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An Improved Ant Colony Optimization Based Parking Algorithm with Graph Coloring

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Advanced Information Networking and Applications (AINA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 451))

Abstract

In an era which is going towards the spread of smart cities and intelligent transportation systems, vehicular ad hoc networks are an interesting framework to propose innovative solutions. One of the most tedious problems for drivers in a urban environment is the parking process. Indeed, drivers looking for an available parking slot keep being the main cause of traffic congestion, which also involves a high stress and air pollution level. In this work, we provide a smart parking solution, aiming at a higher context awareness for drivers, by relying on a well known optimization problem, the ant colony. By choosing an opportune criterion to update the pheromone, we push drivers to choose possibly uncrowded paths, ending up with a solution which guarantees a fair node distribution with respect to the available parking slots.

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References

  1. Greengard, S.: The Internet of Things. MIT Press (2021)

    Google Scholar 

  2. Wiseman, Y.: Autonomous vehicles. In: Research Anthology on Cross-Disciplinary Designs and Applications of Automation, pp. 878–889. IGI Global (2022)

    Google Scholar 

  3. Ghazal, T.M., et al.: IoT for smart cities: machine learning approaches in smart healthcare-a review. Future Internet 13(8), 218 (2021)

    Article  Google Scholar 

  4. Lapegna, M., Stranieri, S.: DClu: a direction-based clustering algorithm for VANETs management. In: Barolli, L., Yim, K., Chen, H.C. (eds.) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2021. Lecture Notes in Networks and Systems, vol. 279, pp. 253–262. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-79728-7_25

  5. Alsarhan, A., Al-Ghuwairi, A.R., Almalkawi, I.T., Alauthman, M., Al-Dubai, A.: Machine learning-driven optimization for intrusion detection in smart vehicular networks. Wirel. Pers. Commun. 117(4), 3129–3152 (2021)

    Article  Google Scholar 

  6. Di Luccio, D., et al.: Coastal marine data crowdsourcing using the internet of floating thingsithe results of a water quality model. IEEE Access 8, 101209–101223 (2020)

    Article  Google Scholar 

  7. Romano, D., Lapegna, M.: A GPU-parallel image coregistration algorithm for InSar processing at the edge. Sensors 21(17), 5916 (2021)

    Article  Google Scholar 

  8. Statista: Proportion of population in cities worldwide from 1985 to 2050 (2021)

    Google Scholar 

  9. Pope Iii, C.A., et al.: Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. Jama 287(9), 1132–1141 (2002)

    Article  Google Scholar 

  10. Shahzad, A., Choi, J., Xiong, N., Kim, Y.-G., Lee, M.: Centralized connectivity for multiwireless edge computing and cellular platform: a smart vehicle parking system. Wirel. Commun. Mob. Comput. 2018 (2018)

    Google Scholar 

  11. Singh, P.K., Singh, R., Nandi, S.K., Nandi, S.: Smart contract based decentralized parking management in ITS. In: Lüke, KH., Eichler, G., Erfurth, C., Fahrnberger, G. (eds.) Innovations for Community Services. I4CS 2019. Communications in Computer and Information Science, vol. 1041, pp. 66–77. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-22482-0_6

  12. Amato, F., Casola, V., Gaglione, A., Mazzeo, A.: A semantic enriched data model for sensor network interoperability. Simul. Model. Pract. Theory 19(8), 1745–1757 (2011)

    Article  Google Scholar 

  13. Yousefi, S., Mousavi, M.S., Fathy, M.: Vehicular ad hoc networks (VANETs): challenges and perspectives. In: 2006 6th International Conference on ITS Telecommunications, pp. 761–766. IEEE (2006)

    Google Scholar 

  14. Naskath, J., Paramasivan, B., Aldabbas, H.: A study on modeling vehicles mobility with MLC for enhancing vehicle-to-vehicle connectivity in VANET. J. Ambient Intell. Hum. Comput. 12(8), 8255–8264 (2021)

    Google Scholar 

  15. Ghaffari, A.: Hybrid opportunistic and position-based routing protocol in vehicular ad hoc networks. J. Ambient Intell. Hum. Comput. 11(4), 1593–1603 (2020)

    Article  Google Scholar 

  16. Sepulcre, M., Gozalvez, J., Härri, J., Hartenstein, H.: Contextual communications congestion control for cooperative vehicular networks. IEEE Trans. Wirel. Commun. 10(2), 385–389 (2010)

    Article  Google Scholar 

  17. Yaqoob, S., Ullah, A., Akbar, M., Imran, M., Shoaib, M.: Congestion avoidance through fog computing in internet of vehicles. J. Ambient Intell. Humaniz. Comput. 10(10), 3863–3877 (2019). https://doi.org/10.1007/s12652-019-01253-x

    Article  Google Scholar 

  18. Wang, X., Shi, H., Zhang, C.: Path planning for intelligent parking system based on improved ant colony optimization. IEEE Access 8, 65267–65273 (2020)

    Article  Google Scholar 

  19. Dorigo, M., Blum, C.: Ant colony optimization theory: a survey. Theor. Comput. Sci. 344(2–3), 243–278 (2005)

    Article  MathSciNet  Google Scholar 

  20. Balzano, W., Stranieri, S.: ACOp: an algorithm based on ant colony optimization for parking slot detection. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds.) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol. 927, pp. 833–840. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-15035-8_81

  21. Viet, N.H., Vien, N.A., Lee, S.G., Chung, T.C.: Obstacle avoidance path planning for mobile robot based on multi colony ANT algorithm. In: First International Conference on Advances in Computer-Human Interaction, pp. 285–289. IEEE (2008)

    Google Scholar 

  22. Mamandi, A., Yousefi, S., Atani, R.E.: Game theory-based and heuristic algorithms for parking-IoT search. In: 2015 International Symposium on Computer Science and Software Engineering (CSSE), pp. 1–8. IEEE (2015)

    Google Scholar 

  23. Amato, F., Casola, V., Mazzeo, A., and Romano, S.: A semantic based methodology to classify and protect sensitive data in medical records. In: 2010 Sixth International Conference on Information Assurance and Security, pp. 240–246. IEEE (2010)

    Google Scholar 

  24. Amato, F., Casola, V., Mazzocca, N., Romano, S.: A semantic approach for fine-grain access control of e-health documents. Log. J. IGPL 21(4), 692–701 (2013)

    Article  MathSciNet  Google Scholar 

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Acknowledgments

This paper has been produced with the financial support of the Justice Programme of the European Union, 101046629 CREA2, JUST-2021-EJUSTICE, JUST2027 Programme. The contents of this report are the sole responsibility of the authors and can in no way be taken to reflect the views of the European Commission.

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Authors and Affiliations

  1. University of Naples Federico II, Naples, Italy

    Marco Agizza, Walter Balzano & Silvia Stranieri

Authors
  1. Marco Agizza
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  2. Walter Balzano
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  3. Silvia Stranieri
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Corresponding author

Correspondence to Walter Balzano .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. University of Technology Sydney, Sydney, NSW, Australia

    Farookh Hussain

  3. Faculty of Bussiness Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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Agizza, M., Balzano, W., Stranieri, S. (2022). An Improved Ant Colony Optimization Based Parking Algorithm with Graph Coloring. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 451. Springer, Cham. https://doi.org/10.1007/978-3-030-99619-2_8

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