 Federated conference on computer science and information systems (FedCSIS), pp 1–8. https://doi.org/10.15439/2014F503. URL https://fedcsis.org/proceedings/2014/drp/503.html

  7. Rani S, Ahmed SH (2018) Secure edge computing: an architectural approach and industrial use case. Internet Technol Lett 1:e68

    Article  Google Scholar 

  8. Dastjerdi AV, Buyya R (2016) Fog computing: helping the internet of things realize its potential. Computer 49(8):112–116. https://doi.org/10.1109/MC.2016.245. URL http://ieeexplore.ieee.org/document/7543455/

  9. Deshmukh UA, More SA (2016) Fog computing: a new approach in the world of cloud computing. Instr Technol 49

  10. Gohar M, Ahmed SH, Khan M, Guizani N, Ahmed A, Rahman AU (2018) A big data analytics architecture for the internet of small things. IEEE Commun Mag 56(2):128–133

    Article  Google Scholar 

  11. Marn-Tordera E, Masip-Bruin X, Garca-Almiana J, Jukan A, Ren G-J, Zhu J (2017) Do we all really know what a fog node is? Current trends towards an open definition. Comput Commun 109:117–130. https://doi.org/10.1016/j.comcom.2017.05.013. URL http://linkinghub.elsevier.com/retrieve/pii/S0140366416307113

  12. Anawar MR, Wang S, Azam Zia M, Jadoon AK, Akram U, Raza S (2018) Fog computing: an overview of big Iot data analytics. Wireless Commun Mob Comput. https://doi.org/10.1155/2018/7157192

  13. Cisco estimation report. URL https://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/white-paper-c11-738085.html#_Toc503317525

  14. Hussain F, Alkarkhi A (2017) Big data and fog computing. In: Internet of Things, pp 27–44. https://doi.org/10.1007/978-3-319-55405-1_3

  15. Chiang M, Zhang T (2016) Fog and IoT: an overview of research opportunities. IEEE Internet Things J 3(6):854–864. https://doi.org/10.1109/JIOT.2016.2584538. URL http://ieeexplore.ieee.org/document/7498684/

  16. Kukreja P, Sharma DD (2016) A detail review on cloud. Fog Dew Comput 5(5):9

    Google Scholar 

  17. More P (2015) Review of implementing fog computing. Int J Res Eng Technol 4(06):335–338

    Article  Google Scholar 

  18. Rahmani A-M, Thanigaivelan NK, Gia TN, Granados J, Negash B, Liljeberg P, Tenhunen H (2015) Smart e-health gateway: bringing intelligence to Internet-of-Things based ubiquitous healthcare systems. In: IEEE, pp 826–834. https://doi.org/10.1109/CCNC.2015.7158084. URL http://ieeexplore.ieee.org/document/7158084/

  19. Aazam M, Huh E-N (2014) Fog computing and smart gateway based communication for Cloud of Things. In: IEEE, pp 464–470. https://doi.org/10.1109/FiCloud.2014.83. URL http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6984239

  20. Aazam M, Huh E-N (2015) Fog computing micro datacenter based dynamic resource estimation and pricing model for IoT. In: IEEE, pp 687–694. https://doi.org/10.1109/AINA.2015.254. URL http://ieeexplore.ieee.org/document/7098039/

  21. Gia TN, Jiang M, Rahmani A-M, Westerlund T, Liljeberg P, Tenhunen H (2015) Fog computing in healthcare Internet of Things: a case study on ECG feature extraction. In: IEEE, pp 356–363. https://doi.org/10.1109/CIT/IUCC/DASC/PICOM.2015.51. URL http://ieeexplore.ieee.org/document/7363093/

  22. ASE International Conference on Big Data (2015) Academy of Science and Engineering, Association for Computing Machinery. In: ASE international conference on social informatics, a hierarchical distributed fog computing architecture for big data analysis in smart cities, 00000 OCLC: 956994157. URL http://dl.acm.org/citation.cfm?id=2818869

  23. Bonomi F (2011) The smart and connected vehicle and the Internet of Things, enabling technologies. URL http://tf.nist.gov/seminars/WSTS/PDFs/1-0_Cisco_FBonomi_ConnectedVehicles.pdf

  24. Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things, ACM Press, p 13. https://doi.org/10.1145/2342509.2342513. URL http://dl.acm.org/citation.cfm?doid=2342509.2342513

  25. Bonomi F, Milito R, Natarajan P, Zhu J (2014) Fog computing: a platform for Internet of Things and analytics. In: Bessis N, Dobre C (eds) Big data and Internet of Things: a roadmap for smart environments, vol 546, Springer International Publishing, Cham, pp 169–186. https://doi.org/10.1007/978-3-319-05029-4_7. URL http://link.springer.com/10.1007/978-3-319-05029-4_7

  26. Gazis V, Leonardi A, Mathioudakis K, Sasloglou K, Kikiras P, Sudhaakar R (2015) Components of fog computing in an industrial Internet of Things context. In: IEEE, pp 1–6. https://doi.org/10.1109/SECONW.2015.7328144. URL http://ieeexplore.ieee.org/document/7328144/

  27. Abdullahi I, Arif S, Hassan S (2015) Ubiquitous shift with information centric network caching using fog computing. In: Phon-Amnuaisuk S, Au TW (eds) Computational intelligence in information systems, vol 331, Springer International Publishing, Cham, pp 327–335. https://doi.org/10.1007/978-3-319-13153-5_32. URL http://link.springer.com/10.1007/978-3-319-13153-5_32

  28. Skala K, Davidovic D, Afgan E, Sovic I, Sojat Z (2015) Scalable distributed computing hierarchy: cloud, fog and dew computing. Open J Cloud Comput (OJCC) 2(1):9–00063

    Google Scholar 

  29. Mahmud R, Kotagiri R, Buyya R (2018) Fog computing: a taxonomy, survey and future directions. In: Di Martino B, Li K-C, Yang LT, Esposito A (eds) Internet of everything, Springer, Singapore, pp 103–130. https://doi.org/10.1007/978-981-10-5861-5_5. URL http://link.springer.com/10.1007/978-981-10-5861-5_5

  30. Saharan KP, Kumar A (2015) Fog in comparison to cloud: a survey. Int J Comput Appl 122(3):10–12. https://doi.org/10.5120/21679-4773. URL http://research.ijcaonline.org/volume122/number3/pxc3904773.pdf

  31. Yi S, Li C, Li Q (2015) A survey of fog computing: concepts, applications and issues, ACM Press, pp 37–42. https://doi.org/10.1145/2757384.2757397. URL http://dl.acm.org/citation.cfm?doid=2757384.2757397

  32. Yi S, Hao Z, Qin Z, Li Q (2015) Fog computing: platform and applications. In: IEEE, pp 73–78. https://doi.org/10.1109/HotWeb.2015.22. URL http://ieeexplore.ieee.org/document/7372286/

  33. Razouk W, Sgandurra D, Sakurai K (2017) A new security middleware architecture based on fog computing and cloud to support IoT constrained devices, ACM Press, pp 1–8. https://doi.org/10.1145/3109761.3158413. URL http://dl.acm.org/citation.cfm?doid=3109761.3158413

  34. Alrawais A, Alhothaily A, Hu C, Cheng X (2017) Fog computing for the Internet of Things: security and privacy issues. IEEE Internet Comput 21(2):34–42. https://doi.org/10.1109/MIC.2017.37. URL http://ieeexplore.ieee.org/document/7867732/

  35. Roman R, Lopez J, Mambo M (2018) Mobile edge computing, Fog et al.: a survey and analysis of security threats and challenges. Future Gener Comput Syst 78:680–698. https://doi.org/10.1016/j.future.2016.11.009. URL https://linkinghub.elsevier.com/retrieve/pii/S0167739X16305635

  36. Zhao P, Tian H, Fan S, Paulraj A (2018) Information prediction and dynamic programming-based RAN slicing for mobile edge computing. IEEE Wirel Commun Lett 7(4):614–617. https://doi.org/10.1109/LWC.2018.2802522. URL https://ieeexplore.ieee.org/document/8281474/

  37. Krner M, Runge TM, Panda A, Ratnasamy S, Shenker S (2018) Open carrier interface: an open source edge computing framework. In: Proceedings of the 2018 workshop on networking for emerging applications and technologies—NEAT ’18, ACM Press, Budapest, Hungary, pp 27–32. https://doi.org/10.1145/3229574.3229579. URL http://dl.acm.org/citation.cfm?doid=3229574.3229579

  38. Syamkumar M, Barford P, Durairajan R (2018) Deployment characteristics of “The Edge” in mobile edge computing. In: Proceedings of the 2018 workshop on mobile edge communications—MECOMM’18, ACM Press, Budapest, Hungary, pp 43–49. https://doi.org/10.1145/3229556.3229557. URL http://dl.acm.org/citation.cfm?doid=3229556.3229557

  39. Yu W, Liang F, He X, Hatcher WG, Lu C, Lin J, Yang X (2018) A survey on the edge computing for the Internet of Things. In: IEEE access, vol 6, pp 6900–6919. https://doi.org/10.1109/ACCESS.2017.2778504. URL http://ieeexplore.ieee.org/document/8123913/

  40. Jeong S, Simeone O, Kang J (2018) Mobile edge computing via a UAV-mounted cloudlet: optimization of bit allocation and path planning. IEEE Trans Veh Technol 67(3):2049–2063. https://doi.org/10.1109/TVT.2017.2706308. URL http://ieeexplore.ieee.org/document/7932157/

  41. Rahmani AM, Gia TN, Negash B, Anzanpour A, Azimi I, Jiang M, Liljeberg P (2018) Exploiting smart e-health gateways at the edge of healthcare Internet-of-Things: a fog computing approach. Future Gener Comput Syst 78:641–658. https://doi.org/10.1016/j.future.2017.02.014. URL http://linkinghub.elsevier.com/retrieve/pii/S0167739X17302121

  42. Vora J, Tanwar S, Tyagi S, Kumar N, Rodrigues JJPC (2017) FAAL: fog computing-based patient monitoring system for ambient assisted living. In: IEEE, pp 1–6. https://doi.org/10.1109/HealthCom.2017.8210825. URL http://ieeexplore.ieee.org/document/8210825/

  43. Fakeeh KA (2016) Privacy and security problems in fog computing. Commun Appl Electron 4:7

    Google Scholar 

  44. Taneja M, Davy A (2016) Resource aware placement of data analytics platform in fog computing. Procedia Comput Sci 97:153–156. https://doi.org/10.1016/j.procs.2016.08.295. URL http://linkinghub.elsevier.com/retrieve/pii/S1877050916321111

  45. Singh S, Chana I (2015) QoS-aware autonomic resource management in cloud computing: a systematic review. ACM Comput Surv 48(3):1–46. https://doi.org/10.1145/2843889. URL http://dl.acm.org/citation.cfm?doid=2856149.2843889

  46. Souza VB, Masip-Bruin X, Marin-Tordera E, Ramirez W , Sanchez S (2016) Towards distributed service allocation in fog-to-cloud (F2c) scenarios. In: IEEE, pp 1–6. https://doi.org/10.1109/GLOCOM.2016.7842341. URL http://ieeexplore.ieee.org/document/7842341/

  47. Gupta M (2017) Fog computing pushing intelligence to the edge. Int J Sci Technol Eng 3(8):5

    Google Scholar 

  48. Zhao H, Li X (2013) Resource management in utility and cloud computing, SpringerBriefs in Computer Science, Springer New York, New York. https://doi.org/10.1007/978-1-4614-8970-2. URL http://link.springer.com/10.1007/978-1-4614-8970-2

  49. Kameda H, Li J, Kim C, Zhang Y (1997) Optimal load balancing in distributed computer systems, telecommunication networks and computer systems, Springer London. https://doi.org/10.1007/978-1-4471-0969-3. URL http://link.springer.com/10.1007/978-1-4471-0969-3

  50. Kopparapu C (2002) Load balancing servers, firewalls, and caches. Wiley, New York

    Google Scholar 

  51. Bittencourt LF, Rana OF (2017) Mobility-aware application scheduling in fog computing. IEEE Cloud Comput 4:26–35

    Article  Google Scholar 

  52. Etemad M, Aazam M, St-Hilaire M (2017) Using DEVS for modeling and simulating a fog computing environment. In: IEEE, pp 849–854. https://doi.org/10.1109/ICCNC.2017.7876242. URL http://ieeexplore.ieee.org/document/7876242/

  53. Aazam M, Zeadally S, Harras KA Offloading in fog computing for IoT: review, enabling technologies, and research opportunities. Future Gener Comput Syst. https://doi.org/10.1016/j.future.2018.04.057. URL http://linkinghub.elsevier.com/retrieve/pii/S0167739X18301973

  54. Rayes A, Salam S (2017) Fog computing defining. In: Internet of Things from hype to reality, Springer International Publishing, Cham, pp 139–164. https://doi.org/10.1007/978-3-319-44860-2_6. URL http://link.springer.com/10.1007/978-3-319-44860-2_6

  55. Klas GI (2015) Fog computing and mobile edge cloud gain momentum open fog consortium, ETSI MEC and cloudlets

  56. Deng R, Lu R, Lai C, Luan TH (2015) Towards power consumption-delay tradeoff by workload allocation in cloud-fog computing. In: IEEE, pp 3909–3914. https://doi.org/10.1109/ICC.2015.7248934. URL http://ieeexplore.ieee.org/document/7248934/

  57. Dolui K, Datta SK (2017) Comparison of edge computing implementations: fog computing, cloudlet and mobile edge computing. In: IEEE, pp 1–6. https://doi.org/10.1109/GIOTS.2017.8016213. URL http://ieeexplore.ieee.org/document/8016213/

  58. Hu P, Dhelim S, Ning H, Qiu T (2017) Survey on fog computing: architecture, key technologies, applications and open issues. J Netw Comput Appl 98:27–42. https://doi.org/10.1016/j.jnca.2017.09.002. URL http://linkinghub.elsevier.com/retrieve/pii/S1084804517302953

  59. Fog computing in the internet of things (2017) Intelligence at the edge, 1st edn. Springer, New York

  60. Toosi AN, Son J, Buyya R (2018) Clouds-pi: a low-cost raspberry-pi based testbed for software-defined-networking in cloud data centers. ACM SIGCOMM Comput Commun Rev 7:1–11

    Google Scholar 

  61. Wang K, Shen M, Cho J, Banerjee A, Van der Merwe J, Webb K (2015) MobiScud: a fast moving personal cloud in the mobile network, ACM Press, pp 19–24. https://doi.org/10.1145/2785971.2785979. URL http://dl.acm.org/citation.cfm?doid=2785971.2785979

  62. Han B, Gopalakrishnan V, Ji L, Lee S (2015) Network function virtualization: challenges and opportunities for innovations. IEEE Commun Mag 53(2):90–97. https://doi.org/10.1109/MCOM.2015.7045396. URL http://ieeexplore.ieee.org/document/7045396/

  63. Vinueza Naranjo PG, Baccarelli E, Scarpiniti M Design and energy-efficient resource management of virtualized networked Fog architectures for the real-time support of IoT applications. J Supercomput. https://doi.org/10.1007/s11227-018-2274-0. URL http://link.springer.com/10.1007/s11227-018-2274-0

  64. Oueis J, Strinati EC, Barbarossa S (2015) The fog balancing: load distribution for small cell cloud computing. In: IEEE, pp 1–6. https://doi.org/10.1109/VTCSpring.2015.7146129. URL http://ieeexplore.ieee.org/document/7146129/

  65. De Vleeschauwer D, Robinson DC (2011) Optimum caching strategies for a telco CDN. Bell Labs Tech J 16(2):115–132. https://doi.org/10.1002/bltj.20506. URL http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6770158

  66. Pooranian Z, Shojafar M, Naranjo PGV, Chiaraviglio L, Conti M (2017) A novel distributed fog-based networked architecture to preserve energy in fog data centers. In: IEEE, pp 604–609. https://doi.org/10.1109/MASS.2017.33. URL http://ieeexplore.ieee.org/document/8108808/

  67. Gupta P, Goyal MK, Gupta N (2015) Reliability aware load balancing algorithm for content delivery network. In: Satapathy SC, Govardhan A, Raju KS, Mandal JK (eds) Emerging ICT for bridging the future—proceedings of the 49th annual convention of the computer society of India (CSI), vol 337, Springer International Publishing, Cham, pp 427–434. https://doi.org/10.1007/978-3-319-13728-5_48. URL http://link.springer.com/10.1007/978-3-319-13728-5_48

  68. Zhou J, Qiao Y (2015) Low-peak-to-average power ratio and low-complexity asymmetrically clipped optical orthogonal frequency-division multiplexing uplink transmission scheme for long-reach passive optical network. Opt Lett 40(17):4034. https://doi.org/10.1364/OL.40.004034. URL https://www.osapublishing.org/abstract.cfm?URI=ol-40-17-4034

  69. Nag A, Payne DB, Ruffini M (2016) N:1 protection design for minimizing olts in resilient dual-homed long-reach passive optical network. J Opt Commun Netw 8(2):93. https://doi.org/10.1364/JOCN.8.000093. URL https://www.osapublishing.org/abstract.cfm?URI=jocn-8-2-93

  70. Dixit A, Lannoo B, Colle D, Pickavet M, Demeester P (2015) Delay models in ethernet long-reach passive optical networks. In: IEEE, pp 1239–1247. https://doi.org/10.1109/INFOCOM.2015.7218499. URL http://ieeexplore.ieee.org/document/7218499/

  71. De Andrade M, Buttaboni A, Tornatore M, Boffi P, Martelli P, Pattavina A (2015) Optimization of long-reach TDM/WDM passive optical networks. Opt Switch Netw 16:36–45. https://doi.org/10.1016/j.osn.2014.11.001. URL http://linkinghub.elsevier.com/retrieve/pii/S157342771400126X

  72. Liu Y, Guo L, Yu C, Yu Y, Wang X (2014) Planning of survivable long-reach passive optical network (LR-PON) against single shared-risk link group (SRLG) failure. Opt Switch Netwo 11:167–176. https://doi.org/10.1016/j.osn.2013.06.001. URL http://linkinghub.elsevier.com/retrieve/pii/S1573427713000404

  73. Truong NB, Lee GM, Ghamri-Doudane Y (2015) Software defined networking-based vehicular adhoc network with fog computing. In: IEEE, pp 1202–1207. https://doi.org/10.1109/INM.2015.7140467. URL http://ieeexplore.ieee.org/document/7140467/

  74. He X, Ren Z, Shi C, Fang J (2016) Cloud/fog networking in the internet of vehicles. China Commun 13:140–149

    Article  Google Scholar 

  75. Din S, Paul A, Ahmad A, Ahmed SH, Jeon G, Rawat DB (2018) Hierarchical architecture for 5g based software-defined intelligent transportation system. In: IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE

  76. Sheetal J Architecture of 5g technology in mobile communication. In: Proceedings of 18th IRF International Conference, 11th January

  77. Brown D, Mather D, Shaddock RN, Weeks WA, Franckx J, Erreygers JJJM (2018) Single line passive optical network converter module. US Patent 9,900,108 (Feb. 20)

  78. Chakraborty P (2018) Design of passive optical network for hospital management. Asian J Converg Technol 4(I)

  79. Mahmud R, Kotagiri R, Buyya R (2018) Fog computing: a taxonomy, survey and future directions. In: Internet of everything, Springer, pp 103–130

  80. Mercian A, McGarry MP, Reisslein M (2013) Offline and online multi-thread polling in long-reach pons: a critical evaluation. J Lightwave Technol 31(12):2018–2028. https://doi.org/10.1109/JLT.2013.2262766. URL http://ieeexplore.ieee.org/document/6515602/

  81. Townsend PD, Talli G, MacHale EK, Antony C (2008) Long reach PONs, COIN 2008. In: 7th International Conference on Optical Internet, pp 1–200000

  82. Helmy A, Krishna N, Nayak A (2018) On the feasibility of service composition in a long-reach pon backhaul. In: 2018 International Conference on Optical Network Design and Modeling (ONDM), IEEE, pp 41–46

  83. Helmy A, Nayak A (2018) Toward parallel edge computing in long-reach pons. J Opt Commun Netw 10(9):736–748

    Article  Google Scholar 

  84. Arbelaez A, Mehta D, Sullivan OB, Quesad L (2018) Parallel constraint-based local search: an application to designing resilient long-reach passive optical networks. In: Handbook of parallel constraint reasoning, Springer, pp 633–665

  85. Dastjerdi A, Gupta H, Calheiros R, Ghosh S, Buyya R (2016) Fog computing: principles, architectures, and applications. In: Internet of Things, Elsevier, pp 61–75. https://doi.org/10.1016/B978-0-12-805395-9.00004-6. URL http://linkinghub.elsevier.com/retrieve/pii/B9780128053959000046

  86. Stojmenovic I, Wen S, Huang X, Luan H (2016) An overview of fog computing and its security issues: an overview of fog computing and its security issues. Concurr Comput Pract Exp 28(10):2991–3005. https://doi.org/10.1002/cpe.3485. URL http://doi.wiley.com/10.1002/cpe.3485

  87. Dastjerdi AV, Gupta H, Calheiros RN, Ghosh SK, Buyya R (2016) Fog computing: principles, architectures, and applications. In: Internet of Things, Elsevier, pp 61–75

  88. Chiang M, Zhang T (2016) Fog and iot: an overview of research opportunities. IEEE Internet Things J 3(6):854–864

    Article  Google Scholar 

  89. More P (2015) Review of implementing fog computing. Int J Res Eng Technol 4(06):335–338

    Article  Google Scholar 

  90. Lin CC, Yang JW (2018) Cost-efficient deployment of fog computing systems at logistics centers in industry 4.0. IEEE Trans Ind Inf. https://doi.org/10.1109/TII.2018.2827920

  91. Jia G, Han G, Wang H, Wang F (2018) Cost aware cache replacement policy in shared last-level cache for hybrid memory based fog computing. EnterpInf Syst 12(4):435–451

    Article  Google Scholar 

  92. Sarkar S, Chatterjee S, Misra S (2018) Assessment of the suitability of fog computing in the context of internet of things. IEEE Trans Cloud Comput 6(1):46–59

    Article  Google Scholar 

  93. Song Z, Duan Y, Wan S, Sun X, Zou Q, Gao H, Zhu D (2018) Processing optimization of typed resources with synchronized storage and computation adaptation in fog computing. Wireless Commun Mob Comput. https://doi.org/10.1155/2018/3794175

  94. He S, Cheng B, Wang H, Xiao X, Cao Y, Chen J (2018) Data security storage model for fog computing in large-scale iot application. In: IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE, pp 39–44

  95. Bi Y, Han G, Lin C, Deng Q, Guo L, Li F (2018) Mobility support for fog computing: an sdn approach. IEEE Commun Mag 56(5):53–59

    Article  Google Scholar 

  96. Roig PJ, Alcaraz S, Gilly K, Juiz C (2018) Study on mobility and migration in a fog computing environment. In: 22nd International Conference Electronics, IEEE, pp 1–6

  97. Zhang P, Liu JK, Yu FR, Sookhak M, Au MH, Luo X (2018) A survey on access control in fog computing. IEEE Commun Mag 56(2):144–149

    Article  Google Scholar 

  98. Thota C, Sundarasekar R, Manogaran G, Varatharajan R, Priyan M (2018) Centralized fog computing security platform for iot and cloud in healthcare system. In: Exploring the Convergence of Big Data and the Internet of Things, IGI Global, pp 141–154

  99. Wang B, Chang Z, Zhou Z, Ristaniemi T (2018) Reliable and privacy-preserving task recomposition for crowdsensing in vehicular fog computing. In: IEEE 87th Vehicular Technology Conference (VTC Spring), IEEE, pp 1–6

  100. Guan Y, Shao J, Wei G, Xie M (2018) Data security and privacy in fog computing. IEEE Netw 99:1–6

    Google Scholar 

  101. Matt C (2018) Fog computing. Bus Inf. Syst Eng 60(4):351–355

    Google Scholar 

  102. Shi C, Ren Z, Yang K, Chen C, Zhang H, Xiao Y, Hou X (2018) Ultra-low latency cloud-fog computing for industrial internet of things. In: 2018 IEEE Wireless Communications and Networking Conference (WCNC), IEEE, pp 1–6

  103. Mahmud R, Ramamohanarao K, Buyya R Latency-aware application module management for fog computing environments. In: ACM Transactions on Internet Technology (TOIT)

  104. Mahmud R, Srirama SN, Ramamohanarao K, Buyya R (2018) Quality of experience (QoE)-aware placement of applications in fog computing environments. J Parallel Distrib Comput. https://doi.org/10.1016/j.jpdc.2018.03.004

  105. Chekired DA, Khoukhi L, Mouftah HT (2018) Industrial IoT data scheduling based on hierarchical fog computing: a key for enabling smart factory. IEEE Trans Ind Inf 14(10):4590–4602. https://doi.org/10.1109/TII.2018.2843802

    Article  Google Scholar 

  106. Kiani A, Ansari N, Khreishah A Hierarchical capacity provisioning for fog computing. arXiv preprint arXiv:1807.01093

  107. Naqvi SAA, Javaid N, Butt H, Kamal MB, Hamza A, Kashif M (2018) Metaheuristic optimization technique for load balancing in cloud-fog environment integrated with smart grid. In: International Conference on Network-Based Information Systems, Springer, pp 700–711

  108. Hussain MM, Alam MS, Beg MS (2019) Feasibility of fog computing in smart grid architectures. In: Proceedings of 2nd International Conference on Communication, Computing and Networking, Springer, pp 999–1010

  109. Okay FY, Ozdemir S (2018) A secure data aggregation protocol for fog computing based smart grids. In: 2018 IEEE 12th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG), IEEE, pp 1–6

  110. Lyu L, Nandakumar K, Rubinstein B, Jin J, Bedo J, Palaniswami M (2018) PPFA privacy preserving fog-enabled aggregation in smart grid. IEEE Trans Ind Inf. https://doi.org/10.1109/TII.2018.2803782

  111. Ling CW, Datta A, Xu J (2018) A case for distributed multilevel storage infrastructure for visual surveillance in intelligent transportation networks. IEEE Internet Comput 22(1):42–51

    Article  Google Scholar 

  112. Cao Y, Hou P, Brown D, Wang J, Chen S (2015) Distributed analytics and edge intelligence: pervasive health monitoring at the era of fog computing. In: Proceedings of the 2015 Workshop on Mobile Big Data, ACM, pp 43–48

  113. Gia TN, Jiang M, Rahmani A-M, Westerlund T, Liljeberg P, Tenhunen H (2015) Fog computing in healthcare internet of things: a case study on ecg feature extraction. In: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM), IEEE, pp 356–363

  114. Aazam M, Huh E-N (2015) E-hamc: leveraging fog computing for emergency alert service. In: 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), IEEE, pp 518–523

  115. Ballas C, Marsden M, Zhang D, O’Connor NE, Little S (2018) Performance of video processing at the edge for crowd-monitoring applications. In: 2018 IEEE 4th World Forum Internet Things (WF-IoT). https://doi.org/10.1109/WF-IoT.2018.8355170

  116. Hong K, Lillethun D, Ramachandran U, Ottenwälder B, Koldehofe B (2013) Mobile fog: a programming model for large-scale applications on the internet of things. In: Proceedings of the Second ACM SIGCOMM Workshop on Mobile Cloud Computing, ACM, pp 15–20

  117. Zhu X, Chan DS, Hu H, Prabhu MS, Ganesan E, Bonomi F (2015) Improving video performance with edge servers in the fog computing architecture. Intel Technol J 19(1):202–224

    Google Scholar 

  118. Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, ACM, pp 13–16

  119. Grover J, Jain A, Singhal S, Yadav A (2018) Real-time vanet applications using fog computing. In: Proceedings of First International Conference on Smart System, Innovations and Computing, Springer, pp 683–691

  120. Stojmenovic I, Wen S (2014) The fog computing paradigm: scenarios and security issues. In: 2014 Federated Conference on Computer Science and Information Systems (FedCSIS), IEEE, pp 1–8

  121. Bonomi F, Milito R, Natarajan P, Zhu J (2014) Fog computing: a platform for internet of things and analytics. In: Big Data and Internet of Things: A Roadmap for Smart Environments, Springer, pp 169–186

  122. Liu J, Li J, Zhang L, Dai F, Zhang Y, Meng X, Shen J (2018) Secure intelligent traffic light control using fog computing. Future Gener Comput Syst 78:817–824

    Article  Google Scholar 

  123. Choo KKR, Lu R, Chen L, Yi X (2018) A foggy research future: advances and future opportunities in fog computing research. Future Gener Comput Syst 78:677–679

    Article  Google Scholar 

  124. Tran VL, Islam A, Kharel J, Shin SY (2018) On the application of social internet of things with fog computing: a new paradigm for traffic information sharing system. In: 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud), IEEE, pp 349–354

  125. Rao YS, Sree KB (2018) A review on fog computing: conceptual live Vm migration framework, issues, applications and its challenges. Int J Sci Res Comput Sci Eng Inf Technol 3(1)

  126. Garg S, Singh A, Batra S, Kumar N, Yang LT (2018) Uav-empowered edge computing environment for cyber-threat detection in smart vehicles. IEEE Netw 32(3):42–51

    Article  Google Scholar 

  127. Li L, Ota K, Dong M (2018) Deep learning for smart industry: efficient manufacture inspection system with fog computing. IEEE Trans Ind Inf 14(10)

  128. Tortonesi M, Govoni M, Morelli A, Riberto G, Stefanelli C, Suri N (2018) Taming the IoT data deluge: an innovative information-centric service model for fog computing applications. Future Gen Comput Syst. https://doi.org/10.1016/j.future.2018.06.009

  129. Raja K, Krithika L (2016) Smart street light system. Autom Auton Syst 8(4):97–99

    Google Scholar 

  130. Wang S, Dey S (2012) Cloud mobile gaming: modeling and measuring user experience in mobile wireless networks. ACM SIGMOBILE Mob Comput Commun Rev 16(1):10–21

    Article  Google Scholar 

  131. Zhao Z, Hwang K, Villeta J (2012) Game cloud design with virtualized cpu/gpu servers and initial performance results. In: Proceedings of the 3rd Workshop on Scientific Cloud Computing, ACM, pp 23–30

  132. Yang L, Cao J, Yuan Y, Li T, Han A, Chan A (2013) A framework for partitioning and execution of data stream applications in mobile cloud computing. ACM SIGMETRICS Perform Eval Rev 40(4):23–32

    Article  Google Scholar 

  133. Qian Z, He Y, Su C, Wu Z, Zhu H, Zhang T, Zhou L, Yu Y, Zhang Z (2013) Timestream: reliable stream computation in the cloud. In: Proceedings of the 8th ACM European Conference on Computer Systems, ACM, pp 1–14

  134. Nath SB, Gupta H, Chakraborty S, Ghosh SK A survey of fog computing and communication: current researches and future directions. arXiv preprint arXiv:1804.04365

  135. Yi S, Li C, Li Q (2015) A survey of fog computing: concepts, applications and issues. In: Proceedings of the 2015 Workshop on Mobile Big Data, ACM, pp 37–42

  136. Yi S, Hao Z, Qin Z, Li Q (2015) Fog computing: platform and applications. In: Third IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb), IEEE 2015, pp 73–78

  137. Rahmani A-M, Thanigaivelan NK, Gia TN, Granados J, Negash B, Liljeberg P, Tenhunen H, Smart, (2015) e-health gateway: bringing intelligence to internet-of-things based ubiquitous healthcare. systems. In: 2015 12th Annual Consumer Communications and Networking Conference (CCNC), IEEE, pp 826–834

  138. Mahmoud MM, Rodrigues JJ, Ahmed SH, Shah SC, Al-Muhtadi JF, Korotaev VV, De Albuquerque VHC (2018) Enabling technologies on cloud of things for smart healthcare. IEEE Access 6:31950–31967

    Article  Google Scholar 

  139. Din S, Paul A, Guizani N, Ahmed SH, Khan M, Rathore MM (2017) Features selection model for internet of e-health things using big data. In: GLOBECOM 2017—2017 IEEE Global Communications Conference, IEEE, pp 1–7

  140. Varghese B, Wang N, Barbhuiya S, Kilpatrick P, Nikolopoulos DS (2016) Challenges and opportunities in edge computing. In: IEEE, pp 20–26. https://doi.org/10.1109/SmartCloud.2016.18. URL http://ieeexplore.ieee.org/document/7796149/

  141. Shenoy K, Bhokare P, Pai U (2013) FOG computing future of cloud computing. Int J Sci Res (IJSR) 4(6):55–56

    Google Scholar 

  142. Hao Z, Novak E, Yi S, Li Q (2017) Challenges and software architecture for fog computing. IEEE Internet Comput 21(2):44–53. https://doi.org/10.1109/MIC.2017.26. URL http://ieeexplore.ieee.org/document/7867731/

  143. Varghese B, Wang N, Nikolopoulos DS, Buyya R (2017) Feasibility of fog computing. arXiv preprint arXiv:1701.05451

  144. Puthal D, Obaidat MS, Nanda P, Prasad M, Mohanty SP, Zomaya AY (2018) Secure and sustainable load balancing of edge data centers in fog computing. IEEE Commun Mag 56(5):60–65

    Article  Google Scholar 

  145. Wan J, Chen B, Wang S, Xia M, Li D, Liu C (2018) Fog computing for energy-aware load balancing and scheduling in smart factory. IEEE Trans Ind Inf. https://doi.org/10.1109/TII.2018.2818932

  146. Iorga M, Feldman L, Barton R, Martin MJ, Goren NS, Mahmoudi C (2018) Fog computing conceptual model. Technical report

  147. Aazam M, Zeadally S, Harras KA (2018) Deploying fog computing in industrial internet of things and industry 4.0. IEEE Trans Ind. Inf 14(10):4674–4682

    Google Scholar 

  148. Comma-di L, Abdullaziz OI, Antevski K, Chundrigar SB, Gdowski R, Kuo P-H, Mourad A, Yen L-H, Zabala A (2018) Opportunities and challenges of joint edge and fog orchestration. In: 2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), IEEE, pp 344–349

  149. Chaudhary D, Bhushan K, Gupta B (2018) Survey on ddos attacks and defense mechanisms in cloud and fog computing. Int J E-serv Mobile Appl (IJESMA) 10(3):61–83

    Article  Google Scholar 

  150. Jiang Y, Huang Z, Tsang DH (2018) Challenges and solutions in fog computing orchestration. IEEE Netw 32(3):122–129

    Article  Google Scholar 

  151. Santos J, Vanhove T, Sebrechts M, Dupont T, Kerckhove W, Braem B, Van Seghbroeck G, Wauters T, Leroux P, Latre S et al (2018) City of things: enabling resource provisioning in smart cities. IEEE Commun Mag 56(7):177–183

    Article  Google Scholar 

  152. Wu H-Y, Lee C-R, Energy efficient scheduling for heterogeneous fog computing architectures. In: 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), IEEE, pp 555–560

  153. Mehta A, Elmroth E (2018) Distributed cost-optimized placement for latency-critical applications in heterogeneous environments. In: 2018 IEEE International Conference on Autonomic Computing, Trento, Italy, September 3–7, 2018, pp 121–130

  154. Byers CC, Clarke JM, Salgueiro G (2018) Configuring heterogeneous computing environments using machine learning. US Patent App. 15/390,921 (Jun. 28)

  155. Cappiello C, Plebani P, Vitali M (2018) A data utility model for data-intensive applications in fog computing environments. In: Fog computing, Springer, pp 183–202

  156. Khan MA, Umer T, Khan SU, Yu S, Rachedi A (2018) Ieee access special section editorial: green cloud and fog computing: energy efficiency and sustainability aware infrastructures, protocols, and applications. IEEE Access 6:12280–12283

    Article  Google Scholar 

  157. Qiao G, Leng S, Zhang K, He Y (2018) Collaborative task offloading in vehicular edge multi-access networks. IEEE Commun Mag 56(8):48–54

    Article  Google Scholar 

  158. Aazam M, Zeadally S, Harras KA (2018) Offloading in fog computing for IoT: review, enabling technologies, and research opportunities. Future Gen Comput Syst 87:278–289. https://doi.org/10.1016/j.future.2018.04.057

    Article  Google Scholar 

  159. Zhang G, Shen F, Yang Y, Qian H, Yao W (2018) Fair task offloading among fog nodes in fog computing networks. In: 2018 IEEE International Conference on Communications (ICC), IEEE, pp 1–6

  160. Jošilo S, Dán G Decentralized fog computing resource management for offloading of periodic tasks. In: Poster Presented at IEEE INFOCOM

  161. Agarwal S, Yadav S, Yadav AK (2015) An architecture for elastic resource allocation in Fog. Computing 6(2):7

    Google Scholar 

  162. Alrawais A, Alhothaily A, Hu C, Cheng X (2017) Fog computing for the internet of things: security and privacy issues. IEEE Internet Comput 21(2):34–42

    Article  Google Scholar 

  163. Tsugawa M, Matsunaga A, Fortes JA (2014) Cloud computing security: What changes with software-defined networking? Secure cloud computing. Springer, Berlin, pp 77–93

    Chapter  Google Scholar 

  164. Hu P, Ning H, Qiu T, Song H, Wang Y, Yao X (2017) Security and privacy preservation scheme of face identification and resolution framework using fog computing in internet of things. IEEE Internet Things J 4(5):1143–1155

    Article  Google Scholar 

  165. Wang C, Wang Q, Ren K, Lou W (2010) Privacy-preserving public auditing for data storage security in cloud computing. In: 2010 Proceedings, Infocom, IEEE, pp 1–9

  166. Basudan S, Lin X, Sankaranarayanan K (2017) A privacy-preserving vehicular crowdsensing-based road surface condition monitoring system using fog computing. IEEE Internet Things J 4(3):772–782

    Article  Google Scholar 

  167. Koo D, Hur J (2018) Privacy-preserving deduplication of encrypted data with dynamic ownership management in fog computing. Future Gener Comput Syst 78:739–752

    Article  Google Scholar 

  168. Ma L, Teymorian AY, Cheng X (2008) A hybrid rogue access point protection framework for commodity wi-fi. networks. In: The 27th Conference on Computer Communications INFOCOM 2008, IEEE, pp 1220–1228

  169. Modi C, Patel D, Borisaniya B, Patel H, Patel A, Rajarajan M (2013) A survey of intrusion detection techniques in cloud. J Netw Comput Appl 36(1):42–57

    Article  Google Scholar 

  170. Valenzuela J, Wang J, Bissinger N (2013) Real-time intrusion detection in power system operations. IEEE Trans Power Syst 28(2):1052–1062

    Article  Google Scholar 

  171. Qin Z, Li Q, Chuah M-C (2013) Defending against unidentifiable attacks in electric power grids. IEEE Trans Parallel Distrib Syst 24(10):1961–1971

    Article  Google Scholar 

  172. Cao N, Wang C, Li M, Ren K, Lou W (2014) Privacy-preserving multi-keyword ranked search over encrypted cloud data. IEEE Trans Parallel Distrib Syst 25(1):222–233

    Article  Google Scholar 

  173. Rial A, Danezis G (2011) Privacy-preserving smart metering. In: Proceedings of the 10th Annual ACM Workshop on Privacy in the Electronic Society, ACM, pp 49–60

  174. Wang L, Liu G, Sun L (2017) A secure and privacy-preserving navigation scheme using spatial crowdsourcing in fog-based vanets. Sensors 17(4):668

    Article  Google Scholar 

  175. Qin Z, Yi S, Li Q, Zamkov D (2014) Preserving secondary users’ privacy in cognitive radio networks. In: 2014 Proceedings of INFOCOM, IEEE, pp 772–780

  176. Wei W, Xu F, Li Q (2012) Mobishare: flexible privacy-preserving location sharing in mobile online social networks. In: 012 Proceedings of INFOCOM,, IEEE, pp 2616–2620

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Singh, S.P., Nayyar, A., Kumar, R. et al. Fog computing: from architecture to edge computing and big data processing. J Supercomput 75, 2070–2105 (2019). https://doi.org/10.1007/s11227-018-2701-2

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