Skip to main content

Advertisement

Log in

Fog Computing for 5G-Enabled Tactile Internet: Research Issues, Challenges, and Future Research Directions

  • Published:
Mobile Networks and Applications Aims and scope Submit manuscript

Abstract

From the last few years, we have witnessed an exponential increase in the usage of delay-sensitive applications by the end-users because of the paradigm shift and revolution in different technologies starting from 1G to 5G most of which are having focus on QoS and QoE to the end-users. The existing standards on 5G mainly concentrate on the following issues: 10 Gigabyte data rate, 1-millisecond latency, high bandwidth per unit area, 99.999% availability, 100% coverage and 90% reduction in network energy usage. Hence, 5G has the capability to support various types of communications from the low power Local Area Network (LAN) to Wide Area Networks (WAN) with low-latency and high-speed. It allows human-to-human (H2H), human-to-machine (H2M) interactions for exchanging of data and signals. So, for better data transmission between different entities (for example, smart objects located across different geographic locations), efficient communication between billions of smart devices is required and the associated technology is called as “Internet of Things”. However, issues such as- latency-tolerant, low-data rate, high complexity, privacy and security in existing solutions may deteriorate the performance of any implemented solution in this environment. To mitigate the above-mentioned problems, the literature suggests that fog computing can be one of the options as it provides ultra-low-latency for Tactile-based applications. Tactile Internet is an emerging technology used for H2M interactions to support high-reliability, ultra-responsive, and high fidelity. Keeping focus on all the aforementioned challenges and constraints, in this paper, we provide an analysis on the usage of the strong backbone infrastructure of fog computing for 5G-enabled Tactile Internet with a maximum bandwidth of 1 Gigabyte having the minimum latency of 1-millisecond. It supports low-latency and high-reliability in Tactile-based applications. Keeping focus on the issues such as- resource management, communication infrastructure, fog orchestration, fog networking, healthcare, security and privacy of fog system in Tactile-based applications, we have explored and compared the existing state-of-the-art proposals using various parameters such as- energy-efficient, QoS, scalability, mobility, and interoperability. In addition, a number of open research challenges of fog computing for 5G-enabled Tactile Internet are also explored to provide deep insights to the readers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  1. ITU-T Technology Watch Report, ‘The Tactile Internet’ Aug 2014, accessed 2 August 2019

  2. Node-RED, accessed 2 August 2019. Available: https://nodered.org/

  3. Cisco, 2019, accessed 4 August 2019. Available: (https://blogs.cisco.com/sp/mobile-vni-forecast-2017-2022-5g-emerges)

  4. Al-Sa’d MF, Tlili M, Abdellatif AA, Mohamed A, Elfouly T, Harras K, Connor MD et al (2018) A deep learning approach for vital signs compression and energy efficient delivery in mhealth systems. IEEE Access 6:33727–33739

    Google Scholar 

  5. Aazam M, Huh E-N (2014) Fog computing and smart gateway based communication for cloud of things. In: 2014 International conference on future internet of things and cloud. IEEE, pp 464–470

  6. 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 

  7. Abeshu A, Chilamkurti N (2018) Deep learning: the frontier for distributed attack detection in fog-to-things computing. IEEE Commun Mag 56(2):169–175

    Google Scholar 

  8. Agarwal S, Yadav S, Yadav AK (2016) An efficient architecture and algorithm for resource provisioning in fog computing. Int J Inf Eng Electron Bus 8(1):48

    Google Scholar 

  9. Ahn S, Gorlatova M, Naghizadeh P, Chiang M, Mittal P (2018) Adaptive fog-based output security for augmented reality. In: Proceedings of the 2018 morning workshop on virtual reality and augmented reality network. ACM, pp 1–6

  10. Aijaz A, Dohler M, Aghvami AH, Friderikos V, Frodigh M (2016) Realizing the tactile internet: haptic communications over next generation 5g cellular networks. IEEE Wirel Commun 24(2):82–89

    Google Scholar 

  11. Al-Dhubhani R, Mehmood R, Katib I, Algarni A (2017) Location privacy in smart cities era. In: International conference on smart cities, infrastructure, technologies and applications. Springer, pp 123–138

  12. 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

    Google Scholar 

  13. Amadeo M, Campolo C, Molinaro A, Rottondi C, Verticale G (2018) Securing the mobile edge through named data networking. In: 2018 IEEE 4th world forum on internet of things (WF-IoT). IEEE, pp 80–85

  14. Amendola D, Cordeschi N, Baccarelli E (2016) Bandwidth management vms live migration in wireless fog computing for 5g networks. In: 2016 5th IEEE international conference on cloud networking (Cloudnet). IEEE, pp 21–26

  15. An X, Zhou X, Lü X, Lin F, Yang L (2018) Sample selected extreme learning machine based intrusion detection in fog computing and mec. Wireless Communications and Mobile Computing 2018

  16. Andreev S, Galinina O, Pyattaev A, Gerasimenko M, Tirronen T, Torsner J, Sachs J, Dohler M, Koucheryavy Y (2015) Understanding the IoT connectivity landscape: a contemporary m2m radio technology roadmap. IEEE Commun Mag 53(9):32–40

    Google Scholar 

  17. Antonakoglou K, Xu X, Steinbach E, Mahmoodi T, Dohler M (2018) Toward haptic communications over the 5g tactile internet. IEEE Commun Surv Tutorials 20(4):3034–3059

    Google Scholar 

  18. Ateya AA, Vybornova A, Kirichek R, Koucheryavy A (2017) Multilevel cloud based tactile internet system. In: 2017 19th international conference on advanced communication technology (ICACT). IEEE, pp 105–110

  19. Bastug E, Bennis M, Debbah M (2014) Living on the edge: the role of proactive caching in 5g wireless networks. IEEE Commun Mag 52(8):82–89

    Google Scholar 

  20. Basudan S, Lin X, Sankaranarayanan K (2017) An efficient compromised node revocation scheme in fog-assisted vehicular crowdsensing. In: GLOBECOM 2017–2017 IEEE global communications conference. IEEE, pp 1–6

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

    Google Scholar 

  22. Bhardwaj K, Miranda JC, Gavrilovska A (2018) Towards IoT-ddos prevention using edge computing. In: {USENIX} workshop on hot topics in edge computing (HotEdge 18)

  23. Bhardwaj K, Shih M-W, Agarwal P, Gavrilovska A, Kim T, Schwan K (2016) Fast, scalable and secure onloading of edge functions using airbox. In: 2016 IEEE/ACM symposium on edge computing (SEC). IEEE, pp 14–27

  24. Bittencourt LF, Lopes MM, Petri I, Rana OF (2015) Towards virtual machine migration in fog computing. In: 2015 10th international conference on P2P, parallel, grid, cloud and internet computing (3PGCIC). IEEE, pp 1–8

  25. Cao Y, Chen S, Hou P, Brown D (2015) Fast: a fog computing assisted distributed analytics system to monitor fall for stroke mitigation. In: 2015 IEEE international conference on networking, architecture and storage (NAS). IEEE, pp 2–11

  26. Cardellini V, Grassi V, Presti FL, Nardelli M (2015) On qos-aware scheduling of data stream applications over fog computing infrastructures. In: 2015 IEEE symposium on computers and communication (ISCC). IEEE, pp 271–276

  27. Cha J, Ho Y-S, Kim Y, Ryu J, Oakley I (2009) A framework for haptic broadcasting. IEEE MultiMedia 16(3):16–27

    Google Scholar 

  28. Chen L, Xu J (2017) Socially trusted collaborative edge computing in ultra dense networks. In: Proceedings of the second ACM/IEEE symposium on edge computing. ACM, p 9

  29. Chen M, Zhang Y, Li Y, Mao S, Leung VC (2015) Emc: emotion-aware mobile cloud computing in 5g. IEEE Netw 29(2):32–38

    Google Scholar 

  30. Chen X, Jiao L, Li W, Fu X (2015) Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans Netw 24(5):2795–2808

    Google Scholar 

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

    Google Scholar 

  32. Coileáin DÓ, O’mahony D (2015) Accounting and accountability in content distribution architectures: a survey. ACM Comput Surv (CSUR) 47(4):59

    Google Scholar 

  33. Craciunescu R, Mihovska A, Mihaylov M, Kyriazakos S, Prasad R, Halunga S (2015) Implementation of fog computing for reliable e-health applications. In: 2015 49th Asilomar conference on signals, systems and computers. IEEE, pp 459–463

  34. da Silva CA, de Aquino Júnior GS (2018) Fog computing in healthcare: a review. In: 2018 IEEE symposium on computers and communications (ISCC). IEEE, pp 1126–1131

  35. 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

  36. Dsouza C, Ahn G-J, Taguinod M (2014) Policy-driven security management for fog computing: preliminary framework and a case study. In: Proceedings of the 2014 IEEE 15th international conference on information reuse and integration (IEEE IRI 2014). IEEE, pp 16–23

  37. Dubey H, Yang J, Constant N, Amiri AM, Yang Q, Makodiya K (2015) Fog data: enhancing telehealth big data through fog computing. In: Proceedings of the ASE bigdata & socialinformatics 2015. ACM, p 14

  38. Echeverria S, Klinedinst D, Williams K, Lewis GA (2016) Establishing trusted identities in disconnected edge environments. In: 2016 IEEE/ACM symposium on edge computing (SEC). IEEE, pp 51–63

  39. Esposito C, Castiglione A, Pop F, Choo K-KR (2017) Challenges of connecting edge and cloud computing: a security and forensic perspective. IEEE Cloud Comput 4(2):13–17

    Google Scholar 

  40. Fettweis G (2014) The tactile internet: applications and challenges. IEEE Veh Technol Mag 9(1):64–70

    Google Scholar 

  41. Fratu O, Pena C, Craciunescu R, Halunga S (2015) Fog computing system for monitoring mild dementia and copd patients-romanian case study. In: 2015 12th international conference on telecommunication in modern satellite, cable and broadcasting services (TELSIKS). IEEE, pp 123–128

  42. Gao W (2014) Opportunistic peer-to-peer mobile cloud computing at the tactical edge. In: 2014 IEEE military communications conference. IEEE, pp 1614–1620

  43. 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. IEEE, pp 356–363

  44. Giang NK, Blackstock M, Lea R, Leung VC (2015) Developing IoT applications in the fog: a distributed dataflow approach. In: 2015 5th international conference on the internet of things (IOT). IEEE, pp 155–162

  45. Giri D, Obaidat MS, Maitra T (2017) Sechealth: an efficient fog based sender initiated secure data transmission of healthcare sensors for e-medical system. In: GLOBECOM 2017–2017 IEEE global communications conference. IEEE, pp 1–6

  46. Gu L, Zeng D, Guo S, Barnawi A, Xiang Y (2015) Cost efficient resource management in fog computing supported medical cyber-physical system. IEEE Trans Emerging Top Comput 5(1):108–119

    Google Scholar 

  47. Han B, Gopalakrishnan V, Ji L, Lee S (2015) Network function virtualization: challenges and opportunities for innovations. IEEE Commun Mag 53(2):90–97

    Google Scholar 

  48. Hara K, Azenkot S, Campbell M, Bennett CL, Le V, Pannella S, Moore R, Minckler K, Ng RH, Froehlich JE (2015) Improving public transit accessibility for blind riders by crowdsourcing bus stop landmark locations with google street view: an extended analysis. ACM Trans Accessible Comput (TACCESS) 6 (2):5

  49. Hassan MA, Xiao M, Wei Q, Chen S (2015) Help your mobile applications with fog computing. In: 2015 12th annual IEEE international conference on sensing, communication, and networking-workshops (SECON Workshops). IEEE, pp 1–6

  50. He D, Qiao Y, Chan S, Guizani N (2018) Flight security and safety of drones in airborne fog computing systems. IEEE Commun Mag 56(5):66–71

    Google Scholar 

  51. He T, Ciftcioglu EN, Wang S, Chan KS (2017) Location privacy in mobile edge clouds: a chaff-based approach. IEEE J Sel Areas Commun 35(11):2625–2636

    Google Scholar 

  52. He X, Liu J, Jin R, Dai H (2017) Privacy-aware offloading in mobile-edge computing. In: GLOBECOM 2017–2017 IEEE global communications conference. IEEE, pp 1–6

  53. Holland O, Steinbach E, Prasad RV, Liu Q, Dawy Z, Aijaz A, Pappas N, Chandra K, Rao VS, Oteafy S et al (2019) The IEEE 1918.1 Tactile Internet standards working group and its standards. Proc IEEE 107(2):256–279

    Google Scholar 

  54. 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

  55. Hong K, Lillethun D, Ramachandran U, Ottenwälder B, Koldehofe B (2013) Opportunistic spatio-temporal event processing for mobile situation awareness. In: Proceedings of the 7th ACM international conference on distributed event-based systems. ACM, pp 195–206

  56. 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 IoT J 4(5):1143–1155

    Google Scholar 

  57. Huang C, Lu R, Choo K-KR (2017) Vehicular fog computing: architecture, use case, and security and forensic challenges. IEEE Commun Mag 55(11):105–111

    Google Scholar 

  58. Huo Y, Hu C, Qi X, Jing T (2017) Lodpd: a location difference-based proximity detection protocol for fog computing. IEEE IoT J 4(5):1117–1124

    Google Scholar 

  59. Intharawijitr K, Iida K, Koga H (2016) Analysis of fog model considering computing and communication latency in 5g cellular networks. In: 2016 IEEE international conference on pervasive computing and communication workshops (PerCom Workshops). IEEE, pp 1–4

  60. Jacob R, Shalaik B, Winstanley AC, Mooney P (2011) Haptic feedback for passengers using public transport. In: International conference on digital information and communication technology and its applications. Springer, pp 24–32

  61. Jacob R, Winstanley A, Togher N, Roche R, Mooney P (2012) Pedestrian navigation using the sense of touch. Comput Environ Urban Syst 36(6):513–525

    Google Scholar 

  62. Kapsalis A, Kasnesis P, Venieris IS, Kaklamani DI, Patrikakis CZ (2017) A cooperative fog approach for effective workload balancing. IEEE Cloud Comput 4(2):36–45

    Google Scholar 

  63. Khan S, Parkinson S, Qin Y (2017) Fog computing security: a review of current applications and security solutions. J Cloud Comput 6(1):19

    Google Scholar 

  64. Kim H, Feamster N (2013) Improving network management with software defined networking. IEEE Commun Mag 51(2):114–119

    Google Scholar 

  65. Kim Y, Kim D, Son J, Wang W, Noh Y (2018) A new fog-cloud storage framework with transparency and auditability. In: 2018 IEEE international conference on communications (ICC). IEEE, pp 1–7

  66. Kitanov S, Monteiro E, Janevski T (2016) 5g and the fog: survey of related technologies and research directions. In: 2016 18th Mediterranean electrotechnical conference (MELECON). IEEE, pp 1–6

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

    Google Scholar 

  68. Kreutz D, Ramos F, Verissimo P, Rothenberg CE, Azodolmolky S, Uhlig S (2014) Software-defined networking: a comprehensive survey. arXiv preprint arXiv:1406.0440

  69. Krishnan YN, Bhagwat CN, Utpat AP (2015) Fog computing network based cloud computing. In: 2015 2nd international conference on electronics and communication systems (ICECS). IEEE, pp 250–251

  70. Kugler H-J, Mullery A (1994) Towards a Pan-European telecommunication service infrastructure-IS&N’94: second international conference on intelligence in broadband services and networks, Aachen, Germany, September 7-9, 1994. Proceedings, vol. 15773. Springer Science & Business Media

  71. Lee G (2015) Software defined networking-based vehicular adhoc network with fog computing. In: 2015 IFIP/IEEE international symposium on integrated network management (IM). IEEE, pp 1202–1207

  72. Li C, Li C-P, Hosseini K, Lee SB, Jiang J, Chen W, Horn G, Ji T, Smee JE, Li J (2018) 5G-based systems design for tactile internet. Proc IEEE 99:1–18

    Google Scholar 

  73. Li C, Qin Z, Novak E, Li Q (2017) Securing sdn infrastructure of IoT–fog networks from mitm attacks. IEEE IoT J 4(5):1156–1164

    Google Scholar 

  74. 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

    Google Scholar 

  75. Luan TH, Gao L, Li Z, Xiang Y, Wei G, Sun L (2015) Fog computing: focusing on mobile users at the edge. arXiv preprint arXiv:1502.01815

  76. Madsen H, Burtschy B, Albeanu G, Popentiu-Vladicescu F (2013) Reliability in the utility computing era: towards reliable fog computing. In: 2013 20th international conference on systems, signals and image processing (IWSSIP). IEEE, pp 43–46

  77. Maier M, Chowdhury M, Rimal BP, Van DP (2016) The tactile internet: vision, recent progress, and open challenges. IEEE Commun Mag 54(5):138–145

  78. Mao Y, Yi S, Li Q, Feng J, Xu F, Zhong S (2018) A privacy-preserving deep learning approach for face recognition with edge computing. In: USENIX workshop on hot topics in edge computing (HotEdge 18), Boston, MA

  79. Masip-Bruin X, Marín-Tordera E, Alonso A, Garcia J (2016) Fog-to-cloud computing (f2c): the key technology enabler for dependable e-health services deployment. In: 2016 Mediterranean ad hoc networking workshop (Med-Hoc-Net). IEEE, pp 1–5

  80. Mehmood R, Alam F, Albogami NN, Katib I, Albeshri A, Altowaijri SM (2017) Utilearn: a personalised ubiquitous teaching and learning system for smart societies. IEEE Access 5:2615–2635

    Google Scholar 

  81. Mehmood R, Faisal MA, Altowaijri S (2015) Future networked healthcare systems: a review and case study. In: Handbook of research on redesigning the future of internet architectures. IGI Global, pp 531–558

  82. Mijumbi R, Serrat J, Gorricho J-L, Bouten N, De Turck F, Boutaba R (2015) Network function virtualization: state-of-the-art and research challenges. IEEE Commun Surv Tutorials 18(1):236–262

    Google Scholar 

  83. Monteiro A, Dubey H, Mahler L, Yang Q, Mankodiya K (2016) Fit: a fog computing device for speech tele-treatments. In: 2016 IEEE international conference on smart computing (SMARTCOMP). IEEE, pp 1–3

  84. Moosavi SR, Gia TN, Nigussie E, Rahmani AM, Virtanen S, Tenhunen H, Isoaho J (2016) End-to-end security scheme for mobility enabled healthcare internet of things. Futur Gener Comput Syst 64:108–124

    Google Scholar 

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

    Google Scholar 

  86. Muhammed T, Mehmood R, Albeshri A, Katib I (2018) Ubehealth: a personalized ubiquitous cloud and edge-enabled networked healthcare system for smart cities. IEEE Access 6:32258–32285

    Google Scholar 

  87. Mutlag AA, Ghani MKA, Arunkumar NA, Mohamed MA, Mohd O (2019) Enabling technologies for fog computing in healthcare IoT systems. Futur Gener Comput Syst 90:62–78

    Google Scholar 

  88. Ni J, Lin X, Zhang K, Yu Y (2016) Secure and deduplicated spatial crowdsourcing: a fog-based approach. In: 2016 IEEE global communications conference (GLOBECOM). IEEE , pp 1–6

  89. 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

    Google Scholar 

  90. Ni J, Zhang K, Lin X, Shen XS (2017) Securing fog computing for internet of things applications: challenges and solutions. IEEE Commun Surv Tutorials 20(1):601–628

    Google Scholar 

  91. Ni J, Zhang K, Lin X, Shen XS (2018) Securing fog computing for internet of things applications: challenges and solutions. IEEE Commun Surv Tutorials 20(1):601–628

    Google Scholar 

  92. Nunes BAA, Mendonca M, Nguyen X-N, Obraczka K, Turletti T (2014) A survey of software-defined networking: past, present, and future of programmable networks. IEEE Commun Surv Tutorials 16(3):1617–1634

    Google Scholar 

  93. Oteafy SM, Hassanein HS (2018) Leveraging tactile internet cognizance and operation via IoT and edge technologies. Proc IEEE 107(2):364–375

    Google Scholar 

  94. Ottenwalder B, Koldehofe B, Rothermel K, Hong K, Ramachandran U (2014) Recep: selection-based reuse for distributed complex event processing. In: Proceedings of the 8th ACM international conference on distributed event-based systems. ACM, pp 59–70

  95. Oueis J, Strinati EC, Sardellitti S, Barbarossa S (2015) Small cell clustering for efficient distributed fog computing: a multi-user case. In: 2015 IEEE 82nd vehicular technology conference (VTC2015-Fall). IEEE, pp 1–5

  96. Pahl C, El Ioini N, Helmer S, Lee B (2018) An architecture pattern for trusted orchestration in IoT edge clouds. In: 2018 third international conference on fog and mobile edge computing (FMEC). IEEE, pp 63–70

  97. Papagianni C, Leivadeas A, Papavassiliou S (2013) A cloud-oriented content delivery network paradigm: modeling and assessment. IEEE Trans Dependable Secure Comput 10(5):287–300

    Google Scholar 

  98. Parvez I, Rahmati A, Guvenc I, Sarwat AI, Dai H (2018) A survey on low latency towards 5g: ran, core network and caching solutions. IEEE Commun Surv Tutorials 20(4):3098–3130

    Google Scholar 

  99. Peng M, Li Y, Zhao Z, Wang C (2014) System architecture and key technologies for 5g heterogeneous cloud radio access networks. arXiv preprint arXiv:1412.6677

  100. Peng M, Yan S, Zhang K, Wang C (2015) Fog computing based radio access networks:, Issues and challenges. arXiv preprint arXiv:1506.04233

  101. 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

    Google Scholar 

  102. Sabes-Figuera R, Maghiros I (2013) European hospital survey: benchmarking deployment of e-health services (2012–2013). European Comission

  103. Sachs J, Andersson LA, Araújo J, Curescu C, Lundsjö J, Rune G, Steinbach E, Wikström G (2018) Adaptive 5g low-latency communication for tactile internet services. Proc IEEE 107(2):325–349

    Google Scholar 

  104. Saeed A, Abdelkader A, Khan M, Neishaboori A, Harras KA, Mohamed A (2017) Argus: realistic target coverage by drones. In: Proceedings of the 16th ACM/IEEE international conference on information processing in sensor networks. ACM, pp 155–166

  105. Saroa MK, Aron R (2018) Fog computing and its role in development of smart applications. In: 2018 IEEE international conference on parallel & distributed processing with applications, ubiquitous computing & communications, big data & cloud computing, social computing & networking, sustainable computing & communications (ISPA/IUCC/BDCloud/SocialCom/ SustainCom). IEEE, pp 1120–1127

  106. Sha K, Errabelly R, Wei W, Yang TA, Wang Z (2017) Edgesec: design of an edge layer security service to enhance IoT security. In: 2017 IEEE 1st international conference on fog and edge computing (ICFEC). IEEE, pp 81–88

  107. Sharma V, You I, Palmieri F, Jayakody DNK, Li J (2018) Secure and energy-efficient handover in fog networks using blockchain-based dmm. IEEE Commun Mag 56(5):22–31

    Google Scholar 

  108. Shen S, Huang L, Zhou H, Yu S, Fan E, Cao Q (2018) Multistage signaling game-based optimal detection strategies for suppressing malware diffusion in fog-cloud-based IoT networks. IEEE IoT J 5(2):1043–1054

    Google Scholar 

  109. Shen W, Yu J, Xia H, Zhang H, Lu X, Hao R (2017) Light-weight and privacy-preserving secure cloud auditing scheme for group users via the third party medium. J Netw Comput Appl 82:56–64

    Google Scholar 

  110. Shi H, Chen N, Deters R (2015) Combining mobile and fog computing: using coap to link mobile device clouds with fog computing. In: 2015 IEEE international conference on data science and data intensive systems. IEEE, pp 564–571

  111. Shirazi SN, Gouglidis A, Farshad A, Hutchison D (2017) The extended cloud: review and analysis of mobile edge computing and fog from a security and resilience perspective. IEEE J Sel Areas Commun 35(11):2586–2595

    Google Scholar 

  112. Simsek M, Aijaz A, Dohler M, Sachs J, Fettweis G (2016) 5G-enabled tactile internet. IEEE J. Sel Areas Commun 34(3):460–473

    Google Scholar 

  113. Slabicki M, Grochla K (2016) Performance evaluation of coap, snmp and netconf protocols in fog computing architecture. In: NOMS 2016-2016 IEEE/IFIP network operations and management symposium. IEEE, pp 1315–1319

  114. Stantchev V, Barnawi A, Ghulam S, Schubert J, Tamm G (2015) Smart items, fog and cloud computing as enablers of servitization in healthcare. Sensors & Transducers 185(2):121

    Google Scholar 

  115. Stojmenovic I, Wen S (2014) The fog computing paradigm: scenarios and security issues. In: 2014 federated conference on computer science and information systems. IEEE, pp 1–8

  116. Sukhmani S, Sadeghi M, Erol-Kantarci M, El Saddik A (2018) Edge caching and computing in 5g for mobile ar/vr and tactile internet. IEEE MultiMedia 26(1):21–30

    Google Scholar 

  117. Varadi S, Varkonyi GG, Kertész A (2018) Law and IoT: how to see things clearly in the fog. In: 2018 third international conference on fog and mobile edge computing (FMEC). IEEE, pp 233–238

  118. Wang H, Tan CC, Li Q (2008) Snoogle: a search engine for the physical world. In: IEEE INFOCOM 2008-the 27th conference on computer communications. IEEE, pp 1382–1390

  119. Wang H, Tan C, Li Q (2009) Snoogle: a search engine for pervasive environments. IEEE Trans Parallel Distrib Syst 21(8): 1188–1202

    Google Scholar 

  120. Wang X, Chen M, Taleb T, Ksentini A, Leung VC (2014) Cache in the air: exploiting content caching and delivery techniques for 5g systems. IEEE Commun Mag 52(2):131–139

    Google Scholar 

  121. Xu F, Tan CC, Li Q, Yan G, Wu J (2010) Designing a practical access point association protocol. In: 2010 Proceedings IEEE INFOCOM. IEEE, pp 1–9

  122. Yangui S, Ravindran P, Bibani O, Glitho RH, Hadj-Alouane NB, Morrow MJ, Polakos PA (2016) A platform as-a-service for hybrid cloud/fog environments. In: 2016 IEEE international symposium on local and metropolitan area networks (LANMAN). IEEE, pp 1–7

  123. Yi S, Hao Z, Qin Z, Li Q (2015) Fog computing: platform and applications. In: 2015 third IEEE workshop on hot topics in web systems and technologies (HotWeb). IEEE, pp 73–78

  124. Yi S, Qin Z, Li Q (2015) Security and privacy issues of fog computing: a survey. In: International conference on wireless algorithms, systems, and applications. Springer, pp 685– 695

  125. Yu Z, Au MH, Xu Q, Yang R, Han J (2018) Towards leakage-resilient fine-grained access control in fog computing. Futur Gener Comput Syst 78:763–777

    Google Scholar 

  126. Zao JK, Gan TT, You CK, Méndez SJR, Chung CE, Te Wang Y, Mullen T, Jung TP (2014) Augmented brain computer interaction based on fog computing and linked data. In: 2014 international conference on intelligent environments. IEEE, pp 374– 377

  127. Zeng D, Gu L, Guo S, Cheng Z, Yu S (2016) Joint optimization of task scheduling and image placement in fog computing supported software-defined embedded system. IEEE Trans Comput 65(12):3702–3712

    MathSciNet  Google Scholar 

  128. 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

    Google Scholar 

  129. Zhang Y, Tan C, Qun L (2013) Cachekeeper: a system-wide web caching service for smartphones. In: Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. ACM, pp 265–274

  130. Zhanikeev M (2015) A cloud visitation platform to facilitate cloud federation and fog computing. Computer 48(5):80– 83

    Google Scholar 

  131. Zheng X, Cai Z, Li J, Gao H (2016) A study on application-aware scheduling in wireless networks. IEEE Trans Mob Comput 16(7):1787–1801

    Google Scholar 

Download references

Acknowledgements

We are thankful to all the anonymous reviewers for the valuable comments and suggestions which are really helpful to improve the quality and presentation of the paper. This work is sponsored by the funds from TCS Innovation Lab, New Delhi and authors are thankful to TCS.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shubhani Aggarwal.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aggarwal, S., Kumar, N. Fog Computing for 5G-Enabled Tactile Internet: Research Issues, Challenges, and Future Research Directions. Mobile Netw Appl 28, 690–717 (2023). https://doi.org/10.1007/s11036-019-01430-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11036-019-01430-4

Keywords

Navigation