Study of Edge Computing on Cloud Infrastructure and Application Performance

Authors

  • Mr Kuldeep Assistant Professor Department of Computer Science CRM Jat College Hisar
  • Dr. Naveen Verma Assistant Professor , Dr. B. R. Ambedkar Govt. College Kaithal
  • Dr Rakesh Sharma Assistant Professor Department of Computer Science, CRM Jat College Hisar

DOI:

https://doi.org/10.36676/jrps.v13.i1.1533

Keywords:

Edge Computing, Cloud Infrastructure, Application Performance

Abstract

Edge computing has revolutionised cloud computing by processing data closer to its source. This paper examines how edge computing affects cloud infrastructure and application performance, focussing on latency, bandwidth optimisation, and data transfer costs. Edge computing improves real-time application performance in latency-sensitive industries like IoT, autonomous systems, and streaming services by spreading processing tasks to the edge. The paper examines how edge-cloud integration improves bandwidth efficiency, latency, and system scalability. Case studies demonstrate realistic solutions and address future trends and issues like security, scalability, and interoperability. This study found that edge computing improves cloud infrastructure and addresses important performance bottlenecks, boosting current application performance.

References

Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012). Fog computing and its role in the internet of things. Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, 13-16. https://doi.org/10.1145/2342509.2342513 DOI: https://doi.org/10.1145/2342509.2342513

Satyanarayanan, M. (2017). The emergence of edge computing. Computer, 50(1), 30-39. https://doi.org/10.1109/MC.2017.9 DOI: https://doi.org/10.1109/MC.2017.9

Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE Internet of Things Journal, 3(5), 637-646. https://doi.org/10.1109/JIOT.2016.2579198 DOI: https://doi.org/10.1109/JIOT.2016.2579198

Abbas, N., Zhang, Y., Taherkordi, A., & Skeie, T. (2018). Mobile edge computing: A survey. IEEE Internet of Things Journal, 5(1), 450-465. https://doi.org/10.1109/JIOT.2017.2750180 DOI: https://doi.org/10.1109/JIOT.2017.2750180

Varghese, B., & Buyya, R. (2018). Next generation cloud computing: New trends and research directions. Future Generation Computer Systems, 79, 849-861. https://doi.org/10.1016/j.future.2017.09.020 DOI: https://doi.org/10.1016/j.future.2017.09.020

Mach, P., & Becvar, Z. (2017). Mobile edge computing: A survey on architecture and computation offloading. IEEE Communications Surveys & Tutorials, 19(3), 1628-1656. https://doi.org/10.1109/COMST.2017.2682318 DOI: https://doi.org/10.1109/COMST.2017.2682318

Deng, R., Lu, R., Lai, C., Luan, T. H., & Liang, H. (2016). Optimal workload allocation in fog-cloud computing toward balanced delay and power consumption. IEEE Internet of Things Journal, 3(6), 1171-1181. https://doi.org/10.1109/JIOT.2016.2551746 DOI: https://doi.org/10.1109/JIOT.2016.2565516

Satyanarayanan, M., Simoens, P., Xiao, Y., & Pillai, P. (2015). Edge analytics in the internet of things. IEEE Pervasive Computing, 14(2), 24-31. https://doi.org/10.1109/MPRV.2015.32 DOI: https://doi.org/10.1109/MPRV.2015.32

Aazam, M., Khan, I., Alsaffar, A. A., & Huh, E. (2014). Cloud of things: Integrating internet of things and cloud computing and the issues involved. Proceedings of the 11th IEEE International Bhurban Conference on Applied Sciences & Technology (IBCAST), 414-419. https://doi.org/10.1109/IBCAST.2014.6778179 DOI: https://doi.org/10.1109/IBCAST.2014.6778179

Tran, T. X., Hajisami, A., Pandey, P., & Pompili, D. (2017). Collaborative mobile edge computing in 5G networks: New paradigms, scenarios, and challenges. IEEE Communications Magazine, 55(4), 54-61. https://doi.org/10.1109/MCOM.2017.1600943 DOI: https://doi.org/10.1109/MCOM.2017.1600863

Downloads

Published

18-03-2022

How to Cite

Mr Kuldeep, Dr. Naveen Verma, & Dr Rakesh Sharma. (2022). Study of Edge Computing on Cloud Infrastructure and Application Performance. International Journal for Research Publication and Seminar, 13(1), 358–363. https://doi.org/10.36676/jrps.v13.i1.1533