IoT-F2N: An energy-efficient architectural model for IoT using Femtolet-based fog network

  • Anwesha Mukherjee
  • Priti Deb
  • Debashis DeEmail author
  • Rajkumar Buyya


Energy- and latency-optimized Internet of Things (IoT) is an emerging research domain within fifth-generation (5G) wireless network paradigm. In traditional cloud-centric IoT the sensor data processing and storage occurs inside remote cloud servers, which increase delay and energy consumption. To reduce the delay and energy consumption, an IoT paradigm is proposed using 5G device Femtolet-based fog network. In this architecture, the data obtained from sensors are processed and maintained inside the edge and fog devices. The Femtolet works as an adaptable fog device and it expands and shrinks coverage according to user’s presence. A mathematical model is developed for the proposed paradigm. The delay and power consumption in the proposed model are determined. Qualnet 7 is used for simulating the proposed model. The results of simulation illustrate that the proposed architectural model reduces the energy consumption and delay by approximately 25% and 43% respectively than the fog computing-based existing IoT paradigm. The comparative analysis with the existing IoT paradigm shows that IoT using Femtolet-based fog network is a green and efficient approach.


Internet of Things Fog computing Femtolet Fog network Power Delay 



Authors are grateful to Department of Science and Technology (DST) for sanctioning a research Project entitled “Dynamic Optimization of Green Mobile Networks: Algorithm, Architecture and Applications” under Fast Track Young Scientist Scheme Reference No. SERB/F/5044/2012-2013, DST-FIST for SR/FST/ETI-296/2011 and Melbourne-Chindia Cloud Computing (MC3) Research Network.


  1. 1.
    Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660Google Scholar
  2. 2.
    Mukherjee A, De D (2014) Femtocell based green health monitoring strategy. In: XXXIth URSI General Assembly and Scientific Symposium (URSI GASS). IEEE, pp 1–4Google Scholar
  3. 3.
    De D, Mukherjee A, Ray A, Roy DG, Mukherjee S (2016) Architecture of green sensor mobile cloud computing. IET Wirel Sens Syst 6(4):109–120Google Scholar
  4. 4.
    Chandrasekhar V, Andrews JG, Muharemovic T, Shen Z, Gatherer A (2009) Power control in two-tier femtocell networks. IEEE Trans Wirel Commun 8(8):4316–4328Google Scholar
  5. 5.
    Mukherjee A, Bhattacherjee S, Pal S, De D (2013) Femtocell based green power consumption methods for mobile network. Comput Netw 57(1):162–178Google Scholar
  6. 6.
    Mukherjee A, De D, Roy DG (2019) A power and latency aware cloudlet selection strategy for multi-cloudlet environment. IEEE Trans Cloud Comput 7(1):141–154Google Scholar
  7. 7.
    Mahmud R, Kotagiri R, Buyya R (2018) Fog computing: a taxonomy, survey and future directions. In: Yang LT (ed) Internet of everything. Springer, Singapore, pp 103–130Google Scholar
  8. 8.
    Mukherjee A, De D (2016) Femtolet: a novel fifth generation network device for green mobile cloud computing. Simul Model Pract Theory 62:68–87Google Scholar
  9. 9.
    Barbarossa S, Sardellitti S, Di Lorenzo P (2013) Joint allocation of computation and communication resources in multiuser mobile cloud computing. In: 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, pp 26–30Google Scholar
  10. 10.
    Mukherjee A, Deb P, De D, Buyya R (2018) C2OF2N: a low power cooperative code offloading method for femtolet-based fog network. J Supercomput 74(6):2412–2448Google Scholar
  11. 11.
    Deb P, Mukherjee A, De D (2019) Design of green smart room using fifth generation network device femtolet. Wirel Pers Commun 104(3):1037–1064Google Scholar
  12. 12.
    De D, Mukherjee A (2015) Femto-cloud based secure and economic distributed diagnosis and home health care system. J Med Imaging Health Inform 5(3):435–447Google Scholar
  13. 13.
    De D, Mukherjee A, Sau A, Bhakta I (2016) Design of smart neonatal health monitoring system using SMCC. Healthc Technol Lett 4(1):13–19Google Scholar
  14. 14.
    Ahmad M, Amin MB, Hussain S, Kang BH, Cheong T, Lee S (2016) Health fog: a novel framework for health and wellness applications. J Supercomput 72(10):3677–3695Google Scholar
  15. 15.
    Sekhar PK, Wignes F (2016) Trace detection of research department explosive (RDX) using electrochemical gas sensor. Sens Actuators B Chem 227:185–190Google Scholar
  16. 16.
    Rawat P, Singh KD, Chaouchi H, Bonnin JM (2014) Wireless sensor networks: a survey on recent developments and potential synergies. J Supercomput 68(1):1–48Google Scholar
  17. 17.
    Giammarini M, Isidori D, Pieralisi M, Cristalli C, Fioravanti M, Concettoni E (2016) Design of a low cost and high performance wireless sensor network for structural health monitoring. Microsyst Technol 22(7):1845–1853Google Scholar
  18. 18.
    Huh J-H, Kim T-J (2019) A location-based mobile health care facility search system for senior citizens. J Supercomput 75(4):1831–1848Google Scholar
  19. 19.
    Durao F, Carvalho JFS, Fonseka A, Garcia VC (2014) A systematic review on cloud computing. J Supercomput 68(3):1321–1346Google Scholar
  20. 20.
    Abdelmaboud A, Jawawi DNA, Ghani I, Elsafi A, Kitchenham B (2015) Quality of service approaches in cloud computing: a systematic mapping study. J Syst Softw 101:159–179Google Scholar
  21. 21.
    Madria S, Kumar V, Dalvi R (2014) Sensor cloud: a cloud of virtual sensors. IEEE Softw 31(2):70–77Google Scholar
  22. 22.
    Sarkar S, Misra S (2016) Theoretical modelling of fog computing: a green computing paradigm to support IoT applications. IET Netw 5(2):23–29Google Scholar
  23. 23.
    Faruque A, Abdullah M, Vatanparvar K (2016) Energy management-as-a-service over fog computing platform. IEEE Internet Things J 3(2):161–169Google Scholar
  24. 24.
    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):46–59Google Scholar
  25. 25.
    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):1204–1215Google Scholar
  26. 26.
    Satyanarayanan M, Bahl P, Caceres R, Davies N (2009) The case for VM-based cloudlets in mobile computing. IEEE Pervasive Comput 4:14–23Google Scholar
  27. 27.
    Roy DG, De D, Mukherjee A, Buyya R (2017) Application-aware cloudlet selection for computation offloading in multi-cloudlet environment. J Supercomput 73(4):1672–1690Google Scholar
  28. 28.
    Flores H, NarayanaSrirama S (2014) Mobile cloud middleware. J Syst Softw 92:82–94Google Scholar
  29. 29.
    Brogi A, Forti S (2017) QoS-aware deployment of IoT applications through the fog. IEEE Internet Things J 4(5):1185–1192Google Scholar
  30. 30.
    White G, Nallur V, Clarke S (2017) Quality of service approaches in IoT: a systematic mapping. J Syst Softw 132:186–203Google Scholar
  31. 31.
    Zhang P, Zhou M, Fortino G (2018) Security and trust issues in Fog computing: a survey. Future Gener Comput Syst 88:16–27Google Scholar
  32. 32.
    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 16–23Google Scholar
  33. 33.
    Kulkarni S, Saha S, Hockenbury R (2014) Preserving privacy in sensor-fog networks. In: 9th International Conference for Internet Technology and Secured Transactions (ICITST-2014). IEEE, pp 96–99Google Scholar
  34. 34.
    Khan MA, Salah K (2018) IoT security: review, blockchain solutions, and open challenges. Future Gener Comput Syst 82:395–411Google Scholar
  35. 35.
    Reyna A, Martín C, Chen J, Soler E, Díaz M (2018) On blockchain and its integration with IoT. Challenges and opportunities. Future Gener Comput Syst 88:173–190Google Scholar
  36. 36.
    Mukherjee B, Wang S, Lu W, Neupane RL, Dunn D, Ren Y, Su Q, Calyam P (2018) Flexible IoT security middleware for end-to-end cloud–fog communication. Future Gener Comput Syst 87:688–703Google Scholar
  37. 37.
    Aazam M, Zeadally S, Harras KA (2018) Offloading in fog computing for IoT: review, enabling technologies, and research opportunities. Future Gener Comput Syst 87:278–289Google Scholar
  38. 38.
    Dehury CK, Sahoo PK (2016) Design and implementation of a novel service management framework for IoT devices in cloud. J Syst Softw 119:149–161Google Scholar
  39. 39.
    Srinivasan CR, Rajesh B, Saikalyan P, Premsagar K, Yadav ES (2019) A review on the different types of Internet of Things (IoT). J Adv Res Dyn Control Syst 11(1):154–158Google Scholar
  40. 40.
    Hamdan O, Shanableh H, Zaki I, Al-Ali AR, Shanableh T (2019) IoT-based interactive dual mode smart home automation. In: International Conference on Consumer Electronics (ICCE). IEEE, pp 1–2Google Scholar
  41. 41.
    Adeogun RO, Rodriguez I, Razzaghpour M, Berardinelli G, Christensen PH, Mogensen P (2019) Indoor occupancy detection and estimation using machine learning and measurements from an IoT LoRa-based monitoring system. In: 2019 Global Iot Summit (giots)Google Scholar
  42. 42.
    Shridhar VS (2019) The India of Things: Tata communications’ countrywide IoT network aims to improve traffic, manufacturing, and health care. IEEE Spectr 56(2):42–47Google Scholar
  43. 43.
    Al-Turjman F (2019) 5G-enabled devices and smart-spaces in social-IoT: an overview. Future Gener Comput Syst 92:732–744Google Scholar
  44. 44.
    Mutlag AR, Ghani MKA, Arunkumar N, Mohamed MA, Mohd O (2019) Enabling technologies for fog computing in healthcare IoT systems. Future Gener Comput Syst 90:62–78Google Scholar
  45. 45.
    Adhikari M, Gainey H (2019) Energy efficient offloading strategy in fog-cloud environment for IoT applications. Internet Things 6:100053Google Scholar
  46. 46.
    Mukherjee A, De D (2018) Octopus algorithm for wireless personal communications. Wirel Pers Commun 101(1):531–565Google Scholar
  47. 47.
    Mukherjee A, De D, Buyya R (2019) E2R-F2N: energy-efficient retailing using a femtolet-based fog network. Softw Prac Exp 49(3):498–523Google Scholar
  48. 48.

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringIndian Institute of Technology KharagpurKharagpurIndia
  2. 2.Department of Computer Science and Engineering, Centre of Mobile Cloud ComputingMaulana Abul Kalam Azad University of Technology, West BengalKolkataIndia
  3. 3.Department of PhysicsUniversity of Western AustraliaCrawleyAustralia
  4. 4.Cloud Computing and Distributed Systems (CLOUDS) Lab, School of Computing and Information SystemsThe University of MelbourneMelbourneAustralia

Personalised recommendations