Quality of Service Based on Scheduling in Cloud/Fog Environment

Lakshya Mall; Priyanka Vashisht; Ashima Narang

doi:10.55524/ijirem.2024.11.3.10

Abstract

In the area of fog and cloud computing, efficient work scheduling is critical for optimising resource allocation and raising Quality of Service (QOS) levels. Research in this area has resulted in a variety of ways for dealing with this problem. One line of research focuses on lowering data latency and improving QOS in fog-cloud systems by precise job scheduling. This requires intelligently dividing jobs across fog and cloud resources to reduce data processing and delivery delays, ultimately improving the overall user experience.
Furthermore, the investigation encompasses novel methodologies such as hybrid evolutionary algorithms and heuristic strategies. These approaches seek to create a compromise between competing objectives, such as cost and energy efficiency, while also achieving QOS criteria. Researchers aim to develop scheduling systems that optimise resource utilisation and reduce operating costs without sacrificing service quality by applying evolutionary concepts or combining heuristic methods.
Furthermore, ongoing discussions focus on improving resource scheduling approaches to achieve optimal QOS results. This entails continual evaluation and adaption of scheduling algorithms to changing environmental conditions, workload fluctuations, and user requests. Furthermore, developing methodologies such as the CODA approach provide intriguing avenues for efficient job scheduling in fog computing settings, with the potential to revolutionise future resource allocation and QOS enhancement efforts.

Keywords

Quality of Service (QOS) levels, CODA, Fog Computing, Cloud Computing

References

G. Goel and Dr. R. Tiwari, "Resource Scheduling Techniques for Optimal Quality of Service in Fog Computing Environment: A Review," Wireless Personal Communications, vol. 131, pp. 1-24, 2023, doi: 10.1007/s11277-023-10421-4.
S. M. Hussain and G. R. Begh, "Hybrid heuristic algorithm for cost-efficient QoS aware task scheduling in fog–cloud environment," Journal of Computational Science, vol. 64, 2022, Art no. 101828, ISSN 1877-7503.
M. S. Kumar and G. R. Karri, "EEOA: Cost and Energy Efficient Task Scheduling in a Cloud-Fog Framework," Sensors, vol. 23, no. 5, p. 2445, 2023. [Online]. Available: https://doi.org/10.3390/s23052445.
P. Choppara and S. Mangalampalli, "An Effective analysis on various task scheduling algorithms in Fog computing," EAI Endorsed Transactions on Internet of Things, vol. 10, Dec. 2023.
G. Prasanth, M. Kumar, R. Al-Jawry, A. Ali, H. Sabah, and M. Al-Tahee, "Improving Quality of Services of Fog Computing Through Efficient Work Flow Scheduling," in 2023 International Conference on Advances in Computing, Communication and Information Technology (ICACITE), 2023, pp. 43-47, doi: 10.1109/ICACITE57410.2023.10183104.
P. Vashisht, R. Kumar, and A. Sharma, "Efficient dynamic replication algorithm using agent for data grid," The Scientific World Journal, vol. 2014, 2014.
P. Vashisht, A. Sharma, and R. Kumar, "Strategies for replica consistency in data grid–a comprehensive survey," Concurrency and Computation: Practice and Experience, vol. 29, no. 4, p. e3907, 2017.
P. Vashisht, V. Kumar, R. Kumar, and A. Sharma, "Optimization of replica consistency and conflict resolution in data grid environment," International Journal of Mathematical, Engineering and Management Sciences, vol. 4, no. 6, pp. 1420-1431, 2019.
P. Vashisht, V. Kumar, R. Kumar, and A. Sharma, "Optimizing replica creation using agents in data grids," in 2019 Amity International Conference on Artificial Intelligence (AICAI), Dubai, UAE, 2019, pp. 542-547, doi: 10.1109/AICAI.2019.8701395.
P. Vashisht and V. Kumar, "Agent based optimized replica management in data grids," Investigación Operacional, vol. 41, no. 2, pp. 232-249, 2020.
P. Vashisht and V. Kumar, "A Cost Effective and Energy Efficient Algorithm for Cloud Computing," International Journal of Mathematical, Engineering and Management Sciences, vol. 7, pp. 681-696, 2022.
S. D. Vispute and P. Vashisht, "Optimized Energy Efficient Task Scheduling in Fog Computing," in International Conference on Innovations in Computational Intelligence and Computer Vision, Singapore, 2022, pp. 735-746, Springer Nature Singapore.
S. D. Vispute and P. Vashisht, "Energy-efficient task scheduling in fog computing based on particle swarm optimization," SN Computer Science, vol. 4, no. 4, p. 391, 2023.

Cites this article as

L. Mall, P. Vashisht, A. Narang, "Quality of Service Based on Scheduling in Cloud/Fog Environment", International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-11, Issue-3, Page No-65-70, 2024. Available from: https://doi.org/10.55524/ijirem.2024.11.3.10