Enhancing Smart Cities with IoT and Cloud Computing: A Study on Integrating Wireless Ad Hoc Networks for Efficient Communication

Main Article Content

Haider Mohammed Abdulhadi
Yousra Abdul Alsahib S. Aldeen
Maryam A. Yousif
Mays jalal jaseem
Syed Hamid Hussain Madni
https://orcid.org/0000-0002-3816-1382

Abstract

Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things, which enables gadgets to connect with one another mostly without human involvement, is made possible by AI. In line with this, The Ad Hoc Routing Function (ARF) AI computation is used for multi-rule simplification, the use of Adaptive Cloud Computing Virtual Machine Asset Allotment Technique (ACC-VMRA) is advised. To confirm its viability, the applied developments of IoT and CC in smart cities is examined and duplicated. The experiment results show that the recommended enhancement calculation is more productive than other currently used methods.

Article Details

How to Cite
1.
Enhancing Smart Cities with IoT and Cloud Computing: A Study on Integrating Wireless Ad Hoc Networks for Efficient Communication. Baghdad Sci.J [Internet]. 2023 Dec. 5 [cited 2024 Dec. 19];20(6(Suppl.):2672. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/9277
Section
article

How to Cite

1.
Enhancing Smart Cities with IoT and Cloud Computing: A Study on Integrating Wireless Ad Hoc Networks for Efficient Communication. Baghdad Sci.J [Internet]. 2023 Dec. 5 [cited 2024 Dec. 19];20(6(Suppl.):2672. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/9277

References

Hameed A, Violos J, Leivadeas A. A deep learning approach for IOT traffic multi-classification in a smart-city scenario. IEEE Access. 2022; 10: 21193–210. https://doi.org/10.1109/access.2022.3153331

Nathali B, Jung C, Kang J, Seo J, Kim J, Han K, et al. Planning of Smart Cities Performance Improvement Using Big Data Analytics approach. 4th Int Conf Adv Comput Commun. Electronics and Communication. ACEC 2016. 2016; https://doi.org/10.15224/978-1-63248-113-9-11

Javadzadeh G, Rahmani AM. Fog computing applications in smart cities: A systematic survey. Wirel. Netw. 2019; 26(2): 1433–57. https://doi.org/10.1007/s11276-019-02208-y

Chen X, Liu Z, Chen Y, Li Z. Mobile edge computing based task offloading and resource allocation in 5G Ultra-Dense Networks. IEEE Access. 2019; 7: 184172–82. https://doi.org/10.1109/access.2019.2960547

Abdulwahid HM, Mishra A. Deployment Optimization Algorithms in Wireless Sensor Networks for Smart Cities: A Systematic Mapping Study. Sensors. 2022 Jul 7; 22(14): 5094. https://doi.org/10.3390/s22145094

Shamshirband S, Fathi M, Chronopoulos AT, Montieri A, Palumbo F, Pescapè A. Computational intelligence intrusion detection techniques in Mobile Cloud Computing Environments: Review, taxonomy, and open research issues. J Inf Secur Appl. 2020; 55: 102582. https://doi.org/10.1016/j.jisa.2020.102582

Shafik W, Matinkhah SM, Ghasemzadeh M. Internet of things-based energy management, challenges, and solutions in smart cities. J Commun Technol, Electronics and Computer Science. 2020; 27: 1-1. https://doi.org/10.22385/jctecs.v27i0.302

Quy VK, Nam VH, Linh DM, Ban NT, Han ND. Communication Solutions for vehicle ad-hoc network in Smart Cities Environment: A Comprehensive Survey. Wirel Pers Commun. 2022; 122(3): 2791–815. https://doi.org/10.1007/s11277-021-09030-w

Laroui M, Khedher HI, Moungla H, Afifi H, Kamal AE. Virtual mobile edge computing based on IOT devices resources in Smart Cities. ICC 2020 – 2020. Int Conf Commun. 2020. https://doi.org/10.1109/icc40277.2020.9148982

Khattak HA, Farman H, Jan B, Din IU. Toward integrating vehicular clouds with IOT for Smart City Services. IEEE Netw. 2019; 33(2): 65–71. https://doi.org/10.1109/mnet.2019.1800236

Shukur H, Zeebaree S, Zebari R, Zeebaree D, Ahmed O, Salih A. Cloud computing virtualization of resources allocation for distributed systems. Int J Appl Sci Technol. 2020; 1(3): 98–105. https://doi.org/10.38094/jastt1331

Li J, Cai J, Khan F, Rehman AU, Balasubramaniam V, Sun J, et al. A secured framework for SDN-based Edge Computing in IOT-enabled healthcare system. IEEE Access. 2020; 8: 135479–90. https://doi.org/10.1109/access.2020.3011503

Alazab M, Lakshmanna K, G TR, Pham Q-V, Reddy Maddikunta PK. Multi-objective cluster head selection using fitness averaged rider optimization algorithm for IOT networks in Smart Cities. Sustain Energy Technol Assess. 2021; 43: 100973. https://doi.org/10.1016/j.seta.2020.100973

Alrikabi HTh, Ali Jasim N. Design and implementation of Smart City applications based on the internet of things. Int J Interact Mob Technol . 2021; 15(13): 4. https://doi.org/10.3991/ijim.v15i13.22331

Marques P, Manfroi D, Deitos E, Cegoni J, Castilhos R, Rochol J, et al. An IOT-based smart cities infrastructure architecture applied to a waste management scenario. Ad Hoc Networks. 2019; 87: 200–8. https://doi.org/10.1016/j.adhoc.2018.12.009

Alamgir Hossain S, Anisur Rahman Md, Hossain MA. Edge computing framework for enabling situation awareness in IOT based Smart City. J Parallel Distrib Comput. 2018; 122: 226–37. https://doi.org/10.1016/j.jpdc.2018.08.009

Kolhe RV, William P, Yawalkar PM, Paithankar DN, Pabale AR. Smart city implementation based on internet of things integrated with Optimization Technology. Measurement: Sensors. 2023; 27: 100789. https://doi.org/10.1016/j.measen.2023.100789

Chen Y, Hu S, Mao H, Deng W, Gao X. Application of the best evacuation model of deep learning in the design of public structures. Image Vis Comput. 2020; 102: 103975. https://doi.org/10.1016/j.imavis.2020.103975

Hussain OF, Al-Kaseem BR, Akif OZ. Smart flow steering agent for end-to-end delay improvement in software-defined networks. Baghdad Sci J. 2021; 18(1): 0163. https://doi.org/10.21123/bsj.2021.18.1.0163

Abdulzahra SA, Al-Qurabat AK, Idrees AK. Compression-based data reduction technique for IOT Sensor Networks. Baghdad Sci J. 2021; 18(1): 0184. https://doi.org/10.21123/bsj.2021.18.1.0184

Similar Articles

You may also start an advanced similarity search for this article.