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Neighborhood-aware Mobile Hub: An Edge Gateway with Leader Election Mechanism for Internet of Mobile Things

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Abstract

Internet of Things (IoT) is the interconnection of thousands of heterogeneous addressable smart objects (i.e., devices embedded with sensors and actuators) with Internet connectivity. Internet of Mobile Things (IoMT) is characterized by considering the mobility of smart objects. For managing smart objects, it is necessary to provide a middleware. Mobile Hub (M-Hub) is an IoT middleware that collects, processes and distributes data from a large number of smart objects on the edge of the network. M-Hub runs on mobile devices, enabling them to be gateways. It represents an autonomous entity, able to detect a set of objects available in the neighborhood and to monitor them independently of other M-Hubs. Hence, in some situations it may happen that a same object is eligible to be monitored by several M-Hubs. In this context, this paper proposes Neighborhood-aware M-Hub (NAM-Hub), a leader election mechanism integrated to the M-Hub to determine a suitable gateway for each smart object discovered opportunistically. It considers context data gathered from the mobile device to dynamically elect leaders (i.e., a leader and a sub-leader). The proposed solution contributes to take advantage from the resources provided for the mobile gateway and avoids their wastage. The proposed leader election mechanism was tested and evaluated considering its performance and the results were promising, with short detection time and recovery time in the system.

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References

  1. Esper – EsperTech. http://www.espertech.com/esper/. Accessed 20 February 2020

  2. Google Gson. https://github.com/google/gson. Accessed 20 February 2020

  3. iBeacon – Apple Developer. https://developer.apple.com/ibeacon/. Accessed 20 February 2020

  4. Mi Smart Band 4 – Mi Global Home. https://www.mi.com/global/mi-smart-band-4. Accessed 20 February 2020

  5. Wi-Fi Aware – Wi-Fi Alliance. https://www.wi-fi.org/discover-wi-fi/wi-fi-aware. Accessed 25 February 2020

  6. Zephyr. https://www.zephyranywhere.com/system/components. Accessed 20 February 2020

  7. Al-Fuqaha A, Guizani M, Mohammadi M, Aledhari M, Ayyash M (2015) Internet of things: a survey on enabling technologies, protocols, and applications. IEEE Commun Surv Tutorial 17(4):2347–2376. https://doi.org/10.1109/COMST.2015.2444095

    Article  Google Scholar 

  8. Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54 (15):2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010

    Article  MATH  Google Scholar 

  9. Bounceur A, Bezoui M, Euler R, Kadjouh N, Lalem F (2017) Brogo: a new low energy consumption algorithm for leader election in wsns. In: 2017 10Th international conference on developments in esystems engineering (deSE), pp 218–223. https://doi.org/10.1109/DeSE.2017.11

  10. Bounceur A, Bezoui M, Euler R, Lalem F, Lounis M (2017) A revised brogo algorithm for leader election in wireless sensor and iot networks. In: 2017 IEEE SENSORS, pp 1–3. https://doi.org/10.1109/ICSENS.2017.8234400

  11. Camps-Mur D, Garcia-Villegas E, Lopez-Aguilera E, Loureiro P, Lambert P, Raissinia A (2015) Enabling always on service discovery: Wifi neighbor awareness networking. IEEE Wirel Commun 22 (2):118–125. https://doi.org/10.1109/MWC.2015.7096294

    Article  Google Scholar 

  12. Capra M, Peloso R, Masera G, Ruo Roch M, Martina M (2019) Edge computing: A survey on the hardware requirements in the internet of things world. Fut Internet 11(4). https://doi.org/10.3390/fi11040100

  13. Chen W, Toueg S, Aguilera MK (2002) On the quality of service of failure detectors. IEEE Trans Comput 51(1):13–32. https://doi.org/10.1109/12.980014

    Article  MathSciNet  MATH  Google Scholar 

  14. Cugola G, Margara A (2012) Processing flows of information: From data stream to complex event processing. ACM Comput Surv 44(3):15:1–15:62. https://doi.org/10.1145/2187671.2187677

    Article  Google Scholar 

  15. daCosta F (2013) Rethinking the Internet of Things: A Scalable Approach to Connecting Everything, 1st edn. Apress, Berkely

  16. David L, Vasconcelos R, Alves L, André R, Endler M (2013) A dds-based middleware for scalable tracking, communication and collaboration of mobile nodes. Jo Internet Serv Appl 4(1). https://doi.org/10.1186/1869-0238-4-16

  17. Dragan R, Ciobanu R, Dobre C (2017) Leader election in opportunistic networks. In: 2017 16Th international symposium on parallel and distributed computing (ISPDC), pp 157–164. https://doi.org/10.1109/ISPDC.2017.10

  18. El-Refaay S, Azer MA, Abdelbaki N (2014) Cluster head election in wireless sensor networks. In: 10Th international conference on information assurance and security, pp 1–5. https://doi.org/10.1109/ISIAS.2014.7064625

  19. Endler M, e Silva FS (2018) Past, present and future of the contextnet iomt middleware. Open J Internet Things (OJIOT) 4(1):7–23

    Google Scholar 

  20. Faika T, Kim T, Khan M (2018) An internet of things (iot)-based network for dispersed and decentralized wireless battery management systems. In: 2018 IEEE Transportation electrification conference and expo (ITEC), pp 1060–1064. https://doi.org/10.1109/ITEC.2018.8450161

  21. Fernández-Campusano C, Larrea M, Cortinas R, Raynal M (2015) Eventual leader election despite crash-recovery and omission failures. In: 2015 IEEE 21St pacific rim international symposium on dependable computing (PRDC), pp 209–214. https://doi.org/10.1109/PRDC.2015.18

  22. Ganti RK, Ye F, Lei H (2011) Mobile crowdsensing: current state and future challenges. IEEE Commun Mag 49(11):32–39. https://doi.org/10.1109/MCOM.2011.6069707

    Article  Google Scholar 

  23. Garcia-Molina H (1982) Elections in a distributed computing system. IEEE Trans Comput 31 (1):48–59. https://doi.org/10.1109/TC.1982.1675885

    Article  Google Scholar 

  24. Gharehchopogh FS, Arjang H (2014) A survey and taxonomy of leader election algorithms in distributed systems. Ind J Sci Technol 7(6)

  25. Gomes BDTP, Muniz LCM, Da Silva e Silva, FJ, Dos Santos DV, Lopes RF, Coutinho LR, Carvalho FO, Endler M (2017) A middleware with comprehensive quality of context support for the internet of things applications. Sensors 17(12). https://doi.org/10.3390/s17122853

  26. Goncalves JF, Da Silva e Silva, FJ, Vasconcelos R, Baptista GLB, Endler M (2013) A security infrastructure for massive mobile data distribution. In: Proceedings of the 11th ACM international symposium on Mobility management and wireless access, pp 41–50. https://doi.org/10.1145/2508222.2508237

  27. Goudos SK, Dallas PI, Chatziefthymiou S, Kyriazakos S (2017) A survey of iot key enabling and future technologies: 5g, mobile iot, sematic web and applications. Wirel Pers Commun 97(2):1645–1675. https://doi.org/10.1007/s11277-017-4647-8

    Article  Google Scholar 

  28. Hassan N, Gillani S, Ahmed E, Yaqoob I, Imran M (2018) The role of edge computing in internet of things. IEEE Commun Mag 56(11):110–115. https://doi.org/10.1109/MCOM.2018.1700906

    Article  Google Scholar 

  29. Jain R (1991) The art of computer systems performance analysis: Techniques for experimental design, Measurement, Simulation, and Modeling. Wiley, New York

  30. Jiang Y (2016) A survey of task allocation and load balancing in distributed systems. IEEE Trans Parallel Distrib Syst 27(2):585–599. https://doi.org/10.1109/TPDS.2015.2407900

    Article  Google Scholar 

  31. Kamilaris A, Pitsillides A (2016) Mobile phone computing and the internet of things: a survey. IEEE Internet Things J 3(6):885–898. https://doi.org/10.1109/JIOT.2016.2600569

    Article  Google Scholar 

  32. Lane ND, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell AT (2010) A survey of mobile phone sensing. IEEE Commun Mag 48(9):140–150. https://doi.org/10.1109/MCOM.2010.5560598

    Article  Google Scholar 

  33. Liu J, Shen H, Narman HS, Chung W, Lin Z (2018) A survey of mobile crowdsensing techniques: a critical component for the internet of things. ACM Trans Cyber-Phys Syst 2(3):1–26. https://doi.org/10.1145/3185504

    Article  Google Scholar 

  34. Ma T, Hillston J, Anderson S (2010) On the quality of service of crash-recovery failure detectors. IEEE Trans Depend Sec Comput 7(3):271–283. https://doi.org/10.1109/TDSC.2009.35

    Article  Google Scholar 

  35. Mao S, Zhao C, Zhou Z, Ye Y (2013) An improved fuzzy unequal clustering algorithm for wireless sensor network. Mob Netw Appl 18(2):206–214. https://doi.org/10.1007/s11036-012-0356-4

    Article  Google Scholar 

  36. Masi AD (2015) Load balancing in p2p smartphone based distributed iot systems. Master’s thesis, Luleȧ University of Technology

  37. Meslin A, Rodriguez N, Endler M (2020) Scalable mobile sensing for smart cities: The musanet experience. IEEE Internet of Things Journal. https://doi.org/10.1109/JIOT.2020.2977298

  38. Miorandi D, Sicari S, De Pellegrini F, Chlamtac I (2012) Internet of things: vision, applications and research challenges. Ad hoc Netw 10(7):1497–1516. https://doi.org/10.1016/j.adhoc.2012.02.016

    Article  Google Scholar 

  39. Nahrstedt K, Li H, Nguyen P, Chang S, Vu L (2016) Internet of mobile things: Mobility-driven challenges, designs and implementations. In: 2016 IEEE First international conference on internet-of-things design and implementation (ioTDI), pp 25–36. https://doi.org/10.1109/IoTDI.2015.41

  40. Salman O, Elhajj I, Chehab A, Kayssi A (2018) Iot survey: an sdn and fog computing perspective. Comput Netw 143:221–246. https://doi.org/10.1016/j.comnet.2018.07.020

    Article  Google Scholar 

  41. Santana EFZ, Chaves AP, Gerosa MA, Kon F, Milojicic DS (2017) Software platforms for smart cities: concepts, requirements, challenges, and a unified reference architecture. ACM Comput Sureys 50 (6):78:1–78:37. https://doi.org/10.1145/3124391

    Google Scholar 

  42. Sindhanaiselvan K, Mannan JM, Aruna SK (2019) Designing a dynamic topology (dht) for cluster head selection in mobile adhoc network. Mobile Networks and Applications. https://doi.org/10.1007/s11036-019-01283-x

  43. Singh KJ, Kapoor DS (2017) Create your own internet of things: a survey of iot platforms. IEEE Consum Electron Mag 6(2):57–68. https://doi.org/10.1109/MCE.2016.2640718

    Article  Google Scholar 

  44. Talavera LE, Endler M, Vasconcelos I, Vasconcelos R, Cunha M, Da Silva e Silva, FJ (2015) The mobile hub concept: Enabling applications for the internet of mobile things. In: 2015 IEEE International conference on pervasive computing and communication workshops (percom workshops), pp 123–128. https://doi.org/10.1109/PERCOMW.2015.7134005

  45. Vasudevan S, Kurose J, Towsley D (2004) Design and analysis of a leader election algorithm for mobile ad hoc networks. In: Proceedings of the 12th IEEE International Conference on Network Protocols, pp 350–360. https://doi.org/10.1109/ICNP.2004.1348124

  46. Véstias M. P., Duarte RP, de Sousa JT, Neto HC (2020) Moving deep learning to the edge Algorithms 13(5). https://doi.org/10.3390/a13050125

  47. Zhang B, Liu G, Hu B (2010) The coordination of nodes in the internet of things. In: 2010 International conference on information, networking and automation (ICINA), vol 2, pp v2–299–v2–302. https://doi.org/10.1109/ICINA.2010.5636506

  48. Zhou Z, Chen X, Li E, Zeng L, Luo K, Zhang J (2019) Edge intelligence: Paving the last mile of artificial intelligence with edge computing. Proc IEEE 107(8):1738–1762. https://doi.org/10.1109/JPROC.2019.2918951

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank FAPEMA (State of Maranhão Research Funding Agency) for supporting their research projects. This research is part of the INCT of the Future Internet for Smart Cities funded by CNPq proc. 465446/2014-0, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, FAPESP proc. 14/50937-1, and FAPESP proc. 15/24485-9.

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Authors and Affiliations

  1. Federal University of Maranhão, MA, Brazil

    Marcelino Silva, Rafael Lopes, Francisco Silva, Davi Viana & Luciano Coutinho

  2. Federal Institute of Maranhão, MA, Brazil

    Ariel Teles

  3. Vaagdevi College of Engineering, Warangal, India

    Nishu Gupta

  4. Pontifícia Universidade Católica do Rio de Janeiro, RJ, Brazil

    Markus Endler

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  1. Marcelino Silva
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Correspondence to Ariel Teles.

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Silva, M., Teles, A., Lopes, R. et al. Neighborhood-aware Mobile Hub: An Edge Gateway with Leader Election Mechanism for Internet of Mobile Things. Mobile Netw Appl 27, 276–289 (2022). https://doi.org/10.1007/s11036-020-01630-3

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