Unleashing the Power of QoS: A Comprehensive Study and Evaluation of Services-based Scheduling Techniques for Fog Computing
Keywords:Fog Computing, Resource use efficiency, Quality of Service, Scheduling Algorithms, IoT (Internet of Things)
Fog computing, a special worldview, has become famous for applications or technology that should be area and dormancy delicate. It is a powerful expansion to distributed computing that makes it conceivable to offer assets and administrations near-end gadgets that are not in the cloud. The presence of various heterogeneous, possibly cell phones in a fog system raised worries about QoS. A few QoS factors are considered, and QoS-aware methodologies are introduced in different pieces of the fog system. Despite the implication of quality of service in fog computing, there is currently no comprehensive focus on QoS-aware techniques. Subsequently, this study looks at ongoing discoveries that have utilized reliable energy to guarantee QoS in fog computing. To enhance the technological capabilities with the presentation of the IoT worldview, various computing parts require various alterations to help the QoS. Continuous reaction to time-delicate positions is advanced by the Nature of the Administration point of support. Any QoS boundaries ought to be eliminated and managed to enhance the quality of life of a human being. Fog computing was acquainted in 2012 with further developing QoS in existing systems with an end goal to address QoS issues welcomed on by utilizing distributed computing alone. Improving QoS is currently the principal accentuation or innovation of fog computing. Hence, the fundamental target of this study is to audit and survey the writing on the endeavors made to improve different QoS parts.
Alaghbari, Khaled A., Mohamad Hanif Md Saad, Aini Hussain, and Muhammad Raisul Alam. 2022. “Complex Event Processing for Physical and Cyber Security in Datacentres - Recent Progress, Challenges and Recommendations.” Journal of Cloud Computing 11(1), https://doi.org/10.1186/s13677-022-00338-x.
Alsmadi, Ahmad Mohammad et al. 2021. “Fog Computing Scheduling Algorithm for Smart City.” International Journal of Electrical and Computer Engineering 11(3): 2219–28, DOI: 10.11591/ijece.v11i3.pp2219-2228.
Arikumar, K S, and V Natarajan. 2020. “FIoT: A QoS-Aware Fog-IoT Framework to Minimize Latency in IoT Applications via Fog Offloading.” In Evolution in Computational Intelligence: Frontiers in Intelligent Computing: Theory and Applications (FICTA 2020), Volume 1, Springer, 551–59, DOI:10.1007/978-981-15-5788-0_53.
Badotra, Sumit, and Surya Narayan Panda. 2021. “SNORT Based Early DDoS Detection System Using Opendaylight and Open Networking Operating System in Software Defined Networking.”Cluster Computing 24(1):501–13, https://doi.org/10.1007/s10586-020-03133-y.
Bala, Mohammad Irfan, and Mohammad Ahsan Chishti. 2019. “Survey of Applications, Challenges and Opportunities in Fog Computing.” International Journal of Pervasive Computing and Communications, DOI:10.1108/IJPCC-06-2019-059.
Bhatt, Chintan, and C K Bhensdadia. 2017. “Fog Computing: Applications, Concepts, and Issues.” International Journal of Grid and High Performance Computing (IJGHPC) 9(4): 105–13, https://doi.org/10.4018/IJGHPC.2017100107.
Bonomi, Flavio, Rodolfo Milito, Jiang Zhu, and Sateesh Addepalli. 2012. “Fog Computing and Its Role in the Internet of Things.” MCC’12 - Proceedings of the 1st ACM Mobile Cloud Computing Workshop: 13–15, https://doi.org/10.1145/2342509.2342513.
Cheng, Yew Leong, Meng Hee Lim, and Kar Hoou Hui. 2022. “Impact of Internet of Things Paradigm towards Energy Consumption Prediction: A Systematic Literature Review.” Sustainable Cities and Society 78: 103624, https://doi.org/10.1016/j.scs.2021.103624.
Das, Resul, and Muhammad Muhammad Inuwa. 2023. “A Review on Fog Computing: Issues, Characteristics, Challenges, and Potential Applications.” Telematics and Informatics Reports 10(February):100049, https://doi.org/10.1016/j.teler.2023.100049.
Deng, Ruilong et al. 2016. “Optimal Workload Allocation in Fog-Cloud Computing Toward Balanced Delay and Power Consumption.” IEEE Internet of Things Journal 3(6): 1171–81, DOI: 10.1109/JIOT.2016.2565516.
Faticanti, Francescomaria et al. 2020. “Throughput-Aware Partitioning and Placement of Applications in Fog Computing.” IEEE Transactions on Network and Service Management 17(4): 2436–50, DOI: 10.1109/TNSM.2020.3023011.
Fu, Weina, Shuai Liu, and Gautam Srivastava. 2019. “Optimization of Big Data Scheduling in Social Networks.” Entropy 21(9): 1–16, doi:10.3390/e21090902.
Ghobaei-Arani, Mostafa, Reihaneh Khorsand, and Mohammadreza Ramezanpour. 2019. “An Autonomous Resource Provisioning Framework for Massively Multiplayer Online Games in Cloud Environment.” Journal of Network and Computer Applications 142(June): 76–97, DOI:10.1109/ACCESS.2021.3090366.
Ghobaei-Arani, Mostafa, Alireza Souri, and Ali A Rahmanian. 2020. “Resource Management Approaches in Fog Computing: A Comprehensive Review.” Journal of Grid Computing 18(1): 1–42, https://doi.org/10.1007/s10723-019-09491-1.
Guleria, Kalpna et al. 2021. “An Enhanced Energy Proficient Clustering (EEPC) Algorithm for Relay Selection in Heterogeneous WSNs.” Ad Hoc Networks 116, https://doi.org/10.1016/j.adhoc.2021.102473.
Haghi Kashani, Mostafa, Amir Masoud Rahmani, and Nima Jafari Navimipour. 2020. “Quality of Service-Aware Approaches in Fog Computing.” International Journal of Communication Systems 33(8), https://doi.org/10.1002/dac.4340.
Huang, Xiaoge, Yifan Cui, Qianbin Chen, and Jie Zhang. 2020. “Joint Task Offloading and QoS-Aware Resource Allocation in Fog-Enabled Internet-of-Things Networks.” IEEE Internet of Things Journal 7(8): 7194–7206, DOI: 10.1109/JIOT.2020.2982670.
Intharawijitr, Krittin, Katsuyoshi Iida, and Hiroyuki Koga. 2016. “Analysis of Fog Model Considering Computing and Communication Latency in 5G Cellular Networks.” In 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), 1–4, DOI: 10.1109/PERCOMW.2016.7457059.
Islam, Mir Salim Ul, Ashok Kumar, and Yu-Chen Hu. 2021. “Context-Aware Scheduling in Fog Computing: A Survey, Taxonomy, Challenges and Future Directions.” Journal of Network and Computer Applications 180: 103008, https://doi.org/10.1016/j.jnca.2021.103008.
Jamil, Bushra et al. 2020. “A Job Scheduling Algorithm for Delay and Performance Optimization in Fog Computing.” Concurrency and Computation: Practice and Experience 32(7): e5581, https://doi.org/10.1002/cpe.5581.
Jo, Dongsik, and Gerard Jounghyun Kim. 2019. “AR Enabled IoT for a Smart and Interactive Environment: A Survey and Future Directions.” Sensors (Switzerland) 19(19), doi:10.3390/s19194330.
Kaur, Navjeet, Ashok Kumar, and Rajesh Kumar. 2021. “A Systematic Review on Task Scheduling in Fog Computing: Taxonomy, Tools, Challenges, and Future Directions.” Concurrency and Computation: Practice and Experience 33(21): e6432, https://doi.org/10.1002/cpe.6432.
Kertesz, A., T. Pflanzner, and T. Gyimothy. 2019. “A Mobile IoT Device Simulator for IoT-Fog-Cloud Systems.” Journal of Grid Computing 17(3): 529–51, DOI: 10.1007/s10723-018-9468-9.
Khattar, Nagma, Jagpreet Sidhu, and Jaiteg Singh. 2019. “Toward Energy-Efficient Cloud Computing: A Survey of Dynamic Power Management and Heuristics-Based Optimization Techniques.” The Journal of Supercomputing 75, https://doi.org/10.1007/s11227-019-02764-2.
Kimani, Kenneth, Vitalice Oduol, and Kibet Langat. 2019. “Cyber Security Challenges for IoT-Based Smart Grid Networks.” International journal of critical infrastructure protection 25: 36–49, https://doi.org/10.1016/j.ijcip.2019.01.001.
Li, Qiang et al. 2020. “Capacity-Aware Edge Caching in Fog Computing Networks.” IEEE Transactions on Vehicular Technology 69(8): 9244–48, DOI: 10.1109/TVT.2020.3001301.
Lin, Chun Cheng, and Jhih Wun Yang. 2018. “Cost-Efficient Deployment of Fog Computing Systems at Logistics Centers in Industry 4.0.” IEEE Transactions on Industrial Informatics 14(10): 4603–11, DOI:10.1109/TII.2018.2827920.
Mahmud, Redowan, and Rajkumar Buyya. 2019. “Modeling and Simulation of Fog and Edge Computing Environments Using Ifogsim Toolkit.” Fog and Edge Computing: Principles and Paradigms: 433–165, DOI:10.1002/9781119525080.ch17.
Maiti, Prasenjit, Jaya Shukla, Bibhudatta Sahoo, and Ashok Kumar Turuk. 2019. “Mathematical Modeling of QoS-Aware Fog Computing Architecture for Iot Services.” Advances in Intelligent Systems and Computing 814(November 2018): 13–21, DOI:10.1007/978-981-13-1501-5_2.
Miah, Md Sipon, Michael Schukat, and Enda Barrett. 2018. “An Enhanced Sum Rate in the Cluster Based Cognitive Radio Relay Network Using the Sequential Approach for the Future Internet of Things.” Human-centric Computing and Information Sciences 8(1). https://doi.org/10.1186/s13673-018-0139-4.
Pereira, Jorge et al. 2019. “Assessing the Reliability of Fog Computing for Smart Mobility Applications in VANETs.” Future Generation Computer Systems 94(August 2019): 317–32, DOI:10.1016/j.future.2018.11.043.
Qu, Zhiguo et al. 2020. “Study QoS Optimization and Energy Saving Techniques in Cloud, Fog, EDge, and IoT.” Complexity 2020, https://doi.org/10.1155/2020/8964165.
Rani, Meena, Kalpna Guleria, and Surya Narayan Panda. 2021. “Cloud Computing An Empowering Technology: Architecture, Applications and Challenges.” 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021: 1–6, DOI: 10.1109/ICRITO51393.2021.9596259.
Rohinidevi, V Vasuki et al. 2022. “A Taxonomy towards Fog Computing Resource Allocation.” In 2022 2nd International Conference on Innovative Sustainable Computational Technologies (CISCT), , 1–5, DOI: 10.1109/CISCT55310.2022.10046643.
Saif, Faten A., Rohaya Latip, ZM Hanapi, and K. Shafinah. 2023. “Multi-Objective Grey Wolf Optimizer Algorithm for Task Scheduling in Cloud-Fog Computing.” IEEE Access 11(January): 20635–46, DOI:10.1109/ACCESS.2023.3241240.
Seth, Ishita et al. 2022. “A Taxonomy and Analysis on Internet of Vehicles: Architectures, Protocols, and Challenges.” Wireless Communications and Mobile Computing 2022, Article ID 9232784, 26 pages, volume 2022, https://doi.org/10.1155/2022/9232784.
Singhrova, Anita, and Anu Anu. 2022. “Resource Allocation in Fog Computing Based on Meta-Heuristic Approaches: A Systematic Review.” 22: 503–14, DOI:10.22937/IJCSNS.2022.22.9.65.
Sodhro, Ali Hassan et al. 2018. “5G-Based Transmission Power Control Mechanism in Fog Computing for Internet of Things Devices.” Sustainability (Switzerland) 10(4): 1–17, https://doi.org/10.3390/su10103626.
Souri, Alireza, Parvaneh Asghari, and Reza Rezaei. 2017. “Software as a Service Based CRM Providers in the Cloud Computing: Challenges and Technical Issues.” Journal of Service Science Research 9: 219–37, DOI 10.1007/s12927-017-0011-5.
Sun, Yan, and Nan Zhang. 2017. “A Resource-Sharing Model Based on a Repeated Game in Fog Computing.” Saudi Journal of Biological Sciences 24(3): 687–94. http://dx.doi.org/10.1016/j.sjbs.2017.01.043.
Uppal, Mudita et al. 2021. “Cloud-Based Fault Prediction Using IoT in Office Automation for Improvisation of Health of Employees.” Journal of Healthcare Engineering 2021, Article ID 8106467, 13 pages, Volume 2021 https://doi.org/10.1155/2021/8106467.
Wang, Haozhe et al. 2019. “Data-Driven Dynamic Resource Scheduling for Network Slicing: A Deep Reinforcement Learning Approach.” Information Sciences 498: 106–16, https://doi.org/10.1016/j.ins.2019.05.012.
Yassine, Abdulsalam, Shailendra Singh, M Shamim Hossain, and Ghulam Muhammad. 2019. “IoT Big Data Analytics for Smart Homes with Fog and Cloud Computing.” Future Generation Computer Systems 91: 563–73, DOI:10.1016/j.future.2018.08.040.
Yoghourdjian, Vahan et al. 2021. “Scalability of Network Visualisation from a Cognitive Load Perspective.” IEEE Transactions on Visualization and Computer Graphics 27(2): 1677–87, https://doi.org/10.48550/arXiv.2008.07944.
Zeng, Deze et al. 2016. “Joint Optimization of Task Scheduling and Image Placement in Fog Computing Supported Software-Defined Embedded System.” IEEE Transactions on Computers 65(12): 3702–12, DOI: 10.1109/TC.2016.2536019.
Krishna, K. S. ., Satish, T. ., & Mishra, J. . (2023). Machine Learning-Based IOT Air Quality and Pollution Detection. International Journal on Recent and Innovation Trends in Computing and Communication, 11(2s), 132–145. https://doi.org/10.17762/ijritcc.v11i2s.6036
Prof. Muhamad Angriawan. (2016). Performance Analysis and Resource Allocation in MIMO-OFDM Systems. International Journal of New Practices in Management and Engineering, 5(02), 01 - 07. Retrieved from http://ijnpme.org/index.php/IJNPME/article/view/44
Kamble, S.D., Saini, D.K.J.B., Jain, S., Kumar, K., Kumar, S., Dhabliya, D. A novel approach of surveillance video indexing and retrieval using object detection and tracking (2023) Journal of Interdisciplinary Mathematics, 26 (3), pp. 341-350.
How to Cite
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.