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Dew Computing-Based Sustainable Internet of Vehicular Things

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Dew Computing

Part of the book series: Internet of Things ((ITTCC))

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Abstract

The present chapter investigates some future research cases, themes, and directions in vehicular dew computing. Dew computing is a paradigm for organizing the software and hardware of on-premises computers in a cloud computing architecture. The on-the-spot computer offers services that work independently from the cloud. It seeks to maximize the capabilities of computers on-site and cloud services. Thus it combines the concept of cloud computing with edge computing. Cloud/Fog/Edge depends on Internet connectivity. Today’s transportation and routing decisions depend on intelligent technologies. In dynamic vehicle routing and procurement planning, the Internet connectivity problem is the most important because we make a decision depending on real time, and its availability in rural/semi-urban areas is limited. To address these challenges, this investigation proposes a novel dew-caching architecture under the cloud using the Internet of vehicular things (IoVs) in different practical applications such as smart logistic routing, disaster management, etc. Also, dew computing plays a significant role in this situation. This allows the user to access the services, files, and resources when there is disrupted Internet connectivity, and then the files and resources are synced back to the cloud server when the connection is made again. The end-user gets additional freedom to retrieve essential data using dew computing. When Internet access is available, the data is synced with the master copy at the cloud server as well as in the dew server located on the user’s device. Users can read, write, update, and remove data on their smartphone, which functions as a localized version of a real server. The present study gives some novel areas of applications in dew computing utilizing caching in the Internet of vehicular things.

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Notes

  1. 1.

    https://economictimes.indiatimes.com/tech/newsletters/ettech-unwrapped/indias-dubious-record-on-internet-shutdowns-set-to-continue/articleshow/94105055.cms?from=mdr.

References

  1. Ahmed, Z.E., Hasan, M.K., Saeed, R.A., Hassan, R., Islam, S., Mokhtar, R.A., Khan, S., Akhtaruzzaman, M.: Optimizing energy consumption for cloud internet of things. Front. Phys. 8, 358 (2020)

    Google Scholar 

  2. Amadeo, M., Campolo, C., Molinaro, A.: Priority-based content delivery in the internet of vehicles through named data networking. J. Sens. Actuator Netw. 5(4), 17 (2016)

    Article  Google Scholar 

  3. Alrawais, A., Alhothaily, A., et al.: Fog computing for the internet of things: security and privacy issues. IEEE Internet Comput. 21(2), 34–42 (2017)

    Google Scholar 

  4. Behbehani, F.S., El-Gorashi, T.E., Elmirghani, J.M.: Optimized processing placement over a vehicular cloud. IEEE Access 10, 41411–41428 (2022)

    Google Scholar 

  5. Bhatia, T., Verma, A.K.: Data security in mobile cloud computing paradigm: a survey, taxonomy and open research issues. J. Supercomput. 73(6), 2558–2631 (2017)

    Google Scholar 

  6. Chai, S., Lau, V.K.N.: Online trajectory and radio resource optimization of cache-enabled UAV wireless networks with content and energy recharging. IEEE Trans. Signal Process. 68, 1286–1299 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  7. Chen, C., Xiang, H., Qiu, T., Wang, C., Zhou, Y., Chang, V.: A rear-end collision prediction scheme based on deep learning in the internet of vehicles. J. Parall. Distrib. Comput. 117, 192–204 (2018)

    Article  Google Scholar 

  8. Chen, M., Mozaffari, M., Saad, W., Yin, C., Debbah, M., Hong, C.S.: Caching in the sky: proactive deployment of cache-enabled unmanned aerial vehicles for optimized quality-of-experience. IEEE J. Sel. Areas Commun. 35(5), 1046–1061 (2017)

    Google Scholar 

  9. Chen, Z., Kountouris, M.: D2D caching versus small cell caching: where to cache content in a wireless network? In: 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), pp. 1–6. IEEE (2016)

    Google Scholar 

  10. Dai, Y., Xu, D., Maharjan, S., Qiao, G., Zhang, Y.: Artificial intelligence empowered edge computing and caching for internet of vehicles. IEEE Wirel. Commun. 26(3), 12–18 (2019)

    Google Scholar 

  11. Das, M., Roy, A., Maity, S., Kar, S.: A quantum-inspired ant colony optimization for solving a sustainable four-dimensional traveling salesman problem under type-2 fuzzy variable. Adv. Eng. Inform. 55, 101816 (2023)

    Article  Google Scholar 

  12. Dijkstra, E.W.: A note on two problems in connexion with graphs. In: Edsger Wybe Dijkstra: his Life, Work, and Legacy, pp. 287–290. Springer (2022)

    Google Scholar 

  13. Fu, L.: An adaptive routing algorithm for in-vehicle route guidance systems with real-time information. Transp. Res. Part B: Methodol. 35(8), 749–765 (2001)

    Google Scholar 

  14. Goudarzi, F., Asgari, H., Al-Raweshidy, H.S.: Traffic-aware VANET routing for city environments-a protocol based on ant colony optimization. IEEE Syst. J. 13(1), 571–581 (2018)

    Google Scholar 

  15. Guo, Y., Yang, Q., Yu, F.R., Leung, V.C.: Cache-enabled adaptive video streaming over vehicular networks: a dynamic approach. IEEE Trans. Veh. Technol. 67(6), 5445–5459 (2018)

    Google Scholar 

  16. Gusev, M.: A dew computing solution for IoT streaming devices. In: 2017 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 387–392. IEEE (2017)

    Google Scholar 

  17. Gusev, M.: What makes dew computing more than edge computing for internet of things. In: 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), pp. 1795–1800. IEEE (2021)

    Google Scholar 

  18. Gusev, M., Wang, Y.: Formal description of dew computing. In: Proceedings of The 3rd International Workshop on Dew Computing, pp. 8–13 (2018)

    Google Scholar 

  19. Gushev, M.: Dew computing architecture for cyber-physical systems and IoT. Internet Things 11, 100186 (2020)

    Article  Google Scholar 

  20. Han, K.-H., Kim, J.-H.: Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. IEEE Trans. Evol. Comput. 6(6), 580–593 (2002)

    Article  Google Scholar 

  21. Fida Hasan, K., Kaur, T., Mhedi Hasan, M., Feng, Y.: Cognitive internet of vehicles: motivation, layered architecture and security issues. In: 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI), pp. 1–6. IEEE (2019)

    Google Scholar 

  22. Hasan, M.K., Ismail, A.F., Abdalla, A.H., Ramli, H.A., Hashim, W., Islam, S.: Throughput maximization for the cross-tier interference in heterogeneous network. Adv. Sci. Lett. 22(10), 2785–2789 (2016)

    Google Scholar 

  23. Hindustantimes.: FDI rules in food retail (2022)

    Google Scholar 

  24. Hou, L., Lei, L., Zheng, K., Wang, X.: A q-learning-based proactive caching strategy for non-safety related services in vehicular networks. IEEE Internet Things J. 6(3), 4512–4520 (2018)

    Google Scholar 

  25. Javed, M.A., Zeadally, S.: Ai-empowered content caching in vehicular edge computing: opportunities and challenges. IEEE Netw. 35(3), 109–115 (2021)

    Google Scholar 

  26. Karp, B., Kung, H.T.: GPSR: greedy perimeter stateless routing for wireless networks. In: Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, pp. 243–254 (2000)

    Google Scholar 

  27. Li, H., Zhang, J., Zhao, L.: Vehicular high-definition maps cache based on dew computing. In: 2022 9th International Conference on Dependable Systems and Their Applications (DSA), pp. 1067–1068. IEEE (2022)

    Google Scholar 

  28. Lochert, C., Hartenstein, H., Tian, J., Fussler, H., Hermann, D., Mauve, M.: A routing strategy for vehicular ad hoc networks in city environments. In: IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No. 03TH8683), pp. 156–161. IEEE (2003)

    Google Scholar 

  29. Lv, Z., Chen, D., Wang, Q.: Diversified technologies in internet of vehicles under intelligent edge computing. IEEE Trans. Intell. Transp. Syst. 22(4), 2048–2059 (2020)

    Article  Google Scholar 

  30. Mane, T.S., Agrawal, H.: Cloud-fog-dew architecture for refined driving assistance: the complete service computing ecosystem. In: 2017 IEEE 17th International Conference on Ubiquitous Wireless Broadband (ICUWB), pp. 1–7. IEEE (2017)

    Google Scholar 

  31. Marinescu, D.C.: Cloud Computing: theory and Practice. Morgan Kaufmann (2022)

    Google Scholar 

  32. Martuscelli, G., Boukerche, A., Foschini, L., Bellavista, P.: V2v protocols for traffic congestion discovery along routes of interest in VANETS: a quantitative study. Wirel. Commun. Mob. Comput. 16(17), 2907–2923 (2016)

    Article  Google Scholar 

  33. Meng, Z., Guan, Z., Wu, Z., Li, A, Chen, Z.: Security enhanced internet of vehicles with cloud-fog-dew computing. ZTE Commun. 15(S2), 47–51 (2020)

    Google Scholar 

  34. Mohammed, C.M., Zeebaree, S.R., et al.: Sufficient comparison among cloud computing services: IaaS, PaaS, and SaaS: a review. Int. J. Sci. Bus. 5(2), 17–30 (2021)

    Google Scholar 

  35. Mulay, P., Kadlag, S., Shirodkar, R.: Smart supply-chain management learning system for homeopathy. Indian J. Publ. Health Res. Dev. 8(4) (2017)

    Google Scholar 

  36. Nguyen, T.N.: The challenges in ml-based security for SDN. In: 2018 2nd Cyber Security in Networking Conference (CSNet), pp. 1–9. IEEE (2018)

    Google Scholar 

  37. Ning, Z., Huang, J., Wang, X., Rodrigues, J.J.P.C., Guo, L.: Mobile edge computing-enabled internet of vehicles: toward energy-efficient scheduling. IEEE Netw. 33(5), 198–205 (2019)

    Google Scholar 

  38. Pan, Y., Thulasiraman, p., Wang, Y.: Overview of cloudlet, fog computing, edge computing, and dew computing. In: Proceedings of The 3rd International Workshop on Dew Computing, pp. 20–23 (2018)

    Google Scholar 

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

    Google Scholar 

  40. Patel, H.M., Chaudhari, R.R., Prajapati, K.R., Patel, A.A.: The interdependent part of cloud computing: dew computing. In: Intelligent Communication and Computational Technologies, pp. 345–355. Springer (2018)

    Google Scholar 

  41. Pradhan, K., Basu, S., Thakur, K., Maity, S., Maiti, M.: Imprecise modified solid green traveling purchaser problem for substitute items using quantum-inspired genetic algorithm. Comput. Ind. Eng. 147, 106578 (2020)

    Article  Google Scholar 

  42. Ramesh, T.: Traveling purchaser problem. Opsearch 18(1–3), 78–91 (1981)

    MATH  Google Scholar 

  43. Ray, P.P.: An introduction to dew computing: definition, concept and implications. IEEE Access 6, 723–737 (2017)

    Google Scholar 

  44. Rindos, A., Wang, Y.: Dew computing: the complementary piece of cloud computing. In: 2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom) (BDCloud-SocialCom-SustainCom), pp. 15–20. IEEE (2016)

    Google Scholar 

  45. Skala, K., Davidovic, D., Afgan, E., Sovic, I., Sojat, Z.: Scalable distributed computing hierarchy: cloud, fog and dew computing. Open J. Cloud Comput. (OJCC) 2(1), 16–24 (2015)

    Google Scholar 

  46. Šojat, Z., Skala, K.: Views on the role and importance of dew computing in the service and control technology. In: 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 164–168. IEEE (2016)

    Google Scholar 

  47. Suwansrikham, P., Kun, S., Hayat, S., Jackson, J.: Dew computing and asymmetric security framework for big data file sharing. Information 11(6), 303 (2020)

    Article  Google Scholar 

  48. Talbi, H., Draa, A., Batouche, M.: A new quantum-inspired genetic algorithm for solving the travelling salesman problem. In: 2004 IEEE International Conference on Industrial Technology, 2004. IEEE ICIT’04, vol. 3, pp. 1192–1197. IEEE (2004)

    Google Scholar 

  49. Tefera, G., She, K., Shelke, M., Ahmed, A.: Decentralized adaptive resource-aware computation offloading & caching for multi-access edge computing networks. Sustain. Comput.: Inform. Syst. 30, 100555 (2021)

    Google Scholar 

  50. Toth, P., Vigo, D.: Vehicle Routing: problems, Methods, and Applications. SIAM (2014)

    Google Scholar 

  51. Wang, H., Liu, T., Kim, B., Lin, C.-W., Shiraishi, S., Xie, J., Han, Z.: Architectural design alternatives based on cloud/edge/fog computing for connected vehicles. IEEE Commun. Surv. Tutor. 22(4), 2349–2377 (2020)

    Article  Google Scholar 

  52. Wang, J., Osagie, E., Thulasiraman, p., Thulasiram, R.K.: Hopnet: a hybrid ant colony optimization routing algorithm for mobile ad hoc network. Ad Hoc Netw. 7(4), 690–705 (2009)

    Google Scholar 

  53. Wang, X., Leng, S., Yang, K.: Social-aware edge caching in fog radio access networks. IEEE Access 5, 8492–8501 (2017)

    Article  Google Scholar 

  54. Wang, Y.: Definition and categorization of dew computing. Open J. Cloud Comput. (OJCC) 3(1), 1–7 (2016)

    Google Scholar 

  55. Wang, Y.: A disaster-resilient messaging protocol based on dew computing. In: 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), pp. 1922–1926. IEEE (2020)

    Google Scholar 

  56. Wang, Y., Pan, Y.: Cloud-dew architecture: realizing the potential of distributed database systems in unreliable networks. In: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA), pp. 85. The Steering Committee of The World Congress in Computer Science, Computer (2015)

    Google Scholar 

  57. Wang, Z., Liu, Y.Y., Thulasiraman, P., Thulasiram, R.K.: Ant brood clustering on intel XEON multi-core: Challenges and strategies. In: 2018 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1126–1233. IEEE (2018)

    Google Scholar 

  58. Wu, H., Lyu, F., Zhou, C., Chen, J., Wang, L., Shen, X.: Optimal UAV caching and trajectory in aerial-assisted vehicular networks: a learning-based approach. IEEE J. Sel. Areas Commun. 38(12), 2783–2797 (2020)

    Google Scholar 

  59. Yao, L., Chen, A., Deng, J., Wang, J., Guowei, W.: A cooperative caching scheme based on mobility prediction in vehicular content centric networks. IEEE Trans. Veh. Technol. 67(6), 5435–5444 (2017)

    Article  Google Scholar 

  60. Yu, Y.-C.: A dew computing architecture for smart parking system with cloud image recognition service. In: 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), pp. 1805–1809. IEEE (2021)

    Google Scholar 

  61. Zeadally, S., Javed, M.A., Hamida, E.B.: Vehicular communications for its: standardization and challenges. IEEE Commun. Stand. Mag. 4(1), 11–17 (2020)

    Google Scholar 

  62. Zhang, K., Leng, S., He, Y., Maharjan, S., Zhang, Y.: Cooperative content caching in 5g networks with mobile edge computing. IEEE Wirel. Commun. 25(3), 80–87 (2018)

    Article  Google Scholar 

  63. Zhang, K., Zhu, Y., Leng, S., He, Y., Maharjan, S., Zhang, Y.: Deep learning empowered task offloading for mobile edge computing in urban informatics. IEEE Internet Things J. 6(5), 7635–7647 (2019)

    Article  Google Scholar 

  64. Zhao, Y., Li, Y., Zhang, X., Geng, G., Zhang, W., Sun, Y.: A survey of networking applications applying the software defined networking concept based on machine learning. IEEE Access 7, 95397–95417 (2019)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Haringhata, Nadia, West Bengal, 741249, India

    Sushovan Khatua & Debashis De

  2. Università degli Studi di Brescia, 25123, Brescia, Italy

    Daniele Manerba

  3. Department of Materials and Production, Operations, Research Group, Aalborg University, Aalborg, 9220, Denmark

    Samir Maity

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  1. Sushovan Khatua
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  2. Daniele Manerba
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Correspondence to Sushovan Khatua .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, West Bengal, Kolkata, India

    Debashis De

  2. Department of Computer Science and Engineering, D Y Patil International University, Pune, India

    Samarjit Roy

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Khatua, S., Manerba, D., Maity, S., De, D. (2024). Dew Computing-Based Sustainable Internet of Vehicular Things. In: De, D., Roy, S. (eds) Dew Computing. Internet of Things. Springer, Singapore. https://doi.org/10.1007/978-981-99-4590-0_9

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