Document Type : Research Paper
Authors
Department of Computer Engineering, College of Engineering, Mosul University, Mosul, Iraq
Abstract
An emerging networking technique called fog computing extends cloud computing capabilities to the edge network's borders. It is employed to get around the limitations of cloud computing, like latency and bandwidth problems. Fog computing is suitable for IoT systems and applications that require real-time processing, reliable network access, low latency, and strong security. In this work, the objective is to design and implement a fog computing environment to simulate the behavior of a multi-user healthcare application, which represents the monitoring of elderly care homes in Mosul city. Several algorithms were employed to examine the effects of load balancing inside fog computing networks. These algorithms are Random, Round-Robin, and the modified Throttled algorithm, which is modified by adding an extra management layer to be more suitable for fog computing networks. The response time results obtained from implementing this modified method were superior to those of the random algorithm and closely resembled the response time results of the round-robin algorithm. In case QoS1 with 25 clients, the result was (0.246037794) second without the load balancing algorithm, (0.124323358) second in the Random algorithm, (0.115641477) second in the Round-Robin algorithm, and (0.114981575) second for the modified throttled algorithm. thus, making it applicable for fog computing networks and cloud computing networks.
Keywords
- A. M. and M. G. Rabeea Basir, Saad Qaisar, Mudassar Ali, Monther Aldwairi, Muhammad Ikram Ashraf, “Fog Computing Enabling Industrial Internet of Things: State-of-the-Art and Research Challenges,” Sensors, Vol. 19, No. 21, p. 4807, Nov. 2019. https://doi.org/10.3390/s19214807
- V. N. H. Sabireen, “A Review on Fog Computing: Architecture, Fog with IoT, Algorithms and Research Challenges,” ICT Express, Vol. 7, No. 2, pp. 162–176, Jun. 2021. https://doi.org/10.1016/j.icte.2021.05.004
- A. Varfolomeev and L. Al-Farhani, “Blockchain Fog-based scheme for identity authentication in smart building,” Al-Qadisiyah J. Eng. Sci., Vol. 16, No. 3, pp. 218–227, Oct. 2023 https://doi.org/10.30772/qjes.1999.180617
- R. Neware and U. Shrawankar, “Fog Computing Architecture, Applications and Security Issues,” Int. J. Fog Comput., Vol. 3, No. 1, pp. 75–105, Jan. 2020. https://doi.org/10.4018/IJFC.2020010105
- M. Rahimi, M. Songhorabadi, and M. H. Kashani, “Fog-Based Smart Homes: A Systematic Review,” J. Netw. Comput. Appl., Vol. 153, No. C, p. 102531, Mar.2020. https://doi.org/10.1016/j.jnca.2020.102531
- O. Alani, T. Khaleel, and O. Al-Abdulqader, “A Review on Fog Computing: Research Challenges and Future Directions,” Al-Rafidain Eng. J., Vol. 28, No. 1, pp. 341–350, Mar. 2023. https://doi.org/10.33899/rengj.2022.136642.1211
- P. Hu, S. Dhelim, H. Ning, and T. Qiu, “Survey on Fog Computing: Architecture, Key Technologies, Applications, and Open Issues,” J. Netw. Comput. Appl., Vol. 98, No. C, pp. 27–42, Nov. 2017. https://doi.org/10.1016/j.jnca.2017.09.002.
- R. K. Naha, S. Garg, and A. Chan, “Fog Computing Architecture: Survey and Challenges,” in Big Data-Enabled Internet of Things, Institution of Engineering and Technology, 2019, pp. 199–223. https://doi.org/10.48550/arXiv.1811.09047
- B. Negash, A. M. Rahmani, P. Liljeberg, and A. Jantsch, “Fog Computing Fundamentals in the Internet-of-Things,” in Fog Computing in the Internet of Things, Cham: Springer International Publishing, 2018, pp. 3–13. https://doi.org/10.1007/978-3-319-57639-8_1
- A. M. Rahmani et al., “Exploiting Smart e-Health Gateways at The Edge of Healthcare Internet-of-Things: A Fog Computing Approach,” Futur. Gener. Comput. Syst., Vol. 78, pp. 641–658, Jan. 2018. https://doi.org/10.1016/j.future.2017.02.014
- P. Hu, H. Ning, T. Qiu, Y. Zhang, and X. Luo, “Fog Computing Based Face Identification and Resolution Scheme in Internet of Things,” IEEE Trans. Ind. Informatics, Vol. 13, No. 4, pp. 1910–1920, Aug. 2017. https://doi.org/10.1109/TII.2016.2607178
- Z. Sheng, S. Yang, Y. Yu, A. Vasilakos, J. Mccann, and K. Leung, “A survey on the ietf protocol suite for the internet of things: standards, challenges, and opportunities,” IEEE Wirel. Commun., Vol. 20, No. 6, pp. 91–98, Dec. 2013. https://doi.org/10.1109/MWC.2013.6704479
- C. Puliafito, E. Mingozzi, F. Longo, A. Puliafito, and O. Rana, “Fog Computing for the Internet of Things: A Survey,” ACM Trans. Internet Technol., Vol. 19, No. 2, pp. 1–41, May 2019. https://doi.org/10.1145/3301443
- N. Mohan and J. Kangasharju, “Edge-Fog Cloud: A Distributed Cloud for Internet of Things Computations,” in International Conference on Cloudification of the Internet of Things, IEEE, 2016, pp. 1–6. https://doi.org/10.1109/CIOT.2016.7872914.
- A. Brogi and S. Forti, “QoS-Aware Deployment of IoT Applications Through the Fog,” IEEE Internet Things J., Vol. 4, No. 5, pp. 1185–1192, Oct. 2017. https://doi.org/10.1109/JIOT.2017.2701408
- H. Gupta, A. Vahid Dastjerdi, S. K. Ghosh, and R. Buyya, “iFogSim: A Toolkit for Modeling and Simulation of Resource Management Techniques in Internet of Things, Edge and Fog Computing Environments,” Softw. Pract. Exp., Vol. 47, No. 9, pp. 1275–1296, Sep. 2017. https://doi.org/10.1002/spe.2509
- T. Qayyum, A. W. Malik, M. A. Khan Khattak, O. Khalid, and S. U. Khan, “FogNetSim++: A Toolkit for Modeling and Simulation of Distributed Fog Environment,” IEEE Access, Vol. 6, pp. 63570–63583, 2018. https://doi.org/10.1109/ACCESS.2018.2877696
- A. Varga, “OMNeT++,” in Modeling and Tools for Network Simulation, Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 35–59. https://doi.org/10.1007/978-3-642-12331-3_3
- I. Lera, C. Guerrero, and C. Juiz, “YAFS: A Simulator for IoT Scenarios in Fog Computing,” IEEE Access, Vol. 7, pp. 91745–91758, 2019. https://doi.org/10.1109/ACCESS.2019.2927895
- A. W. Malik, T. Qayyum, A. U. Rahman, M. A. Khan, O. Khalid, and S. U. Khan, “xFogSim: A Distributed Fog Resource Management Framework for Sustainable IoT Services,” IEEE Trans. Sustain. Comput., Vol. 6, No. 4, pp. 691–702, Oct 2021. https://doi.org/10.1109/TSUSC.2020.3025021
- S. Majumder, E. Aghayi, M. Noferesti, Z. Pang, and M. Deen, “Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges,” Sensors, Vol. 17, No. 11, p. 2496, Oct. 2017. https://doi.org/10.3390/s17112496
- O. Debauche, S. Mahmoudi, P. Manneback, and A. Assila, “Fog IoT for Health: A new Architecture for Patients and Elderly Monitoring.,” Procedia Comput. Sci., Vol. 160, pp. 289–297, 2019. https://doi.org/10.1016/j.procs.2019.11.087
- P. Singh, R. Kaur, J. Rashid, and S. Juneja, “A Fog-Cluster Based Load-Balancing Technique,” Sustainability, Vol. 14, No. 13, p. 7961, Jun. 2022. https://doi.org/10.3390/su14137961
- R. Beraldi, C. Canali, R. Lancellotti, and G. Proietti Mattia, “Randomized Load Balancing under Loosely Correlated State Information in Fog Computing,” in Proceedings of the 23rd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, Nov. 2020, pp. 123–127. https://doi.org/10.1145/3416010.3423244
- V. Kashyap and A. Kumar, “Load Balancing Techniques for Fog Computing Environment: Comparison, Taxonomy, Open Issues, and Challenges,” Concurr. Comput. Pract. Exp., Vol. 34, No. 23, p. e7183, Oct. 2022. https://doi.org/10.1002/cpe.7183
- N. R. O. Al-Rubaie, R. N. N. Kamel, and R. M. Alshemari, “Simulating Fog Computing in OMNeT++,” Bull. Electr. Eng. Informatics, Vol. 12, No. 2, pp. 979–986, Apr. 2022. https://doi.org/10.11591/eei.v12i2.4201\
- D. B. Abdullah and H. H. Mohammed, “DHFogSim: Smart Real-Time Traffic Management Framework for Fog Computing Systems,” in 4th International Conference on Advanced Science and Engineering (ICOASE), Sep. 2022, pp. 60–65. https://doi.org/10.1109/ICOASE56293.2022.10075605
- A. S. Kadhim and M. E. Manaa, “Hybrid Load-Balancing Algorithm for Distributed Fog Computing in Internet of Things Environment,” Bull. Electr. Eng. Informatics, Vol. 11, No. 6, pp. 3462–3470, Dec. 2022. https://doi.org/10.11591/eei.v11i6.4127
- Measurement — INET 4.5.0 documentation, 2023, https://inet.omnetpp.org/docs/showcases/measurement.
)
