An Optimized AMS Based Cloud Downloading Service with Advanced Caching and Intelligent Data Distribution Mechanism

Article Sidebar

PDF
Published: Aug 31, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i9s.7463
Keywords:
Cloud, advanced caching, intelligent data distribution, video optimization

Main Article Content

S. Prasanna
Research Scholar, Department of Computer Science and Engineering, St.Peter's Institute of Higher Education and Research, Avadi, Chennai, Tamilnadu, India
B. Shanthini
Professor & Head, St.Peter's Institute of Higher Education and Research, Avadi, Chennai, Tamilnadu, India

Abstract

The popularity of peer-to-peer video content downloading has surged due to diverse content availability and convenient sharing among users. However, scaling systems to accommodate the growing number of users and content items poses a challenge. This research aims to optimize video content downloading in peer-to-peer systems. The objective is to improve performance by developing advanced caching mechanisms, an intelligent data distribution algorithm, and efficient bandwidth resource management. The proposed approach involves implementing innovative caching mechanisms that store frequently accessed content closer to users, reducing download time. An intelligent data distribution algorithm minimizes bottlenecks and maximizes download speeds. Efficient bandwidth resource management ensures fair allocation. Results demonstrate significant enhancements in download time and overall system performance, leading to improved user experience. This research addresses the need for an optimized video content downloading system to handle increasing user and content volumes. The findings hold the potential to enhance user experiences, facilitate seamless video sharing, and advance peer-to-peer video content downloading.

Article Details

How to Cite
Prasanna, S. ., & Shanthini, B. . (2023). An Optimized AMS Based Cloud Downloading Service with Advanced Caching and Intelligent Data Distribution Mechanism. International Journal on Recent and Innovation Trends in Computing and Communication, 11(9s), 515–522. https://doi.org/10.17762/ijritcc.v11i9s.7463
Issue
Vol. 11 No. 9s (2023)
Section
Articles

References

K. Khan, Y. Zhang, L. Sun, and Q. Wang, “Security and privacy in peer-to-peer networks: Challenges and opportunities,” IEEE Network, vol. 34, no. 4, 2020, pp. 124-130.

J. Li, J. Wu, L. Yan, S. Yu, and W. Li, "An empirical study of P2P streaming traffic classification using deep learning," Multimedia Tools and Applications, vol. 78, no. 14, 2019, pp. 19783-19802.

X. Li, Y. Liu, and K. Xu, "Optimizing Bandwidth Allocation for Peer-to-Peer Video Content Delivery," IEEE Transactions on Multimedia, vol. 23, 2021, pp. 2095-2106. doi: 10.1109/TMM.2021.3042232.

Y. Chen, D. Huang, and Y. Li, "Efficient Content Discovery and Search Mechanism for Peer-to-Peer Video Content Downloading," IEEE Transactions on Broadcasting, vol. 67, no. 1, 2021, pp. 23-34. doi: 10.1109/TBC.2020.3041115.

Y. Xu, H. Zhou, Z. Li, and Z. Chen, "Scalable Storage Solutions for Peer-to-Peer Video Content Downloading," IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 11, 2020, pp. 4219-4232. doi: 10.1109/TCSVT.2019.2899200.

Abhijith, G. S. V. ., & Gundad, A. K. V. . (2023). Data Mining for Emotional Analysis of Big Data. International Journal of Intelligent Systems and Applications in Engineering, 11(3s), 271–279. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2684

H. Zhang, X. Zhang, H. Li, and M. Chen, "Performance Optimization and Quality of Service in Peer-to-Peer Video Content Downloading," IEEE Transactions on Multimedia, vol. 22, no. 11, 2020, pp. 3005-3018. doi: 10.1109/TMM.2020.2974512

S. Wang, Z. Liu, L. Li, & L. Sun, "Caching Mechanisms for Peer-to-Peer Video Content Downloading: A Survey," IEEE Transactions on Broadcasting, vol. 66, no. 3, 2020, pp. 721-733. doi: 10.1109/TBC.2019.2944295

H. Zhang, S. Jiang, C. Jiang, and H. Wang, "Content-Aware Caching Scheme for Peer-Assisted Video-on-Demand Systems," IEEE Transactions on Multimedia, vol. 19, no. 12, 2017, pp. 2775-2787.

Q. Li, M. Li, K. Xu, and H. Zhao, "Predictive Caching for Popular Video Contents in P2P VoD Systems," IEEE Transactions on Multimedia, vol. 20, no. 4, 2018, pp. 878-890. doi:10.1109/TMM.2017.2768058

X. Liu, H. Wu, and L. Li, "Adaptive Caching Algorithm for P2P VoD Systems Considering Popularity and Network Conditions," International Journal of Multimedia and Ubiquitous Engineering, vol. 14, no. 5, 2019, pp. 305-316.

H. Wang, L. Liu, Y. Zhao, and X. Zhou, "Distributed Caching in Peer-Assisted VoD Systems with the Consideration of File Popularity," Journal of Network and Systems Management, vol. 28, no. 2, 2020, pp. 528-552.

J. Li, H. Hu, Y. Shu, and C. Li, "Distributed Chunk Scheduling for Smooth Playback of Rate-Adaptive Video Streaming in P2P Networks," IEEE Transactions on Multimedia, vol. 18, no. 1, 2016, pp. 83-95.

X. Wang, W. Tan, Z. Yu, and Y. Zhang, "Load Balancing Optimization for Distributed P2P Storage Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 29, no. 10, 2018, pp. 2353-2366.

Z. Chen, L. Zhang, and H. Li, "Network Coding Based Peer-to-Peer Live Video Streaming with Multiple Description Coding," IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 4, 2019, pp. 1136-1148.

Mr. Ashish Uplenchwar. (2017). Modern Speech Identification Model using Acoustic Neural approach . International Journal of New Practices in Management and Engineering, 6(03), 01 - 06. https://doi.org/10.17762/ijnpme.v6i03.58

J.H. Kim, S.Y. Kim, and Y.C. Kim, "A Hybrid Cloud-P2P Architecture for Efficient Video Streaming Services," IEEE Access, vol. 8, 2020, pp. 198947-198958.

H. Liang, G. Xie, D. Wu, and B. Li, "Cooperative Bandwidth Allocation in Peer-to-Peer Live Streaming," IEEE Transactions on Multimedia, vol. 19, no. 5, 2017, pp. 998-1010.

X. Yu, C. Li, and G. Yu, "Dynamic Management of Bandwidth Allocation for Live Streaming in P2P Systems," Journal of Network and Computer Applications, vol. 118, 2018, pp. 43-54.

H. Wu, X. Liu, Y. Ma, and L. Li, "QoS-Aware Cooperative Bandwidth Allocation Scheme for P2P Video-on-Demand Systems," IEEE Access, vol. 7, 2019, pp. 163032-163042. DOI: 10.1109/ACCESS.2019.2959375.

Y. Zhang, W. Tan, J. Cai, and Z. Yu, "Bandwidth Resource Allocation for P2P Video Streaming with Network Coding," IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 6, 2020, pp. 1745-1759.

A. Taheri, et al., "A Comprehensive Survey of Web Caching and Content Delivery Networks," ACM Computing Surveys, vol. 49, no. 2, 2016, pp. 35:1-35:44. DOI: 10.1145/2897698.

K. Niu, Y. Zhang, M. Li, and Q. Wang, "Distributed Intelligent Data Distribution Mechanism Based on Content-Oriented Networks," IEEE Access, vol. 3, 2015, pp. 2279-2293. DOI: 10.1109/ACCESS.2015.2502359

Thompson, A., Walker, A., Fernández, C., González, J., & Perez, A. Enhancing Engineering Decision Making with Machine Learning Algorithms. Kuwait Journal of Machine Learning, 1(2). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/127

R. Rizvi, et al., "Bandwidth Resource Management in LTE-Advanced Networks: A Comprehensive Survey," IEEE Communications Surveys & Tutorials, vol. 16, no. 1, 2014, pp. 98-117. DOI: 10.1109/SURV.2013.060113.00192

D. Yan, et al., "Dynamic Caching for Efficient Video Distribution in Information-Centric Networks," IEEE Transactions on Multimedia, vol. 19, no. 6, 2017, pp. 1299-1312. DOI: 10.1109/TMM.2017.2652738.

Leila Abadi, Amira Khalid, Predictive Maintenance in Renewable Energy Systems using Machine Learning , Machine Learning Applications Conference Proceedings, Vol 3 2023.

X. Zhang, et al., "A Survey on Distributed Hash Table-based Storage Systems," Journal of Network and Computer Applications, vol. 40, 2014, pp. 312-340. DOI: 10.1016/j.jnca.2013.12.001

Y. Zeng, P. Zhang, Y. Xiao, and X. Zhang, "A Survey on Fairness in Resource Allocation for Wireless Networks: Methods, Measurements, and Challenges," IEEE Communications Surveys & Tutorials, vol. 18, no. 2, 2016, pp. 1323-1350. DOI: 10.1109/COMST.2015.2502918