IJSDIP Logo

International Journal of System Design and Information Processing

psnajournals.org.in

COMPREHENSIVE EVALUATION OF PERFORMANCE, RELIABILITY, AND COST IN AWS SERVERLESS EVENT-DRIVEN ARCHITECTURES

Paper ID:
IJSDIP_2015_VOLUME 3_ISSUE 4_40-49
Author's Name:
Dileep Kumar Ghattamaneni
Volume:
3
Issue:
Issue 4
Year:
2015
Pages:
40-49

Abstract

This research study primarily focuses on the fundamental concepts of serverless within the context of event-driven architecture, with a particular emphasis on AWS (Amazon Web Services), as assessed through performance, reliability, and cost analysis. These are all implemented and computed in an earlier stage. AWS Lambda consists of several ideas related to ephemeral execution, triggers, and fine-grained payment models. These are all used as cloud service prototypes, such as Amazon EC2 auto-scaling and S3 Event triggers, in the early stages of distributed queue systems. These are all influenced by the development of serverless computing. These types of methodology utilize the comparison among the frameworks to analyze the latency, throughput, fault tolerance, and billing structure. All of which have the advantages and disadvantages of event-driven architecture. The findings indicate that serverless technology offers greater elasticity, cost-effectiveness, and performance stability across different periods. This study primarily examined the various offers related to transitioning to cloud computing and analyzed the historical work on future serverless research.

Keywords

AWS Serverless computing, Event-driven architecture, Performance Evaluation, Reliability assessment, Cost optimization, cloud computing.

References

1. Kommera, A. R. (2013). The role of distributed systems in cloud computing: Scalability, efficiency, and resilience. NeuroQuantology, 11(3), 507-516. 2. Klein, J., Gorton, I., Ernst, N., Donohoe, P., Pham, K., & Matser, C. (2014). Quality attribute-guided evaluation of NoSQL databases: an experience report. 3. Tanimoto, S., Sato, R., Kato, K., Iwashita, M., Seki, Y., Sato, H., & Kanai, A. (2014, September). A study of risk assessment quantification in cloud computing. In 2014 17th International Conference on Network-Based Information Systems (pp. 426-431). IEEE. 4. Kaur, K. (2014). Deadline Scheduling Algorithms in Cloud Computing: A Review. International Journal of Computer Applications, 96(24). 5. Wang, L., Liu, M., & Meng, M. Q. H. (2014, May). Hierarchical auction-based mechanism for real-time resource retrieval in cloud mobile robotic system. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (pp. 2164-2169). IEEE.. 6. Hemmati, M., Mehrabi, A., Karamkhani, J., Haidari, Z., Shahbaz-poor, H.-R., Moradi, A., & Ranjbari, M. (2014). Studying and comparing the effectiveness of brain stimulation over the skull through TDCS direct electrical current and matrix to reduce craving of methamphetamine. International Academic Journal of Social Sciences, 1(2), 71–79. 7. Harmsma, E. J. (2012). An approach towards a scalable lock-free asynchronous event loop with encapsulated blocking capabilities (Doctoral dissertation, Faculty of Science and Engineering). 8. Vicario, E. (2000). Architectural Views: The State of Practice in Open-Source Software Projects. LNCS 14889 Software Architecture, 396. 9. Erenkrantz, J. R., Gorlick, M., Suryanarayana, G., & Taylor, R. N. (2007, September). From representations to computations: the evolution of web architectures. In Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering (pp. 255-264). 10. Schwendner, A. (2010). Distributed functional programming in Scheme (Doctoral dissertation, Massachusetts Institute of Technology). 11. Estrin, D., Chandy, K. M., Young, R. M., Smarr, L., Odlyzko, A., Clark, D., ... & Elliott, C. (2009). Participatory sensing: applications and architecture [internet predictions]. IEEE Internet Computing, 14(1), 12-42. 12. Zendehboudi, M., Azimpour, J., & Gorginpour, H. (2014). Offering a Method for Ensuring Data Storage Security in the Cloud Network by Using Kerberos Algorithm. International Academic Journal of Science and Engineering, 1(2), 75–81. 13. Hwang, K., Jin, H., Ho, R., & Ro, W. (2000, May). Reliable cluster computing with a new checkpointing RAID-x architecture. In Proceedings 9th Heterogeneous Computing Workshop (HCW 2000)(Cat. No. PR00556) (pp. 171-184). IEEE. 14. Yasuda, K., & Hagino, T. (2001). Design and concept of ad-hoc filesystem. IEICE transactions on communications, 84(4), 920-929. 15. Shirkani, S., Ghanbari, E., & Maleki, S. (2014). Assessment of the relationship between infrastructures of knowledge management and organizational performance in petrochemical company of Mehr. International Academic Journal of Organizational Behavior and Human Resource Management, 1(1), 80–95. 16. Cuenca-Acuna, F. M., & Nguyen, T. D. (2001, August). Cooperative caching middleware for cluster-based servers. In Proceedings 10th IEEE International Symposium on High Performance Distributed Computing (pp. 303-314). IEEE. 17. Lepreau, J., & Eide, E. (2000). Session summaries from the 17th symposium on operating systems principle (SOSP'99). ACM SIGOPS Operating Systems Review, 34(2), 4-5.