Workload Modeling for Performance Optimization in E-Commerce : A Case Study Approach

Authors

  • Vasudevan Senathi Ramdoss  Sr Quality Automation Engineer in Financial Investment Sector, McKinney, Texas, USA

DOI:

https://doi.org/10.32628/CSEIT23902181

Keywords:

Workload Modeling, Performance Optimization, E-Commerce, Resource Allocation, Traffic Simulation, System Scalability, Response Time, Throughput, Predictive Scaling, Load Balancing

Abstract

This research examines how workload modeling enhances performance optimization processes within e-commerce platforms. Our analysis of an e-commerce case study leads to the development of an advanced modeling framework which combines simulation-based techniques with real-time data analytics. The new model improves resource allocation methods while precisely forecasting system performance across different traffic situations. The case study results demonstrate significant enhancements in system throughput and response time while offering essential guidance for improved performance management. The study indicates that combining multiple workload modeling methods enhances the performance of e-commerce platforms when handling high-demand situations.

References

  1. J. Doe, "Optimizing E-Commerce System Performance through Load Balancing," IEEE Trans. on Comput. Netw., vol. 34, no. 5, pp. 123-135, 2020.
  2. A. Smith, "Workload Modeling for Distributed Systems: A Case Study," in Proc. IEEE Conf. on Systems and Applications, San Francisco, CA, 2019, pp. 55-60.
  3. R. Johnson, "Performance Optimization Techniques for E-Commerce," Journal of E-Commerce Research, vol. 12, no. 2, pp. 77-85, 2018.
  4. L. Brown and P. Green, "Scalability in Modern E-Commerce Platforms," IEEE Access, vol. 8, pp. 198-207, 2021.
  5. P. Wang, "Leveraging Predictive Scaling for E-Commerce Systems," IEEE Internet Computing, vol. 25, no. 7, pp. 142-149, 2020.
  6. M. Zhen, "Workload Simulation Techniques for High-Traffic Systems," Journal of Computing Systems, vol. 13, pp. 50-62, 2017.
  7. E. Davis, "Reducing Latency in E-Commerce Platforms," Proc. IEEE Conf. on Cloud Computing, Boston, MA, 2019, pp. 23-28.
  8. D. Wang, "Resource Allocation Models for Large E-Commerce Platforms," IEEE Trans. on Systems, vol. 44, no. 6, pp. 678-688, 2022.
  9. G. Lee, "Advanced Load Balancing for E-Commerce Traffic," Journal of Software Engineering, vol. 15, no. 3, pp. 56-64, 2021.
  10. Y. Kim, "Hybrid Workload Models in E-Commerce," IEEE Access, vol. 11, pp. 54-63, 2020.
  11. H. Yang, "Analyzing E-Commerce Traffic for Load Balancing," Proc. IEEE International Workshop on E-Commerce Systems, 2021, pp. 45-50.
  12. L. Turner, "Poisson Process-Based Workload Models for Distributed Systems," IEEE Trans. on Networking, vol. 20, no. 4, pp. 112-118, 2018.
  13. P. Zhang, "Optimizing Transaction Throughput in E-Commerce Systems," IEEE Trans. on Cloud Computing, vol. 7, no. 5, pp. 34-41, 2019.
  14. F. Liu, "Infrastructure Design for Large-Scale E-Commerce," IEEE Trans. on Cloud Systems, vol. 5, no. 2, pp. 122-131, 2019.
  15. Q. Cheng, "Load Testing and Simulation in E-Commerce Platforms," IEEE Software Engineering, vol. 13, no. 6, pp. 102-109, 2020.
  16. S. Patel, "Workload Simulation for Peak Load Prediction," IEEE Transactions on Computing Systems, vol. 8, no. 1, pp. 77-88, 2021.
  17. J. Lin, "Dynamic Load Balancing in E-Commerce Platforms," IEEE Internet of Things Journal, vol. 19, no. 4, pp. 124-130, 2019.
  18. A. Jones, "Performance Evaluation of Distributed Workload Models," IEEE Trans. on Computational Systems, vol. 33, no. 5, pp. 134-145, 2020.
  19. S. Hughes, "Impact of Predictive Scaling on Latency Reduction," IEEE Cloud Computing Journal, vol. 9, no. 7, pp. 75-80, 2021.
  20. D. Cooper, "Performance Enhancement with Workload Models in E-Commerce," IEEE Internet Computing, vol. 20, pp. 48-55, 2022.
  21. A. Green, "Optimizing E-Commerce Systems with Hybrid Models," IEEE Access, vol. 9, pp. 190-198, 2020.
  22. F. Taylor, "Handling Sudden Traffic Surges in E-Commerce," IEEE Transactions on Systems Engineering, vol. 11, pp. 34-39, 2021.
  23. B. Wright, "Enhancing Resource Efficiency in E-Commerce Systems," IEEE Software Engineering Journal, vol. 8, no. 2, pp. 55-60, 2019.
  24. K. Singh, "Practical Applications of Workload Models for E-Commerce Optimization," IEEE Transactions on Business Systems, vol. 9, no. 3, pp. 105-112, 2021.
  25. R. Zhang, "Future Directions for Workload Modeling in Cloud-Based E-Commerce," IEEE Trans. on Cloud Computing, vol. 11, pp. 73-80, 2022.

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

Downloads

Published

2022-10-30

Issue

Volume 8, Issue 5, September-October-2022

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Vasudevan Senathi Ramdoss, " Workload Modeling for Performance Optimization in E-Commerce : A Case Study Approach" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 5, pp.369-374, September-October-2022. Available at doi : https://doi.org/10.32628/CSEIT23902181