Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 49 tok/s
Gemini 2.5 Pro 53 tok/s Pro
GPT-5 Medium 19 tok/s Pro
GPT-5 High 16 tok/s Pro
GPT-4o 103 tok/s Pro
Kimi K2 172 tok/s Pro
GPT OSS 120B 472 tok/s Pro
Claude Sonnet 4 39 tok/s Pro
2000 character limit reached

CloudSimSC: A Toolkit for Modeling and Simulation of Serverless Computing Environments (2309.10671v1)

Published 19 Sep 2023 in cs.DC

Abstract: Serverless computing is gaining traction as an attractive model for the deployment of a multitude of workloads in the cloud. Designing and building effective resource management solutions for any computing environment requires extensive long term testing, experimentation and analysis of the achieved performance metrics. Utilizing real test beds and serverless platforms for such experimentation work is often times not possible due to resource, time and cost constraints. Thus, employing simulators to model these environments is key to overcoming the challenge of examining the viability of such novel ideas for resource management. Existing simulation software developed for serverless environments lack generalizibility in terms of their architecture as well as the various aspects of resource management, where most are purely focused on modeling function performance under a specific platform architecture. In contrast, we have developed a serverless simulation model with induced flexibility in its architecture as well as the key resource management aspects of function scheduling and scaling. Further, we incorporate techniques for easily deriving monitoring metrics required for evaluating any implemented solutions by users. Our work is presented as CloudSimSC, a modular extension to CloudSim which is a simulator tool extensively used for modeling cloud environments by the research community. We discuss the implemented features in our simulation tool using multiple use cases.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (17)
  1. R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. De Rose, and R. Buyya, “Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,” Software: Practice and experience, vol. 41, no. 1, pp. 23–50, 2011.
  2. A. Mampage, S. Karunasekera, and R. Buyya, “Deadline-aware dynamic resource management in serverless computing environments,” in Proceedings of the 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid).   IEEE, 2021, pp. 483–492.
  3. N. Mahmoudi and H. Khazaei, “Simfaas: A performance simulator for serverless computing platforms,” arXiv preprint arXiv:2102.08904, 2021.
  4. “What is aws lambda? - aws lambda,” https://docs.aws.amazon.com/lambda/latest/dg/welcome.html, (Accessed on 05/22/2023).
  5. “Google cloud documentation  —  documentation,” https://cloud.google.com/docs, (Accessed on 05/22/2023).
  6. “Azure functions – serverless functions in computing — microsoft azure,” https://azure.microsoft.com/en-au/products/functions/, (Accessed on 05/22/2023).
  7. H. Jeon, C. Cho, S. Shin, and S. Yoon, “A cloudsim-extension for simulating distributed functions-as-a-service,” in Proceedings of the 20th International Conference on parallel and distributed computing, applications and technologies (PDCAT).   IEEE, 2019, pp. 386–391.
  8. F. Mastenbroek, G. Andreadis, S. Jounaid, W. Lai, J. Burley, J. Bosch, E. Van Eyk, L. Versluis, V. Van Beek, and A. Iosup, “Opendc 2.0: Convenient modeling and simulation of emerging technologies in cloud datacenters,” in Proceedings of the 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid).   IEEE, 2021, pp. 455–464.
  9. OpenFaas, “Home — openfaas - serverless functions made simple,” https://www.openfaas.com/, 2021, (Accessed on 11/22/2021).
  10. Kubeless, “Kubeless,” https://kubeless.io/, 2021, (Accessed on 11/22/2021).
  11. “Fission — fission,” https://fission.io/docs/, (Accessed on 05/23/2023).
  12. “Kubernetes,” https://kubernetes.io/, (Accessed on 05/23/2023).
  13. K. Kaffes, N. J. Yadwadkar, and C. Kozyrakis, “Centralized core-granular scheduling for serverless functions,” in Proceedings of the ACM Symposium on Cloud Computing, 2019, pp. 158–164.
  14. A. Suresh, G. Somashekar, A. Varadarajan, V. R. Kakarla, H. Upadhyay, and A. Gandhi, “Ensure: Efficient scheduling and autonomous resource management in serverless environments,” in Proceedings of the IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS).   IEEE, 2020, pp. 1–10.
  15. L. Wang, M. Li, Y. Zhang, T. Ristenpart, and M. Swift, “Peeking behind the curtains of serverless platforms,” in Proceedings of the Annual Technical Conference, 2018.
  16. “Wikipedia access traces — wikibench,” http://www.wikibench.eu/?page_id=60, (Accessed on 12/02/2020).
  17. M. Shahrad, R. Fonseca, Í. Goiri, G. Chaudhry, P. Batum, J. Cooke, E. Laureano, C. Tresness, M. Russinovich, and R. Bianchini, “Serverless in the wild: Characterizing and optimizing the serverless workload at a large cloud provider,” in Proceedings of the USENIX Annual Technical Conference, 2020, pp. 205–218.
Citations (3)

Summary

We haven't generated a summary for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.