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A survey on the scheduling mechanisms in serverless computing: a taxonomy, challenges, and trends

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Abstract

In recent years, serverless computing has received significant attention due to its innovative approach to cloud computing. In this novel approach, a new payment model is presented, and a microservice architecture is implemented to convert applications into functions. These characteristics make it an appropriate choice for topics related to the Internet of Things (IoT) devices at the network’s edge because they constantly suffer from a lack of resources, and the topic of optimal use of resources is significant for them. Scheduling algorithms are used in serverless computing to allocate resources, which is a mechanism for optimizing resource utilization. This process can be challenging due to a number of factors, including dynamic behavior, heterogeneous resources, workloads that vary in volume, and variations in number of requests. Therefore, these factors have caused the presentation of algorithms with different scheduling approaches in the literature. Despite many related serverless computing studies in the literature, to the best of the author’s knowledge, no systematic, comprehensive, and detailed survey has been published that focuses on scheduling algorithms in serverless computing. In this paper, we propose a survey on scheduling approaches in serverless computing across different computing environments, including cloud computing, edge computing, and fog computing, that are presented in a classical taxonomy. The proposed taxonomy is classified into six main approaches: Energy-aware, Data-aware, Deadline-aware, Package-aware, Resource-aware, and Hybrid. After that, open issues and inadequately investigated or new research challenges are discussed, and the survey is concluded.

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Data availability

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Li, Y., Lin, Y., Wang, Y., Ye, K., Xu, C.: Serverless computing: state-of-the-art, challenges and opportunities. IEEE Trans. Serv. Comput. 16(2), 1522–1539 (2022)

    Article  Google Scholar 

  2. Barcelona-Pons, D., Sutra, P., Sánchez-Artigas, M., París, G., García-López, P.: Stateful serverless computing with crucial. ACM Trans. Softw. Eng. Methodol. 31(3), 1–38 (2022)

    Article  Google Scholar 

  3. Sharma, P.: Challenges and opportunities in sustainable serverless computing. ACM SIGENERGY Energy Inform. Rev. 3(3), 53–58 (2023)

    Article  Google Scholar 

  4. Cao, Y., Niu, B., Wang, H., Zhao, X.: Event-based adaptive resilient control for networked nonlinear systems against unknown deception attacks and actuator saturation. Int. J. Robust Nonlinear Control (2024). https://doi.org/10.1002/rnc.7231

    Article  Google Scholar 

  5. Lee, H., Satyam, K., Fox, G.: Evaluation of production serverless computing environments. In: 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), pp. 442–450. IEEE (2018)

  6. Wu, W., Zhang, L., Wu, Y., Zhao, H.: Adaptive saturated two-bit-triggered bipartite consensus control for networked MASs with periodic disturbances: a low-computation method. IMA J. Math. Control. Inf. (2024). https://doi.org/10.1093/imamci/dnae002

    Article  Google Scholar 

  7. Le, D.N., Pal, S., Pattnaik, P.K., OpenFaaS. Cloud computing solutions: architecture, data storage, implementation and security. 287–303 (2022)

  8. Marin, E., Perino, D., Di Pietro, R.: Serverless computing: a security perspective. J. Cloud Comput. 11(1), 1–12 (2022)

    Article  CAS  Google Scholar 

  9. Huang, S., Zong, G., Zhao, N., Zhao, X., Ahmad, A.M.: Performance recovery-based fuzzy robust control of networked nonlinear systems against actuator fault: a deferred actuator-switching method. Fuzzy Sets Syst. 480, 108858 (2024). https://doi.org/10.1016/j.fss.2024.108858

    Article  MathSciNet  Google Scholar 

  10. Tarahomi, M., Izadi, M., Ghobaei-Arani, M.: An efficient power-aware VM allocation mechanism in cloud data centers: a micro genetic-based approach. Cluster Comput. 24, 919–934 (2021). https://doi.org/10.1007/s10586-020-03152-9

    Article  Google Scholar 

  11. Mampage, A., Karunasekera, S., Buyya, R.: A holistic view on resource management in serverless computing environments: taxonomy and future directions. ACM Comput. Surv. 54(11s), 1–36 (2022)

    Article  Google Scholar 

  12. Benedetti, P., Femminella, M., Reali, G., Steenhaut, K.: Experimental analysis of the application of serverless computing to IoT platforms. Sensors 21(3), 928 (2021)

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  13. Sarkar, S., Wankar, R., Srirama, S.N., Suryadevara, N.K.: Serverless management of sensing systems for fog computing framework. IEEE Sens. J. 20(3), 1564–1572 (2019)

    Article  ADS  Google Scholar 

  14. Xue, B., Yang, Q., Jin, Y., Zhu, Q., Lan, J., Lin, Y., Tan, J., et al.: Genotoxicity assessment of haloacetaldehyde disinfection byproducts via a simplified yeast-based toxicogenomics assay. Environ. Sci. Technol. 57(44), 16823–16833 (2023). https://doi.org/10.1021/acs.est.3c04956

    Article  ADS  CAS  PubMed  Google Scholar 

  15. Zhang, C., Zhu, D., Luo, Q., Liu, L., Liu, D., Yan, L., Zhang, Y.: Major factors controlling fracture development in the Middle Permian Lucaogou Formation tight oil reservoir, Junggar Basin, NW China. J. Asian Earth Sci. 146, 279–295 (2017). https://doi.org/10.1016/j.jseaes.2017.04.032

    Article  ADS  Google Scholar 

  16. Rajan, A.P.: A review on serverless architectures-function as a service (FaaS) in cloud computing. TELKOMNIKA (Telecommun. Comput. Electron. Control) 18(1), 530–537 (2020)

    Article  MathSciNet  Google Scholar 

  17. Hellerstein, J.M., Faleiro, J., Gonzalez, J.E., Schleier-Smith, J., Sreekanti, V., Tumanov, A., Wu, C.: Serverless computing: one step forward, two steps back. arXiv preprint arXiv:1812.03651 (2018)

  18. Naranjo, D.M., Risco, S., de Alfonso, C., Pérez, A., Blanquer, I., Moltó, G.: Accelerated serverless computing based on GPU virtualization. J. Parallel Distrib. Comput. 139, 32–42 (2020)

    Article  Google Scholar 

  19. Bebortta, S., Das, S.K., Kandpal, M., Barik, R.K., Dubey, H.: Geospatial serverless computing: architectures, tools and future directions. ISPRS Int. J. Geo Inf. 9(5), 311 (2020)

    Article  Google Scholar 

  20. Patros, P., Spillner, J., Papadopoulos, A.V., Varghese, B., Rana, O., Dustdar, S.: Toward sustainable serverless computing. IEEE Internet Comput. 25(6), 42–50 (2021)

    Article  Google Scholar 

  21. Hassan, H.B., Barakat, S.A., Sarhan, Q.I.: Survey on serverless computing. J. Cloud Comput. 10(1), 1–29 (2021)

    Article  Google Scholar 

  22. Jia, Z., Witchel, E.: Nightcore: efficient and scalable serverless computing for latency-sensitive, interactive microservices. In: Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 152–166 (2021)

  23. Grafberger, A., Chadha, M., Jindal, A., Gu, J., Gerndt, M.: FedLess: secure and scalable federated learning using serverless computing. In: 2021 IEEE International Conference on Big Data (Big Data), pp. 164–173. IEEE (2021)

  24. Kelly, D., Glavin, F., Barrett, E.: Serverless computing: Behind the scenes of major platforms. In: 2020 IEEE 13th International Conference on Cloud Computing (CLOUD), pp. 304–312. IEEE (2020)

  25. Khatri, D., Khatri, S.K., Mishra, D.: Potential bottleneck and measuring performance of serverless computing: a literature study. In: 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp. 161–164. IEEE (2020)

  26. Kjorveziroski, V., Bernad Canto, C., Juan Roig, P., Gilly, K., Mishev, A., Trajkovik, V., Filiposka, S.: IoT serverless computing at the edge: open issues and research direction. Trans. Netw. Commun. (2021)

  27. Lenarduzzi, V., Daly, J., Martini, A., Panichella, S., Tamburri, D.A.: Toward a technical debt conceptualization for serverless computing. IEEE Softw. 38(1), 40–47 (2020)

    Article  Google Scholar 

  28. Golec, M., Ozturac, R., Pooranian, Z., Gill, S.S., Buyya, R.: iFaaSBus: a security-and privacy-based lightweight framework for serverless computing using IoT and machine learning. IEEE Trans. Ind. Inf. 18(5), 3522–3529 (2021)

    Article  Google Scholar 

  29. Mondal, S.K., Pan, R., Kabir, H.M., Tian, T., Dai, H.N.: Kubernetes in IT administration and serverless computing: an empirical study and research challenges. J. Supercomput. 78(2), 2937–2987 (2022)

    Article  Google Scholar 

  30. Prakash, A.A., Kumar, K.S.: Cloud serverless security and services: a survey. In: Applications of Computational Methods in Manufacturing and Product Design, pp. 453–462. Springer, Singapore (2022)

  31. Kumari, A., Behera, R.K., Sahoo, B., Misra, S.: Role of serverless computing in healthcare systems: case studies. In: International Conference on Computational Science and Its Applications, pp. 123–134. Springer, Cham (2022)

  32. Zhang, Y., Goiri, Í., Chaudhry, G.I., Fonseca, R., Elnikety, S., Delimitrou, C., Bianchini, R.: Faster and cheaper serverless computing on harvested resources. In: Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles, pp. 724–739 (2021)

  33. Yan, M., Castro, P., Cheng, P., Ishakian, V.: Building a chatbot with serverless computing. In: Proceedings of the 1st International Workshop on Mashups of Things and APIs, pp. 1–4 (2016)

  34. Sewak, M., Singh, S.: Winning in the era of serverless computing and function as a service. In: 2018 3rd International Conference for Convergence in Technology (I2CT), pp. 1–5. IEEE (2018)

  35. Li, Z., Guo, L., Cheng, J., Chen, Q., He, B., Guo, M.: The serverless computing survey: a technical primer for design architecture. ACM Comput. Surv. 54(10s), 1–34 (2022)

    Article  Google Scholar 

  36. Sankaran, A., Datta, P. and Bates, A.: Workflow integration alleviates identity and access management in serverless computing. In: Annual Computer Security Applications Conference, pp. 496–509 (2020)

  37. Stigler, M.: Understanding serverless computing. In: Beginning Serverless Computing, pp. 1–14. Apress, Berkeley (2018)

  38. Ginzburg, S., Freedman, M.J.: Serverless isn’t server-less: measuring and exploiting resource variability on cloud FaaS platforms. In: Proceedings of the 2020 Sixth International Workshop on Serverless Computing, pp. 43–48 (2020)

  39. Taibi, D., Spillner, J., Wawruch, K.: Serverless computing-where are we now, and where are we heading? IEEE Softw. 38(1), 25–31 (2020)

    Article  Google Scholar 

  40. Ghorbian, M., Ghobaei-Arani, M.: A Blockchain-enabled serverless approach for IoT healthcare applications. In: Serverless Computing: Principles and Paradigms, pp. 193–218. Springer, Cham (2023)

  41. Casale, G., Artač, M., Van Den Heuvel, W.J., van Hoorn, A., Jakovits, P., Leymann, F., Long, M., Papanikolaou, V., Presenza, D., Russo, A., Srirama, S.N.: Radon: rational decomposition and orchestration for serverless computing. SICS Softw.-Intensive Cyber-Phys. Syst. 35(1), 77–87 (2020)

    Google Scholar 

  42. Lloyd, W., Ramesh, S., Chinthalapati, S., Ly, L., Pallickara, S.: Serverless computing: an investigation of factors influencing microservice performance. In: 2018 IEEE International Conference on Cloud Engineering (IC2E), pp. 159–169. IEEE (2018)

  43. Xu, Z., Zhang, H., Geng, X., Wu, Q., Ma, H.: Adaptive function launching acceleration in serverless computing platforms. In: 2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS), pp. 9–16. IEEE (2019)

  44. Adzic, G., Chatley, R.: Serverless computing: economic and architectural impact. In: Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, pp. 884–889 (2017)

  45. Mohanty, S.K., Premsankar, G., Di Francesco, M.: An evaluation of open source serverless computing frameworks. CloudCom 2018, 115–120 (2018)

    Google Scholar 

  46. Aske, A., Zhao, X.: Supporting multi-provider serverless computing on the edge. In: Proceedings of the 47th International Conference on Parallel Processing Companion, pp. 1–6 (2018)

  47. Kaffes, K., Yadwadkar, N.J., Kozyrakis, C.: Centralized core-granular scheduling for serverless functions. In: Proceedings of the ACM Symposium on Cloud Computing, pp. 158–164 (2019)

  48. Mahmoudi, N., Khazaei, H.: Performance modeling of serverless computing platforms. IEEE Trans. Cloud Comput. 10(4), 2834–2847 (2020)

    Article  Google Scholar 

  49. Kaffes, K., Yadwadkar, N.J., Kozyrakis, C.: Practical scheduling for real-world serverless computing. arXiv preprint arXiv:2111.07226 (2021)

  50. Zuk, P., Rzadca, K.: Scheduling methods to reduce response latency of function as a service. In: 2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), pp. 132–140. IEEE (2020)

  51. Jonas, E., Schleier-Smith, J., Sreekanti, V., Tsai, C.C., Khandelwal, A., Pu, Q., Shankar, V., Carreira, J., Krauth, K., Yadwadkar, N., Gonzalez, J.E.: Cloud programming simplified: a berkeley view on serverless computing. arXiv preprint arXiv:1902.03383 (2019)

  52. Bisht, J., Vampugani, V.S.: Load and cost-aware min-min workflow scheduling algorithm for heterogeneous resources in fog, cloud, and edge scenarios. Int. J. Cloud Appl. Comput. 12(1), 1–20 (2022)

    Google Scholar 

  53. Majewski, M., Pawlik, M., Malawski, M.: Algorithms for scheduling scientific workflows on serverless architecture. In: 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pp. 782–789. IEEE (2021)

  54. Mahmoudi, N., Khazaei, H.: MLProxy: SLA-aware reverse proxy for machine learning inference serving on serverless computing platforms. arXiv preprint arXiv:2202.11243 (2022)

  55. Nezafat Tabalvandani, M.A., Hosseini Shirvani, M., Motameni, H.: Reliability-aware web service composition with cost minimization perspective: a multi-objective particle swarm optimization model in multi-cloud scenarios. Soft Comput. 1–24 (2023)

  56. Suresh, A., Somashekar, G., Varadarajan, A., Kakarla, V.R., Upadhyay, H., Gandhi, A.: Ensure: efficient scheduling and autonomous resource management in serverless environments. In: 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), pp. 1–10. IEEE (August)

  57. Pathak, P., Singh, P.: Kubernetes and Docker the Star Duo of container culture. In: Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication: MARC 2021, pp. 79–90. Springer, Singapore (2022)

  58. Balaji, K., Sai Kiran, P., Sunil Kumar, M.: Power aware virtual machine placement in IaaS cloud using discrete firefly algorithm. Appl. Nanosci. 13(3), 2003–2011 (2023)

    Article  ADS  CAS  Google Scholar 

  59. Jiang, J., Gan, S., Du, B., Alonso, G., Klimovic, A., Singla, A., Wu, W., Wang, S., Zhang, C.: A systematic evaluation of machine learning on serverless infrastructure. VLDB J. 1–25 (2023)

  60. Wang, H., Niu, D., Li, B.: Distributed machine learning with a serverless architecture. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pp. 1288–1296. IEEE (2019)

  61. Mampage, A., Karunasekera, S., Buyya, R.: Deep reinforcement learning for application scheduling in resource-constrained, multi-tenant serverless computing environments. Future Gener. Comput. Syst. 143, 277–292 (2023)

    Article  Google Scholar 

  62. Alqaryouti, O., Siyam, N.: Serverless computing and scheduling tasks on cloud: a review. Am. Acad. Sci. Res. J. Eng. Technol. Sci. 40(1), 235–247 (2018)

    Google Scholar 

  63. Kjorveziroski, V., Filiposka, S., Trajkovik, V.: IoT serverless computing at the edge: a systematic mapping review. Computers 10(10), 130 (2021)

    Article  Google Scholar 

  64. Saurav, S.K., Benedict, S.: A taxonomy and survey on energy-aware scientific workflows scheduling in large-scale heterogeneous architecture. In: 2021 6th International Conference on Inventive Computation Technologies (ICICT), pp. 820–826. IEEE (2021)

  65. Shafiei, H., Khonsari, A., Mousavi, P.: Serverless computing: a survey of opportunities, challenges, and applications. ACM Comput. Surv. 54(11s), 1–32 (2022)

    Article  Google Scholar 

  66. Xie, R., Tang, Q., Qiao, S., Zhu, H., Yu, F.R., Huang, T.: When serverless computing meets edge computing: architecture, challenges, and open issues. IEEE Wirel. Commun. 28(5), 126–133 (2021)

    Article  Google Scholar 

  67. Cassel, G.A.S., Rodrigues, V.F., da Rosa Righi, R., Bez, M.R., Nepomuceno, A.C., da Costa, C.A.: Serverless computing for Internet of Things: a systematic literature review. Future Gener. Comput. Syst. 128, 299–316 (2022)

    Article  Google Scholar 

  68. Ghobaei-Arani, M. and Ghorbian, M.: Scheduling mechanisms in serverless computing. In: Serverless Computing: Principles and Paradigms, pp. 243–273. Springer, Cham (2023)

  69. Pérez, A., Risco, S., Naranjo, D.M., Caballer, M., Moltó, G.: On-premises serverless computing for event-driven data processing applications. In: 2019 IEEE 12th International Conference on Cloud Computing (CLOUD), pp. 414–421. IEEE (2019)

  70. Jarachanthan, J., Chen, L., Xu, F., Li, B.: AMPS-Inf: automatic model partitioning for serverless inference with cost efficiency. In: 50th International Conference on Parallel Processing, pp. 1–12 (2021)

  71. Hosseini Shirvani, M., Noorian Talouki, R.: Bi-objective scheduling algorithm for scientific workflows on cloud computing platform with makespan and monetary cost minimization approach. Complex Intell. Syst. 8(2), 1085–1114 (2022)

    Article  Google Scholar 

  72. Wu, S., Tao, Z., Fan, H., Huang, Z., Zhang, X., Jin, H., Yu, C., Cao, C.: Container lifecycle‐aware scheduling for serverless computing. Software 52(2), 337–352 (2022)

    Google Scholar 

  73. Kallam, S., Patan, R., Ramana, T.V., Gandomi, A.H.: Linear weighted regression and energy-aware greedy scheduling for heterogeneous big data. Electronics 10(5), 554 (2021)

    Article  Google Scholar 

  74. Aslanpour, M.S., Toosi, A.N., Cheema, M.A., Gaire, R.: Energy-aware resource scheduling for serverless edge computing. In: 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pp. 190–199. IEEE (2022)

  75. Gunasekaran, J.R., Thinakaran, P., Chidambaram, N., Kandemir, M.T., Das, C.R.: Fifer: tackling underutilization in the serverless era. arXiv preprint arXiv:2008.12819 (2020)

  76. Aslanpour, M.S., Toosi, A.N., Gaire, R. and Cheema, M.A.: WattEdge: a holistic approach for empirical energy measurements in edge computing. In: International Conference on Service-Oriented Computing, pp. 531–547. Springer, Cham (2021)

  77. Rausch, T., Rashed, A., Dustdar, S.: Optimized container scheduling for data-intensive serverless edge computing. Future Gener. Comput. Syst. 114, 259–271 (2021)

    Article  Google Scholar 

  78. Wu, J., Wu, M., Li, H., Li, L., Li, L.: A serverless-based, on-the-fly computing framework for remote sensing image collection. Remote Sens. 14(7), 1728 (2022)

    Article  ADS  Google Scholar 

  79. Yu, M., Cao, T., Wang, W., Chen, R.: Restructuring serverless computing with data-centric function orchestration. arXiv preprint arXiv:2109.13492 (2021)

  80. Das, S.: Ant Colony Optimization for MapReduce Application to Optimise Task Scheduling in Serverless Platform (Doctoral dissertation, Dublin, National College of Ireland) (2021)

  81. Seubring, W., Lazovik, A., Blaauw, F.: Data Locality Aware Scheduling on a Serverless Edge Platform (Doctoral dissertation) (2021)

  82. Jindal, A., Gerndt, M., Chadha, M., Podolskiy, V., Chen, P.: Function delivery network: extending serverless computing for heterogeneous platforms. Software 51(9), 1936–1963 (2021)

    Google Scholar 

  83. Nestorov, A.M., Polo, J., Misale, C., Carrera, D., Youssef, A.S.: Performance evaluation of data-centric workloads in serverless environments. In: 2021 IEEE 14th International Conference on Cloud Computing (CLOUD), pp. 491–496. IEEE (2021)

  84. Przybylski, B., Żuk, P., Rzadca, K.: Data-driven scheduling in serverless computing to reduce response time. In: 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pp. 206–216. IEEE (2021)

  85. García-López, P., Sánchez-Artigas, M., Shillaker, S., Pietzuch, P., Breitgand, D., Vernik, G., Sutra, P., Tarrant, T., Ferrer, A.J.: Servermix: tradeoffs and challenges of serverless data analytics. arXiv preprint arXiv:1907.11465 (2019)

  86. HoseinyFarahabady, M.R., Taheri, J., Zomaya, A.Y. and Tari, Z.: Data-intensive workload consolidation in serverless (Lambda/FaaS) platforms. In: 2021 IEEE 20th International Symposium on Network Computing and Applications (NCA), pp. 1–8. IEEE (2021)

  87. Tang, Y. and Yang, J.: Lambdata: optimizing serverless computing by making data intents explicit. In: 2020 IEEE 13th International Conference on Cloud Computing (CLOUD), pp. 294–303. IEEE (2020)

  88. Singhvi, A., Houck, K., Balasubramanian, A., Shaikh, M.D., Venkataraman, S., Akella, A.: Archipelago: a scalable low-latency serverless platform. arXiv preprint arXiv:1911.09849 (2019)

  89. Asghari Alaie, Y., Hosseini Shirvani, M., Rahmani, A.M.: A hybrid bi-objective scheduling algorithm for execution of scientific workflows on cloud platforms with execution time and reliability approach. J. Supercomput. 79(2), 1451–1503 (2023)

    Article  Google Scholar 

  90. Mampage, A., Karunasekera, S., Buyya, R.: Deadline-aware dynamic resource management in serverless computing environments. In: 2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pp. 483–492. IEEE (2021)

  91. Wang, B., Ali-Eldin, A., Shenoy, P.: Lass: running latency sensitive serverless computations at the edge. In: Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing, pp. 239–251 (2021)

  92. Krishna, S.R., Majji, S., Kishore, S.K., Jaiswal, S., Kostka, J.A.L., Chouhan, A.S.: Optimization of time-driven scheduling technique for serverless cloud computing. Turk. J. Comput. Math. Educ. 12(10), 1–8 (2021)

    Google Scholar 

  93. Zuk, P., Rzadca, K.: Reducing response latency of composite functions-as-a-service through scheduling. J. Parallel Distrib. Comput. 167, 18–30 (2022)

    Article  Google Scholar 

  94. Fan, D. and He, D.: A scheduler for serverless framework base on kubernetes. In: Proceedings of the 2020 4th High Performance Computing and Cluster Technologies Conference & 2020 3rd International Conference on Big Data and Artificial Intelligence, pp. 229–232 (2020)

  95. Totoy, G., Boza, E.F., Abad, C.L.: An Extensible Scheduler for the OpenLambda FaaS Platform. Min-Move’18 (2018)

  96. Aumala, G., Boza, E., Ortiz-Avilés, L., Totoy, G., Abad, C.: Beyond load balancing: package-aware scheduling for serverless platforms. In: 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), pp. 282–291. IEEE (2019)

  97. Bai, T., Nie, J.Y., Zhao, W.X., Zhu, Y., Du, P., Wen, J.R.: An attribute-aware neural attentive model for next basket recommendation. In: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, pp. 1201–1204 (2018)

  98. Chetabi, F.A., Ashtiani, M., Saeedizade, E.: A package-aware approach for function scheduling in serverless computing environments. J.f Grid Comput. 21(2), 23 (2023)

    Article  Google Scholar 

  99. Ebrahimpour, H., Ashtiani, M., Bakhshi, F., Bakhtiariazad, G.: A heuristic-based package-aware function scheduling approach for creating a trade-off between cold start time and cost in FaaS computing environments. J. Supercomput. 1–49 (2023)

  100. Suresh, A., Gandhi, A.: Fnsched: an efficient scheduler for serverless functions. In: Proceedings of the 5th international workshop on serverless computing, pp. 19–24 (2019)

  101. Yuvaraj, N., Karthikeyan, T., Praghash, K.: An improved task allocation scheme in serverless computing using gray wolf Optimization (GWO) based reinforcement learning (RIL) approach. Wirel. Pers. Commun. 117(3), 2403–2421 (2021)

    Article  Google Scholar 

  102. Cheng, Y. and Zhou, Z.: Autonomous resource scheduling for real-time and stream processing. In: 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), pp. 1181–1184. IEEE (2018)

  103. Lakhan, A., Mohammed, M.A., Rashid, A.N., Kadry, S., Panityakul, T., Abdulkareem, K.H., Thinnukool, O.: Smart-contract aware ethereum and client-fog-cloud healthcare system. Sensors 21(12), 4093 (2021)

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  104. Kim, Y.K., HoseinyFarahabady, M.R., Lee, Y.C., Zomaya, A.Y.: Automated fine-grained cpu cap control in serverless computing platform. IEEE Trans. Parallel Distrib. Syst. 31(10), 2289–2301 (2020)

    Article  Google Scholar 

  105. Patterson, L., Pigorovsky, D., Dempsey, B., Lazarev, N., Shah, A., Steinhoff, C., Bruno, A., Hu, J., Delimitrou, C.: A hardware-software stack for serverless edge swarms. arXiv preprint arXiv:2112.14831 (2021)

  106. Soltani, B., Ghenai, A. and Zeghib, N.: A migration-based approach to execute long-duration multi-cloud serverless functions. In: ICAASE, pp. 42–50 (2018)

  107. Zhang, H., Shen, M., Huang, Y., Wen, Y., Luo, Y., Gao, G., Guan, K.: A serverless cloud-fog platform for dnn-based video analytics with incremental learning. arXiv preprint arXiv:2102.03012 (2021)

  108. Gadepalli, P.K., Peach, G., Cherkasova, L., Aitken, R., Parmer, G.: Challenges and opportunities for efficient serverless computing at the edge. In: 2019 38th Symposium on Reliable Distributed Systems (SRDS), pp. 261–2615. IEEE (2019)

  109. Fard, H.M., Prodan, R., Wolf, F.: Dynamic multi-objective scheduling of microservices in the cloud. In: 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), pp. 386–393. IEEE (2020)

  110. Zhang, M., Krintz, C., Wolski, R.: Edge‐adaptable serverless acceleration for machine learning Internet of Things applications. Software 51(9), 1852–1867 (2021)

    Google Scholar 

  111. Aytekin, A., Johansson, M.: Exploiting serverless runtimes for large-scale optimization. In: 2019 IEEE 12th International Conference on Cloud Computing (CLOUD), pp. 499–501. IEEE (2019)

  112. Huang, Z., Mi, Z., Hua, Z.: HCloud: a trusted JointCloud serverless platform for IoT systems with blockchain. China Commun. 17(9), 1–10 (2020)

    Article  Google Scholar 

  113. Zhang, J., Wang, A., Li, M., Chen, Y., Cheng, Y., HyperFaaS: a truly elastic serverless computing framework

  114. Denninnart, C., Gentry, J., Salehi, M.A.: Improving robustness of heterogeneous serverless computing systems via probabilistic task pruning. In: 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 6–15. IEEE (2019)

  115. Ling W, Tian C, Ma L, Hu Z.: Lite-Service: a framework to build and schedule telecom applications in device, edge and cloud. In: 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS) 2018 Jun 28, pp. 708–717. IEEE (2018)

  116. Silab, M.V., Hassanpour, S.B., Khonsari, A., Dadlani, A.: On skipping redundant computation via smart task deployment for faster serverless. In: ICC 2022-IEEE International Conference on Communications (pp. 5475–5480). IEEE (2022)

  117. Tychalas, D., Karatza, H.: SaMW: a probabilistic meta-heuristic algorithm for job scheduling in heterogeneous distributed systems powered by microservices. Clust. Comput. 24(3), 1735–1759 (2021)

    Article  Google Scholar 

  118. Mujezinović, A., Ljubović, V.: Serverless architecture for workflow scheduling with unconstrained execution environment. In: 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 242–246. IEEE (2019)

  119. Denninnart, C. and Salehi, M.A.: SMSE: a serverless platform for multimedia cloud systems. arXiv preprint arXiv:2201.01940 (2022)

  120. Ao, L., Izhikevich, L., Voelker, G.M., Porter, G.: Sprocket: a serverless video processing framework. In: Proceedings of the ACM Symposium on Cloud Computing, pp. 263–274 (2018)

  121. Wen, Z., Wang, Y. and Liu, F.: StepConf: SLO-aware dynamic resource configuration for serverless function workflows. In: IEEE INFOCOM 2022-IEEE Conference on Computer Communications, pp. 1868–1877. IEEE (2022)

  122. Nesen, A., Bhargava, B.: Towards situational awareness with multimodal streaming data fusion: serverless computing approach. In: Proceedings of the International Workshop on Big Data in Emergent Distributed Environments, pp. 1–6 (2021)

  123. Wu, C., Sreekanti, V., Hellerstein, J.M.: Transactional causal consistency for serverless computing. In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 83–97 (2020)

  124. Carver, B., Zhang, J., Wang, A., Anwar, A., Wu, P., Cheng, Y.: Wukong: a scalable and locality-enhanced framework for serverless parallel computing. In: Proceedings of the 11th ACM Symposium on Cloud Computing, pp. 1–15 (2020)

  125. Tang, Q., Xie, R., Yu, F.R., Chen, T., Zhang, R., Huang, T., Liu, Y.: Distributed task scheduling in serverless edge computing networks for the internet of things: a learning approach. IEEE Internet Things J. 9(20), 19634–19648 (2022)

    Article  Google Scholar 

  126. De Palma, G., Giallorenzo, S., Mauro, J., Trentin, M., Zavattaro, G.: Topology-aware serverless function-execution scheduling. arXiv preprint arXiv:2205.10176 (2022)

  127. Lakhan, A., Mohammed, M.A., Rashid, A.N., Kadry, S., Abdulkareem, K.H., Nedoma, J., Martinek, R., Razzak, I.: Restricted Boltzmann machine assisted secure serverless edge system for internet of medical things. IEEE J. Biomed. Health Inform. 27(2), 673–683 (2022)

    Article  Google Scholar 

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This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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  1. Department of Computer Engineering, Qom Branch, Islamic Azad University, Qom, Iran

    Mohsen Ghorbian, Mostafa Ghobaei-Arani & Leila Esmaeili

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  1. Mohsen Ghorbian
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  3. Leila Esmaeili
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MG, MG-A, LE conducted this research. MG: Methodology, Software, Validation, Writing original draft. MG-A: Investigation, Resources, Data curation, Visualization. LE: Investigation, Visualization.

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Correspondence to Mostafa Ghobaei-Arani.

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Ghorbian, M., Ghobaei-Arani, M. & Esmaeili, L. A survey on the scheduling mechanisms in serverless computing: a taxonomy, challenges, and trends. Cluster Comput (2024). https://doi.org/10.1007/s10586-023-04264-8

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