Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

Serverless Edge Computing—Where We Are and What Lies Ahead

Published: 01 May 2023 Publication History

Abstract

The edge–cloud continuum combines heterogeneous resources, which are complex to manage. Serverless edge computing is a suitable candidate to manage the continuum by abstracting away the underlying infrastructure, improving developers’ experiences, and optimizing overall resource utilization. However, understanding and overcoming programming support, reliability, and performance engineering challenges are essential for the success of serverless edge computing. In this article, we review and evaluate the maturity of serverless approaches for the edge–cloud continuum. Our review includes commercial, community-driven offerings and approaches from academia. We identify several maturity levels of serverless edge computing and use them as criteria to evaluate the maturity of current state-of-the-art serverless approaches with a special focus on the programming, reliability, and performance challenges. Finally, we lay a road map toward the next generation of serverless edge computing systems.

References

[1]
S. Deng, H. Zhao, W. Fang, J. Yin, S. Dustdar, and A. Y. Zomaya, “Edge intelligence: The confluence of edge computing and artificial intelligence,” IEEE Internet Things J., vol. 7, no. 8, pp. 7457–7469, Aug. 2020.
[2]
M. S. Aslanpour et al., “Serverless edge computing: Vision and challenges,” in Proc. Australas. Comput. Sci. Week Multiconference, Feb. 2021, pp. 1–10.
[3]
H. Shafiei, A. Khonsari, and P. Mousavi, “Serverless computing: A survey of opportunities, challenges, and applications,” ACM Comput. Surv., vol. 54, no. 11s, pp. 1–32, Nov. 2022.
[4]
S. Nastic, P. Raith, A. Furutanpey, T. Pusztai, and S. Dustdar, “A serverless computing fabric for edge and cloud,” in Proc. IEEE 4th Int. Conf. Cogn. Mach. Intell. (CogMI), 2022, pp. 1–12.
[5]
S. Nastic et al., “Polaris scheduler: Edge sensitive and SLO aware workload scheduling in cloud-edge-IoT clusters,” in Proc. IEEE 14th Int. Conf. Cloud Comput. (CLOUD), 2021, pp. 206–216.
[6]
T. Pusztai et al., “Polaris scheduler: SLO- and topology-aware microservices scheduling at the edge,” in Proc. IEEE/ACM 15th Int. Conf. Utility Cloud Comput. (UCC), 2022, pp. 61–70.
[7]
P. Raith, T. Rausch, S. Dustdar, F. Rossi, V. Cardellini, and R. Ranjan, “Mobility-aware serverless function adaptations across the edge-cloud continuum,” in Proc. IEEE/ACM 15th Int. Conf. Utility Cloud Comput. (UCC), 2022, pp. 123–132.
[8]
V. Prokhorenko and M. A. Babar, “Architectural resilience in cloud, fog and edge systems: A survey,” IEEE Access, vol. 8, pp. 28,078–28,095, Feb. 2020.
[9]
V. Sreekanti, C. Wu, S. Chhatrapati, J. E. Gonzalez, J. M. Hellerstein, and J. M. Faleiro, “A fault-tolerance shim for serverless computing,” in Proc. 15th Eur. Conf. Comput. Syst., 2020, pp. 1–15.
[10]
H. Zhang, A. Cardoza, P. B. Chen, S. Angel, and V. Liu, “Fault-tolerant and transactional stateful serverless workflows,” in Proc. 14th USENIX Symp. Operating Syst. Des. Implementation (OSDI), 2020, pp. 1187–1204.
[11]
A. Jangda, D. Pinckney, Y. Brun, and A. Guha, “Formal foundations of serverless computing,” Proc. ACM Program. Lang., vol. 3, no. OOPSLA, pp. 1–26, Oct. 2019.
[12]
J. Scheuner et al., “TriggerBench: A performance benchmark for serverless function triggers (short paper),” in Proc. IEEE Int. Conf. Cloud Eng. (IC2E), 2022, pp. 96–103.
[13]
L. Baresi and G. Quattrocchi, “PAPS: A serverless platform for edge computing infrastructures,” Frontiers Sustain. Cities, vol. 3, Jul. 2021, Art. no. 690660.
[14]
“Kubeless.” GitHub. Accessed: Mar. 29, 2023. [Online]. Available: https://github.com/vmware-archive/kubeless
[15]
AWS Lambda.” Amazon. Accessed: Mar. 29, 2023. [Online]. Available: https://aws.amazon.com/lambda/
[16]
OpenFaaS. [Online]. Available: https://www.openfaas.com/
[17]
T. Pfandzelter and D. Bermbach, “tinyFaaS: A lightweight FaaS platform for edge environments,” in Proc. IEEE Int. Conf. Fog Comput. (ICFC), 2020, pp. 17–24.
[18]
S. Werner and T. Schirmer, “HARDLESS: A generalized serverless compute architecture for hardware processing accelerators,” in Proc. IEEE Int. Conf. Cloud Eng. (IC2E), 2022, pp. 79–84.
[19]
P. Benedetti, M. Femminella, G. Reali, and K. Steenhaut, “Reinforcement learning applicability for resource-based auto-scaling in serverless edge applications,” in Proc. IEEE Int. Conf. Pervasive Comput. Commun. Workshops Other Affiliated Events (PerCom Workshops), 2022, pp. 674–679.
[20]
D. M. Naranjo, S. Risco, C. de Alfonso, A. Pérez, I. Blanquer, and G. Moltó, “Accelerated serverless computing based on GPU virtualization,” J. Parallel Distrib. Comput., vol. 139, pp. 32–42, May 2020.
[21]
“Zappa.” GitHub. Accessed: Mar. 29, 2023. [Online]. Available: https://github.com/zappa/Zappa
[22]
“Chalice.” GitHub. Accessed: Mar. 29, 2023. [Online]. Available: https://github.com/aws/chalice
[23]
S. Burckhardt, C. Gillum, D. Justo, K. Kallas, C. McMahon, and C. S. Meiklejohn, “Durable functions: Semantics for stateful serverless,” Proc. ACM Program. Lang., vol. 5, no. OOPSLA, pp. 1–27, Oct. 2021.
[24]
W. Zhang, V. Fang, A. Panda, and S. Shenker, “Kappa: A programming framework for serverless computing,” in Proc. 11th ACM Symp. Cloud Comput., 2020, pp. 328–343.
[25]
P. Gackstatter, P. A. Frangoudis, and S. Dustdar, “Pushing serverless to the edge with webassembly runtimes,” in Proc. 22nd IEEE Int. Symp. Cluster, Cloud Internet Comput. (CCGrid), 2022, pp. 140–149.
[26]
S. Shillaker and P. Pietzuch, “FAASM: Lightweight isolation for efficient stateful serverless computing,” in Proc. USENIX Annu. Tech. Conf. (USENIX ATC), 2020, pp. 419–433.
[27]
“Master.” Kserve. Accessed: Mar. 29, 2023. [Online]. Available: https://kserve.github.io/website/master/
[28]
Knative. Accessed: Mar. 29, 2023. [Online]. Available: https://knative.dev/docs/
[29]
Nuclio. Accessed: Mar. 29, 2023. [Online]. Available: https://nuclio.io/
[30]
J. Li, S. G. Kulkarni, K. Ramakrishnan, and D. Li, “Understanding open source serverless platforms: Design considerations and performance,” in Proc. 5th Int. Workshop Serverless Comput., 2019, pp. 37–42.
[31]
T. Rausch, A. Rashed, and S. Dustdar, “Optimized container scheduling for data-intensive serverless edge computing,” Future Gener. Comput. Syst., vol. 114, pp. 259–271, Jan. 2021.
[32]
R. Hetzel, T. Kärkkäinen, and J. Ott, “μactor: Stateful serverless at the edge,” in Proc. 1st Workshop Serverless Mobile Netw. 6G Commun., 2021, pp. 1–6.
[33]
B. Wang, A. Ali-Eldin, and P. Shenoy, “Lass: Running latency sensitive serverless computations at the edge,” in Proc. 30th Int. Symp. High-Perform. Parallel Distrib. Comput., 2021, pp. 239–251.
[34]
F. Lordan, D. Lezzi, and R. M. Badia, “Colony: Parallel functions as a service on the cloud-edge continuum,” in Proc. Eur. Conf. Parallel Process., Cham, Switzerland: Springer-Verlag, 2021, pp. 269–284.
[35]
J. Hu et al., “HiveMind: A scalable and serverless coordination control platform for UAV swarms,” 2020,.
[36]
L. Baresi, D. Y. X. Hu, G. Quattrocchi, and L. Terracciano, “NEPTUNE: Network- and GPU-aware management of serverless functions at the edge,” in Proc. 17th Symp. Softw. Eng. Adaptive Self-Manag. Syst. (SEAMS), New York, NY, USA: Association for Computing Machinery, 2022, pp. 144–155.
[37]
Z. Li, L. Guo, J. Cheng, Q. Chen, B. He, and M. Guo, “The serverless computing survey: A technical primer for design architecture,” ACM Comput. Surv., vol. 54, no. 10s, pp. 1–34.
[38]
P. Karhula, J. Janak, and H. Schulzrinne, “Checkpointing and migration of IoT edge functions,” in Proc. 2nd Int. Workshop Edge Syst., Analytics Netw., 2019, pp. 60–65.
[39]
S. Burckhardt et al., “Netherite: Efficient execution of serverless workflows,” Proc. VLDB Endowment, vol. 15, no. 8, pp. 1591–1604, Apr. 2022.
[41]
R. Klingler, N. Trifunovic, and J. Spillner, “Beyond@ cloudfunction: Powerful code annotations to capture serverless runtime patterns,” in Proc. 7th Int. Workshop Serverless Comput. (WoSC), 2021, pp. 23–28.
[42]
C. P. Smith, A. Jindal, M. Chadha, M. Gerndt, and S. Benedict, “FaDO: FaaS functions and data orchestrator for multiple serverless edge-cloud clusters,” in Proc. IEEE 6th Int. Conf. Fog Edge Comput. (ICFEC), 2022, pp. 17–25.
[43]
IBM.” Apache OpenWhisk. Accessed: Mar. 29, 2023. [Online]. Available: https://openwhisk.apache.org/
[44]
D. Bermbach, J. Bader, J. Hasenburg, T. Pfandzelter, and L. Thamsen, “Auctionwhisk: Using an auction-inspired approach for function placement in serverless fog platforms,” Softw. Pract. Experience, vol. 52, no. 5, pp. 1143–1169, May 2022.
[45]
R. Wolski, C. Krintz, F. Bakir, G. George, and W.-T. Lin, “Cspot: Portable, multi-scale functions-as-a-service for IoT,” in Proc. 4th ACM/IEEE Symp. Edge Comput., 2019, pp. 236–249.
[46]
Z. Li et al., “FaaSFlow: Enable efficient workflow execution for function-as-a-service,” in Proc. 27th ACM Int. Conf. Architectural Support Program. Lang. Operating Syst., 2022, pp. 782–796.
[47]
X. Li, P. Kang, J. Molone, W. Wang, and P. Lama, “KneeScale: Efficient resource scaling for serverless computing at the edge,” in Proc. 22nd IEEE Int. Symp. Cluster, Cloud Internet Comput. (CCGrid), 2022, pp. 180–189.
[48]
“Cloud functions.” Google. Accessed: Mar. 29, 2023. [Online]. Available: https://cloud.google.com/functions
[49]
“Azure Functions documentation.” Microsoft. Accessed: Mar. 29, 2023. [Online]. Available: https://docs.microsoft.com/en-us/azure/azure-functions/
[50]
A. Das, S. Imai, S. Patterson, and M. P. Wittie, “Performance optimization for edge-cloud serverless platforms via dynamic task placement,” in Proc. 20th IEEE/ACM Int. Symp. Cluster, Cloud Internet Comput. (CCGRID), 2020, pp. 41–50.
[51]
Y. Huang, Z. Lin, T. Yao, X. Shang, L. Cui, and J. Z. Huang, “Mobility-aware seamless virtual function migration in deviceless edge computing environments,” in Proc. IEEE 42nd Int. Conf. Distrib. Comput. Syst. (ICDCS), 2022, pp. 447–457.
[52]
I. E. Akkus et al., “SAND: Towards High-Performance serverless computing,” in Proc. USENIX Annu. Tech. Conf. (USENIX ATC), 2018, pp. 923–935.
[53]
“IBM cloud functions.” IBM. [Online]. Available: https://cloud.ibm.com/functions/
[54]
Fission. Accessed: Mar. 29, 2023. [Online]. Available: https://fission.io/
[55]
A. Pérez, S. Risco, D. M. Naranjo, M. Caballer, and G. Moltó, “On-premises serverless computing for event-driven data processing applications,” in Proc. IEEE 12th Int. Conf. Cloud Comput. (CLOUD), 2019, pp. 414–421.
[56]
D. Li et al., “SoDa: A serverless-oriented deadline-aware workflow scheduling engine for IoT applications in edge clouds,” Wireless Commun. Mobile Comput., vol. 2022, Oct. 2022, Art. no. 7862911.
[57]
A. K. Chopra et al., “Deserv: Decentralized serverless computing,” in Proc. IEEE Int. Conf. Web Services (ICWS), 2021, pp. 51–60.
[58]
A. Agache et al., “Fire-cracker: Lightweight virtualization for serverless applications,” in Proc. 17th USENIX Symp. Networked Syst. Des. Implementation (NSDI), 2020, pp. 419–434.
[59]
C. de Alfonso, M. Caballer, A. Calatrava, G. Moltó, and I. Blanquer, “Multi-elastic datacenters: Auto-scaled virtual clusters on energy-aware physical infrastructures,” J. Grid Comput., vol. 17, no. 1, pp. 191–204, Mar. 2019.
[60]
“How workers works.” Cloudflare. Accessed: Mar. 29, 2023. [Online]. Available: https://developers.cloudflare.com/workers/learning/how-workers-works/
[61]
P. K. Gadepalli, S. McBride, G. Peach, L. Cherkasova, and G. Parmer, “Sledge: A serverless-first, light-weight wasm runtime for the edge,” in Proc. 21st Int. Middleware Conf., Dec. 2020, pp. 265–279.
[62]
E. Oakes et al., “SOCK: Rapid task provisioning with serverless-optimized containers,” in Proc. USENIX Annu. Tech. Conf. (USENIX ATC), 2018, pp. 57–70.
[63]
P. Raith and S. Dustdar, “Edge intelligence as a service,” in Proc. IEEE Int. Conf. Services Comput. (SCC), 2021, pp. 252–262.
[64]
T. Pusztai et al., “SLO script: A novel language for implementing complex cloud-native elasticity-driven SLOs,” in Proc. IEEE Int. Conf. Web Services (ICWS), 2021, pp. 21–31.
[65]
T. Pusztai et al., “A novel middleware for efficiently implementing complex cloud-native SLOs,” in Proc. IEEE 14th Int. Conf. Cloud Comput. (CLOUD), 2021, pp. 410–420.
[66]
Z. Li et al., “Help rather than recycle: Alleviating cold startup in serverless computing through Inter-Function container sharing,” in Proc. USENIX Annu. Tech. Conf. (USENIX ATC), 2022, pp. 69–84.
[67]
T. Goethals, M. Sebrechts, M. Al-Naday, B. Volckaert, and F. De Turck, “A functional and performance benchmark of lightweight virtualization platforms for edge computing,” in Proc. IEEE Int. Conf. Edge Comput. Commun. (EDGE), 2022, pp. 60–68.
[68]
G. A. S. Cassel, V. F. Rodrigues, R. da Rosa Righi, M. R. Bez, A. C. Nepomuceno, and C. A. da Costa, “Serverless computing for internet of things: A systematic literature review,” Future Gener. Comput. Syst., vol. 128, pp. 299–316, Mar. 2022.
[69]
V. Kjorveziroski, S. Filiposka, and V. Trajkovic, “IoT serverless computing at the edge: Open issues and research direction,” Computers, vol. 10, no. 10, 2021, Art. no. 130.
[70]
N. E. Ioini, D. Hästbacka, C. Pahl, and D. Taibi, “Platforms for serverless at the edge: A review,” in Proc. Eur. Conf. Service-Oriented Cloud Comput., Cham, Switzerland: Springer-Verlag, 2020, pp. 29–40.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image IEEE Internet Computing
IEEE Internet Computing  Volume 27, Issue 3
May-June 2023
59 pages

Publisher

IEEE Educational Activities Department

United States

Publication History

Published: 01 May 2023

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)0
  • Downloads (Last 6 weeks)0
Reflects downloads up to 13 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2025)A survey on various security protocols of edge computingThe Journal of Supercomputing10.1007/s11227-024-06678-681:1Online publication date: 1-Jan-2025
  • (2024)Komet: A Serverless Platform for Low-Earth Orbit Edge ServicesProceedings of the 2024 ACM Symposium on Cloud Computing10.1145/3698038.3698517(866-882)Online publication date: 20-Nov-2024
  • (2024)Snapipeline: Accelerating Snapshot Startup for FaaS ContainersProceedings of the 2024 ACM Symposium on Cloud Computing10.1145/3698038.3698513(144-159)Online publication date: 20-Nov-2024
  • (2024)Towards Energy-Aware Execution and Offloading of Serverless FunctionsProceedings of the 4th Workshop on Flexible Resource and Application Management on the Edge10.1145/3659994.3660313(23-30)Online publication date: 3-Jun-2024
  • (2024)Smart Nutrition Monitoring System Using Serverless Edge ComputingIEEE Transactions on Consumer Electronics10.1109/TCE.2024.341155270:3(6363-6375)Online publication date: 1-Aug-2024
  • (2024)Intent-driven orchestration of serverless applications in the computing continuumFuture Generation Computer Systems10.1016/j.future.2023.12.032154:C(72-86)Online publication date: 1-May-2024
  • (2024)Self-Provisioning Infrastructures for the Next Generation Serverless ComputingSN Computer Science10.1007/s42979-024-03022-w5:6Online publication date: 26-Jun-2024
  • (2024)Edge-computing-assisted intelligent processing of AI-generated image contentJournal of Real-Time Image Processing10.1007/s11554-023-01400-w21:2Online publication date: 25-Feb-2024
  • (2024)POSEIDON: Efficient Function Placement at the Edge Using Deep Reinforcement LearningService-Oriented Computing10.1007/978-981-96-0805-8_2(21-37)Online publication date: 4-Dec-2024
  • (2023)NEPTUNE: A Comprehensive Framework for Managing Serverless Functions at the EdgeACM Transactions on Autonomous and Adaptive Systems10.1145/363475019:1(1-32)Online publication date: 4-Dec-2023
  • Show More Cited By

View Options

View options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media