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Fog computing in internet of things: Practical applications and future directions

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Abstract

Internet of things (IoT) services have been accepted and accredited globally for the past couple of years and have had increasing interest from researchers. Fog architecture has been brought up in IoT for enhancing its competence in a variety of applications. Fog computing is an emerging concept that transforms centralized Cloud to distributed Fog by bringing storage and computation closer to the user end. The aim of this paper is to highlight the fundamental Fog three-tier model and emphasize its advantages, challenges and possible attacks. This paper will also focus on Fog computing models pertaining to IoT scenario that have been developed over the period to conquer the challenges of existing Fog computing architecture. This paper also highlights Fog’s real importance which will include a review of scenario-based examples. Moreover, open issues have also been discussed to be worked upon in future.

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References

  1. Mahdikhani H, Lu R Achieving privacy-preserving multi dot-product query in Fog computing-enhanced IoT, GLOBECOM 2017 - 2017 IEEE global communications conference

  2. Yang X, Shah SA, Ren A, Zhao N, Fan D, Hu F, Ur Rehman M, von Deneen KM, Tian J (2018) Wandering pattern sensing at S-band. IEEE Journal of Biomedical and Health Informatics, 1–1

  3. Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of things (IoT): A vision, architectural elements, and future directions. Futur Gener Comput Syst 29(7):1645–1660

    Article  Google Scholar 

  4. What is the IoT? Everything you need to know about the Internet of Things right now, https://www.zdnet.com/article/what-is-the-internet-of-things-everything-you-need-to-know-about-the-iot-right-now/ https://www.zdnet.com/article/what-is-the-internet-of-things-everything-you-need-to-know-about-the-iot-right-now/ https://www.zdnet.com/article/what-is-the-internet-of-things-everything-you-need-to-know-about-the-iot-right-now/

  5. Rajasegarar S, Leckie C, Palaniswami M (2008) Anomaly detection in wireless sensor networks. IEEE Wirel Commun 15:4

    Article  Google Scholar 

  6. Shi W, Cao J, Zhang Q, Li Y, Xu L (2016) Edge computing: Vision and challenges. IEEE Internet Things J 3:5

    Article  Google Scholar 

  7. Zhou J, Athukorala K, Gilman E, Riekki J, Ylianttila M (2012) Cloud architecture for dynamic service composition. International Journal of Grid and High Performance Computing 4(2):17–31

    Article  Google Scholar 

  8. Zhou J, Leppänen T, Harjula E, Ylianttila M, Ojala T, Yu C, Jin H, Huazhong LTY (2013) CloudThings: A common architecture for integrating the internet of things with cloud computing, Computer supported cooperative work in design (CSCWD) IEEE 17th International Conference

  9. Grance PMT (2011) The NIST definition of cloud computing, NIST special publication, 800–145

  10. Nisha P (2015) Fog computing and its real time applications. International Journal of Emerging Technology and advanced Engineering 5:6

    Google Scholar 

  11. Khan S, Parkinson S, Qin Y (2017) Fog computing security: a review of current applications and security solutions, Journal of Cloud Computing: Advances, Systems and Applications

  12. 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

    Article  Google Scholar 

  13. Mukherjee M, Shu L, Wang D (2018) Survey of Fog computing: Fundamental, Network applications, and research challenges, IEEE communications surveys and tutorials, Volume 20, No. 3 Third Quarter

  14. Mouradian C, Naboulsi D, Yangui S, Glitho RH, Morrow MJ, Polakos PA (2018) A comprehensive survey on fog computing: State-of-the-art and research challenges, IEEE Communications Surveys and Tutorials, Volume 20, No. 1 First Quarter

  15. Naha RK, Garg S, Georgakopoulos D, Jayaraman PP, Gao L, Xiang Y, Ranjan R (2018) Fog computing: Survey of trends, architectures, Requirements, and Research Directions, ResearchGate

  16. Cisco delivers vision of Fog computing to accelerate value from billions of connected devices, https://newsroom.cisco.com/press-release-content?articleId=1334100

  17. Ivan S, Sheng W (2014) The Fog computing paradigm: Scenarios and security issues, Computer science and information systems, FedCSIS. Federated Conference

  18. Swati A, Shashank Y, Arun K (2016) An efficient Architecture and algorithm for resource provisioning in Fog computing. International Journal of Information Engineering and Electronic Business 8(1):48–61

    Article  Google Scholar 

  19. Bonomi F, Milito R, Natarajan P, Zhu J (2014) Fog computing: A platform for internet of things and analytics, Big data and internet of things: A roadmap for smart environments. Springer, pp 169–186

  20. Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things, MCC’12

  21. Lyu L, Jin J, Rajasegarar S, He X, Palaniswami M (2017) Fog-empowered anomaly detection in IoT using hyperellipsoidal clustering. IEEE Internet Things J 4:5

    Article  Google Scholar 

  22. Kavvadia E, Sagiadinos S, Oikonomou K, Tsioutsiouliklis G, Issa S (2015) Elastic virtual machine placement in cloud computing network environments. Comput Netw 93(Part 3):435– 447

    Article  Google Scholar 

  23. Vaquero LM, Rodero-Merino L (2014) Finding your way in the Fog: Towards a comprehensive definition of fog computing. ACM SIGCOMM Computer Communication Review 44(5):27– 32

    Article  Google Scholar 

  24. Zhan Z-H, Liu X-F, Gong Y-J, Zhang J, Shu-HungChung H, Li Yun (2015) Scheduling, cloud computing resource a survey of its evolutionary approaches. ACM Comput Surv 47(4):63

    Article  Google Scholar 

  25. Stojmenovic I (2014) Fog computing: A Cloud to the ground support for smart things and machine-to-machine networks. Telecommunication Networks and Applications Conference (ATNAC), 2014 Australasian

  26. Lu R, Heung K, Lashkari AH, Ghorbani AA (2017) A lightweight privacy-preserving data aggregation scheme for fog computing-enhanced IoT. IEEE Access 5:3302–3312

    Article  Google Scholar 

  27. Swati A, Shashank Y, Arun K (2015) An architecture for elastic resource allocation in Fog computing. IJCSC J 6(2):201–207

    Google Scholar 

  28. Chiang M, Zhang T (2016) Fog and IoT: An overview of research opportunities. IEEE Internet Things J 6:854–864

    Article  Google Scholar 

  29. Yigitoglu E, Mohamed M, Liu L, Ludwig H (2017) Foggy: A framework for continuous automated IoT application deployment in Fog computing, AI and Mobile Services (AIMS) IEEE International Conference

  30. Kapsalis A, Kasnesis P, Venieris IS, Kaklamani DI, Patrikakis CZ (2017) A Cooperative Fog approach for effective workload balancing, IEEE Cloud Computing, Volume 4, Issue 2

  31. Zhang H, Xiao Y, Bu S, Niyato D, Yu FR, Han Z (2017) Computing resource allocation in three-tier IoT Fog networks: A joint optimization approach combining stackelberg game and matching. IEEE Internet Things J 4(5):1204–1215

    Article  Google Scholar 

  32. Masip-Bruin X, Marín-Tordera E, Tashakor G, Jukan A, Ren G-J (2016) Foggy clouds and cloudy Fogs: a real need for coordinated management of Fog-to-cloud computing systems. IEEE Wirel Commun 23 (5):120–128

    Article  Google Scholar 

  33. Sarkar S, Misra S (2016) Theoretical modelling of Fog computing: A green computing paradigm to support IoT applications, IET Networks, volume 5, Issue No. 2

  34. Alippi C, Fantacci R, Marabissi D, Roveri M (2016) A cloud to the ground: The new frontier of intelligent and autonomous networks of things. IEEE Commun Mag 54(12):14–20

    Article  Google Scholar 

  35. Al Faruque MA, Vatanparvar K (2016) Energy management-as-a-service over fog computing platform. IEEE Internet Things J 3(2):161–169

    Article  Google Scholar 

  36. Wang W, Wang Q, Sohraby K (2017) Multimedia Sensing as a Service (MSaaS): Exploring resource saving potentials of at cloud-edge IoT and Fogs. IEEE Internet Things J 4(2):487–495

    Google Scholar 

  37. Chen S, Zhang T, Shi W (2017) Fog computing, vol 2

  38. Bazm M-M, Lacoste M, Südholt M, Menaud J-M (2017) Side-channels beyond the cloud edge: New isolation threats and solutions, Cyber Security in Networking Conference (CSNet

  39. Fakeeh KA (2016) Privacy and security problems in Fog computing. Commun Appl Elect (CAE) 4:6

    Google Scholar 

  40. Mukherjee M, Matam R, Shu L, Maglaras L, Ferrag MA, Choudhury N, Kumar V (2017) Security and privacy in fog computing: Challenges. IEEE Access 5:19293–19304

    Article  Google Scholar 

  41. Li C, Novak QZ, Li Q (2017) Securing SDN infrastructure of IoT–Fog networks from MitM attacks. IEEE Internet Things J 4(5):1156–1164

    Article  Google Scholar 

  42. Chang C, Srirama SN, Buyya R (2017) Indie Fog: An efficient fog-computing infrastructure for the internet of things. Computer 50(9):92–98

    Article  Google Scholar 

  43. Dastjerdi AV, Buyya R (2016) Fog computing: Helping the internet of things realize its potential. Computer 49(8):112–116

    Article  Google Scholar 

  44. Moreno-Vozmediano R, Montero RS, Hued E, Llorente IM (2017) Cross-site virtual network in cloud and fog computing. IEEE Cloud Comput 4(2):46–53

    Article  Google Scholar 

  45. Holgado-Terriza R-V, Muros-Cobos G-G (2014) Distributed service-based approach for sensor data fusion in IoT Environments, Special issue wireless sensor networks and the internet of things sensors

  46. Ashrafi TH, Hossain MDA, Arefin SE, Das KDJ, Chakrabarty A (2017) Service based FOG computing model for IoT, Collaboration and internet computing (CIC) IEEE 3rd International Conference

  47. Deng S, Huang L, Wu H, Tan W, Taheri J, Zomaya AY, Wu Z (2016) Toward mobile service computing: Opportunities and challenges. IEEE Cloud Comput 3(4):32–41

    Article  Google Scholar 

  48. Wen Z, Yang R, Garraghan P, Lin T, Xu J, Rovatsos M (2017) Fog orchestration for internet of things services. IEEE Internet Comput 21(2):16–24

    Article  Google Scholar 

  49. Patel P, Ali MI, Sheth A (2017) On using the intelligent edge for IoT analytics. IEEE Intell Syst 32 (5):64–69

    Article  Google Scholar 

  50. Brogi A, Forti S (2017) QoS-aware deployment of IoT applications through the Fog. IEEE Internet Things J 4(5):1185–1192

    Article  Google Scholar 

  51. Taneja M, Davy A (2016) Resource aware placement of data analytics platform in Fog computing. Procedia Comput Sci 97:153– 156

    Article  Google Scholar 

  52. Taneja M, Davy A (2016) Poster abstract: Resource aware placement of data stream analytics operators on fog infrastructure for internet of things applications, edge computing (SEC) IEEE/ACM Symposium

  53. Taneja M, Davy A (2017) Resource aware placement of IoT application modules in fog-cloud computing paradigm integrated network and service management (IM), IFIP/IEEE symposium

  54. Zahra S, Alam M, Javaid Q, Wahid A, Javaid N, Malik SUR, Khan MK (2017) Fog Computing Over IoT: A secure deployment and formal verification. IEEE Access 5:27132–27144

    Article  Google Scholar 

  55. Chaudhary R, Kumar N, Sherali Z (2017) Network service chaining in fog and cloud computing for the 5g environment: Data management and security challenges. IEEE Commun Mag 55(11):114–122

    Article  Google Scholar 

  56. Amaxilatis D, Akrivopoulos O, Chatzigiannakis I, Tselios C (2017) Enabling stream processing for people-centric IoT based on the Fog computing paradigm, Emerging technologies and factory automation (ETFA), 22nd IEEE international conference

  57. Nan Y, Li W, Bao W, Delicato FC, Pires PF, Dou Y, Zomaya AY (2017) Adaptive energy-aware computation offloading for cloud of things systems. IEEE Access 5:23947–23957

    Article  Google Scholar 

  58. Name HAM, Oladipo FO, Ariwa E (2017) User mobility and resource scheduling and management in Fog computing to support IoT devices, Innovative Computing Technology (INTECH), 7th International Conference

  59. Bao W, Yuan D, Yang Z, Wang S, Li W, Zhou BB, Zomaya AY (2017) Follow Me Fog: Toward seamless handover timing schemes in a fog computing environment. IEEE Communications Magazine 55(11):72–78

    Article  Google Scholar 

  60. Vilalta R, Lopez V, Giorgetti A, Peng S, Orsini V, Velasco L, Serral-Gracia R, Morris Silvia De Fina D, Cugini F, Castoldi P, Mayoral A, Casellas R, Martinez R, Verikoukis C, Munoz R (2017) TelcoFog: A unified flexible fog and cloud computing architecture for 5G networks. IEEE Commun Mag 55 (8):36–43

    Article  Google Scholar 

  61. Shih Y-Y, Chung W-H, Pang A-C, Chiu T-C, Wei H-Y (2017) Enabling low-latency applications in fog-radio access networks. IEEE Netw 1:52–58

    Article  Google Scholar 

  62. Sun X, Ansari N (2016) EdgeIoT: Mobile edge computing for the internet of things. IEEE Commun Mag 54(12):22–29

    Article  Google Scholar 

  63. Sharma SK, Wang X (2017) Live data analytics with collaborative edge and cloud processing in wireless IoT networks. IEEE Access 5:4621–4635

    Article  Google Scholar 

  64. Liu H, Chen Z, Qian L (2016) emph”The three primary colors of mobile systems. IEEE Commun Mag 54(9):15–21

    Article  Google Scholar 

  65. Hu H, Wen Y, Chua T-S, Li X (2014) emph”Toward scalable systems for big data analytics: A technology tutorial. IEEE Access 2:652–687

    Article  Google Scholar 

  66. Pham X-Q, Huh E-N (2017) emph”Towards task scheduling in a cloudfog computing system, 2016 18th Asia-pacific network operations and management symposium (APNOMS)

  67. Choi N, Kim D, Lee S-J, Yi Y (2017) A Fog operating system for user-oriented IoT services: Challenges and Research Directions. IEEE Commun Mag 55(8):44–51

    Article  Google Scholar 

  68. Yu T, Wang, X, Shami A (2017) A novel Fog computing enabled temporal data reduction scheme in IoT systems, GLOBECOM 2017 - IEEE global communications conference

  69. Mollah MB, Azad Md AK, Vasilakos A (2017) Secure data sharing and searching at the edge of cloud-assisted internet of things. IEEE Cloud Comput 4(1):34–42

    Article  Google Scholar 

  70. Satyanarayanan M, Simoens P, Xiao Y, Pillai P, Chen Z, Ha K, Hu W, Amos B (2015) emph”Edge analytics in the internet of things, vol 14

  71. Ali M, Dhamotharan R, Khan E, Khan SU, Vasilakos AV, Li K, Zomaya AY, Zomaya AY (2017) emph”SeDa SC: Secure data sharing in clouds. IEEE Syst J 11(2):395–404

    Article  Google Scholar 

  72. Seo S-H, Nabeel M, Ding X, Bertino E (2014) emph”An efficient certificateless encryption for secure data sharing in public clouds. IEEE Trans Knowl Data Eng 26(9):2107–2119

    Article  Google Scholar 

  73. Yang S (2017) IoT stream processing and analytics in the Fog. IEEE Commun Mag 55(8):22–27

    Article  Google Scholar 

  74. Ma S, Liu Q, Sheu PC-Y (2018) Foglight: Visible light-enabled indoor localization system for low-power IoT devices. IEEE Internet Things J 5(1):175–185

    Article  Google Scholar 

  75. Ma S, Liu Q, Sheu P (2016) On hearing your position through light for mobile robot indoor navigation, IEEE international conference on multimedia and expo workshops

  76. Inokuchi S, Sato K, Matsuda F (1984) Range imaging system for 3-D object recognition, Proc ICPR, pp 806–808

  77. Manchester Data Encoding for Radio Communications, https://www.maximintegrated.com/en/app-notes/index.mvp/id/3435

  78. Chandola V, Banerjee A, Kumar V (2009) Anomaly detection: A survey. ACM Comput Surveys (CSUR) 41(3):15

    Article  Google Scholar 

  79. Moshtaghi M, Rajasegarar S, Leckie C, Karunasekera S (2011) An efficient hyperellipsoidal clustering algorithm for resource-constrained environments. Pattern Recognition Elsevier 44(9):2197–2209

    Article  Google Scholar 

  80. Rajasegarar S, Gluhak A, Imran MA, Nati M, Moshtaghi M, Leckie C, Palaniswami M (2014) Ellipsoidal neighborhood outlier factor for distributed anomaly detection in resource constrained networks. Pattern Recogn 47(9):2867–2879

    Article  Google Scholar 

  81. He J, Wei J, Chen K, Tang Z, Zhou Y, Zhang Y (2017) Multi-tier Fog computing with large-scale IoT data analytics for smart cities, vol PP

  82. Ni J, Zhang A, Lin X, Shen XS (2017) Security, privacy, and fairness in fog-based vehicular crowdsensing. IEEE Commun Mag 55(6):146–152

    Article  Google Scholar 

  83. Zhang Y, Chen M, Guizani N, Wu D, Leung VCM (2017) SOVCAN: Safety-oriented vehicular controller area network. IEEE Commun Mag 55(8):94–99

    Article  Google Scholar 

  84. Sheng Z, Kenarsari-Anhari A, Taherinejad N, Leung VCM (2016) A multichannel medium access control protocol for vehicular power line communication systems. IEEE Trans Veh Technol 65(2):542–554

    Article  Google Scholar 

  85. Hu B, Ratcliffe M, Qi Y, Zhao Q, Peng H, Fan D, Zheng F, Jackson M, Moore P (2011) EEG-based cognitive interfaces for ubiquitous applications: Developments and challenges, vol 26

  86. Weiss A (2007) Computing in the clouds. netWorker - Cloud computing 11(4):16–25

    Google Scholar 

  87. Pearson S, Benameur A (2010) “Privacy, security and trust issues arising from cloud computing,” Cloud Computing Technology and Science (CloudCom), IEEE Second International Conference

  88. Viola P, Jones MJ (2004) Robust real-time face detection. Int J Comput Vis 57(2):137–154

    Article  Google Scholar 

  89. Abdul W, Ali Z, Ghouzali S, Alfawaz B, Muhammad G, Hossain MS (2017) Biometric security through visual encryption for fog edge computing. IEEE Access 5:5531–5538

    Article  Google Scholar 

  90. Kraemer FA, Braten AE, Tamkittikhun N, Palma D (2017) Fog computing in healthcare—a review and discussion. IEEE Access 5:9206–9222

    Article  Google Scholar 

  91. Zhang Y, Gravina R, Lu H, Villari M, Fortino G (2018) PEA parallel electrocardiogram-based authentication for smart healthcare systems. J Netw Comput Appl 117:10–16

    Article  Google Scholar 

  92. Arteaga-Falconi JS, Osman HA, El Saddik A (2016) ECG authentication for mobile devices. IEEE Trans Instrum Meas 65:3

    Article  Google Scholar 

  93. AzamiSidek K, Mai V, Khalil I (2014) Data mining in mobile ECG based biometric identification. J Netw Comput Appl 44: 83–91

    Article  Google Scholar 

  94. Kang SJ, Lee SY, Cho HI, Park H (2016) ECG authentication system design based on signal analysis in mobile and wearable devices. IEEE Signal Process Lett 23:6

    Article  Google Scholar 

  95. Qian Y, Zhang Y, Ma X, Yu H, Peng L (2019) EARS: Emotion-aware recommender system based on hybrid information fusion. Information Fusion 46:141–146

    Article  Google Scholar 

  96. Mubeen S, Nikolaidis P, Didic A, Pei-Breivold H, Sandström K, Behnam M (2017) Delay mitigation in offloaded cloud controllers in industrial IoT. IEEE Access 5:4418–4430

    Article  Google Scholar 

  97. Xiao S, Yu H, Wu Y, Peng Z, Zhan Y (2018) Self-evolving trading strategy integrating internet of things and big data. IEEE Internet Things J 5(4):2518–2525

    Article  Google Scholar 

  98. Lv S, Lv S (2011) Applying BP neural network model to forecast peak velocity of blasting ground vibration. Procedia Engineer 26:257–263

    Article  Google Scholar 

  99. Wang D, Zhang M, Li Z, Song C, Fu M, Li J, Chen X (2017) System impairment compensation in coherent optical communications by using a bio-inspired detector based on artificial neural network and genetic algorithm. Opt Commun 399:1–12

    Article  Google Scholar 

  100. Rahman A, Hassanain E, Hossain MS (2017) Towards a secure mobile edge computing framework for Hajj. IEEE Access 5:11768–11781

    Article  Google Scholar 

  101. Chen R-Y (2017) An intelligent value stream-based approach to collaboration of food traceability cyber physical system by Fog computing. Food Control, Elsvier 71:124–136

    Article  Google Scholar 

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This article is part of the Topical Collection: Special issue on Fog Computing for Healthcare

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Naeem, R.Z., Bashir, S., Amjad, M.F. et al. Fog computing in internet of things: Practical applications and future directions. Peer-to-Peer Netw. Appl. 12, 1236–1262 (2019). https://doi.org/10.1007/s12083-019-00728-0

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