Review of WebAssembly Application Research for Edge Serverless Computing

doi:10.3778/j.issn.1002-8331.2210-0308

Abstract

Abstract: WebAssembly（Wasm） is a new binary format that is portable, small, fast to load and compatible with the Web. It has the characteristics of high efficiency, security, and openness. The basic concept of edge computing is to run computing tasks on computing resources close to the data source. However, the performance and resources of devices deployed on the edge are usually very limited. In this resource-constrained environment, how to provide low-latency and secure services is an important research direction of edge computing. Serverless is a new way to host applications on infrastructure. At present, it is mainly based on container technology to realize program hosting. Serverless computing is currently the most suitable architecture for edge computing due to its lightweight, function as a service（FaaS）, automatic scaling and so on, but it always has problems such as cold start and large memory consumption. Wasm can replace the traditional container and provide an updated, faster, less resource consuming and secure isolation implementation for edge serverless computing. In this paper, the characteristics of edge serverless computing and its application scenarios, as well as the development trend of Wasm are introduced at first. The current research on Wasm-based edge serverless computing is analyzed and the development direction of Wasm runtime alternative containers as the carrier of edge serverless computing is illustrated. Moreover, the problems of edge Wasm serverless computing platform are discussed and the future optimization directions based on deep reinforcement learning and other artificial intelligence algorithms are summarized.

Key words: WebAssembly, edge computing, serverless computing, deep reinforcement learning, runtime

摘要： WebAssembly（简称Wasm）是一个可移植、体积小、加载迅速且兼容Web的全新二进制格式，具有高效、安全、开放等特点。边缘计算的基本理念是将计算任务在接近数据源的计算资源上运行，而部署在边缘的设备性能和资源通常十分有限，在这种资源受限的环境下如何提供低延迟且安全的服务是边缘计算的重要研究方向。无服务器技术（Serverless）是一种基础设施上托管应用程序的新方式，目前主要基于容器技术实现程序的托管，因为其轻量，函数即服务（FaaS）、自动伸缩等特点，无服务器计算是目前最适合边缘计算的架构，但一直存在冷启动和内存占用大等问题。Wasm可以替代传统容器方式，为边缘无服务器计算提供一种更新、更快、资源占用更小且安全隔离的实现方式。介绍边缘无服务器计算的特性及其应用场景、Wasm的应用现状和发展趋势，分析了基于Wasm的边缘无服务器计算中关键问题的研究现状，阐述了Wasm运行时替代容器作为边缘无服务器计算载体的发展方向，探讨了边缘Wasm无服务器计算平台存在的问题以及未来基于深度强化学习等人工智能算法的优化方向。

关键词: WebAssembly, 边缘计算, 无服务器计算, 深度强化学习, 运行时

WANG Xin, ZHAO Kai, QIN Bin. Review of WebAssembly Application Research for Edge Serverless Computing[J]. Computer Engineering and Applications, 2023, 59(11): 28-36.

王欣, 赵凯, 秦斌. 面向边缘无服务器计算的WebAssembly应用研究综述[J]. 计算机工程与应用, 2023, 59(11): 28-36.

References

[1] SHI W，CAO J，ZHANG Q，et al.Edge computing：vision and challenges[J].IEEE Internet of Things Journal，2016，3（5）：637-646.
[2] 施巍松，张星洲，王一帆，等.边缘计算：现状与展望[J].计算机研究与发展，2019，56（1）：69-89.
SHI W S，ZHANG X Z，WANG Y F，et al.Edge computing：state-of-the-art and future directions[J].Journal of Computer Research and Development，2019，56（1）：69-89.
[3] 杨柏蔼，赵山，刘芳.无服务器计算技术研究综述[J].计算机工程与科学，2022，44（4）：611-619.
YANG B A，ZHAO S，LIU F.A survey on serverless computing[J].Computer Engineering & Science，2022，44（4）：611-619.
[4] BALDINI I，CASTRO P，CHANG K，et al.Serverless computing：current trends and open problems[M]//Research advances in cloud computing.Singapore：Springer，2017：1-20.
[5] CAO K，LIU Y，MENG G，et al.An overview on edge computing research[J].IEEE Access，2020，8：85714-85728.
[6] MAMPAGE A，KARUNASEKERA S，BUYYA R.A holistic view on resource management in serverless computing environments：taxonomy and future directions[J].ACM Computing Surveys（CSUR），2022，54（11s）：1-36.
[7] PFANDZELTER T，BERMBACH D.tinyFaaS：a lightweight faas platform for edge environments[C]//2020 IEEE International Conference on Fog Computing（ICFC），2020：17-24.
[8] ASLANPOUR M S，TOOSI A N，CICCONETTI C，et al.Serverless edge computing：vision and challenges[C]//2021 Australasian Computer Science Week Multiconference，2021：1-10.
[9] CASTRO P，ISHAKIAN V，MUTHUSAMY V，et al.The rise of serverless computing[J].Communications of the ACM，2019，62（12）：44-54.
[10] BENEDETTI P，FEMMINELLA M，REALI G，et al.Experimental analysis of the application of serverless computing to IoT platforms[J].Sensors，2021，21（3）：928.
[11] DENG S，ZHAO H，FANG W，et al.Edge intelligence：the confluence of edge computing and artificial intelligence[J].IEEE Internet of Things Journal，2020，7（8）：7457-7469.
[12] RAUSCH T，HUMMER W，MUTHUSAMY V，et al.Towards a serverless platform for edge AI[C]//2nd USENIX Workshop on Hot Topics in Edge Computing（HotEdge 19），2019.
[13] SINGH P，MASUD M，HOSSAIN M S，et al.Privacy-preserving serverless computing using federated learning for smart grids[J].IEEE Transactions on Industrial Informatics，2022，18（11）：7843-7852.
[14] ANANTHANARAYANAN G，BAHL P，BODíK P，et al.Real-time video analytics：the killer App for edge computing[J].Computer，2017，50（10）：58-67.
[15] HAAS A，ROSSBERG A，SCHUFF D L，et al.Bringing the web up to speed with WebAssembly[C]//Proceedings of the 38th ACM SIGPLAN Conference on Programming Language Design and Implementation，2017：185-200.
[16] NARAYAN S，DISSELKOEN C，MOGHIMI D，et al.Swivel：hardening WebAssembly against spectre[C]//30th USENIX Security Symposium（USENIX Security 21），2021：1433-1450.
[17] LI H，OTA K，DONG M.Learning IoT in edge：deep learning for the Internet of Things with edge computing[J].IEEE Network，2018，32（1）：96-101.
[18] YAN Y，TU T，ZHAO L，et al.Understanding the performance of webassembly applications[C]//Proceedings of the 21st ACM Internet Measurement Conference，2021：533-549.
[19] KHOMTCHOUK B B.WebAssembly enables low latency interoperable augmented and virtual reality software[J].arXiv：2110.07128，2021.
[20] WANG Z，WANG P，LOUIS P C，et al.Wearmask：fast in-browser face mask detection with serverless edge computing for Covid-19[J].arXiv：2101.00784，2021.
[21] WANG Z，WANG J D，WANG Z D，et al.Characterization and implication of edge WebAssembly runtimes[C]//2021 IEEE 23rd Int Conf on High Performance Computing & Communications，2021：71-80.
[22] WALLENTOWITZ S，KERSTING B，DUMITRIU D M.Potential of WebAssembly for embedded systems[C]//2022 11th Mediterranean Conference on Embedded Computing（MECO），2022：1-4.
[23] SPIES B，MOCK M.An evaluation of WebAssembly in non-web environments[C]//2021 XLVII Latin American Computing Conference（CLEI），2021：1-10.
[24] Intel.WebAssembly micro runtime（WAMR）[CP/OL].[2022-11-14].https：//github.com/bytecodealliance/wasm-micro-runtime.
[25] GURDEEP SINGH R，SCHOLLIERS C.WARDuino：a dynamic WebAssembly virtual machine for programming microcontrollers[C]//Proceedings of the 16th ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes，2019：27-36.
[26] SCHEIDL F.WebAssembly：paving the way towards a unified and distributed intra-vehicle computing-and data-acquisition-platform[C]//2020 AEIT International Conference of Electrical and Electronic Technologies for Automotive（AEIT AUTOMOTIVE），2020：1-6.
[27] TRESNESS C.Understanding serverless cold start[EB/OL].[2022?11?14].https：//azure.microsoft.com/en-us/blog/understanding-serverless-cold-start/.
[28] Amazon.AWS documentation[EB/OL].[2022-11-14].https：//docs.aws.amazon.com/lambda/latest/dg/running-lambda-code.html.
[29] LONG J，TAI H Y，HSIEH S T，et al.A lightweight design for serverless function as a service[J].IEEE Software，2020，38（1）：75-80.
[30] BOSSHARD B.On the use of webassembly in a serverless context[C]//Agile Processes in Software Engineering and Extreme Programming-Workshops，2020.
[31] NAPIERALLA J.Considering webassembly containers for edge computing on hardware-constrained IOT devices[Z]. 2020.
[32] MENDKI P.Evaluating webassembly enabled serverless approach for edge computing[C]//2020 IEEE Cloud Summit，2020：161-166.
[33] GACKSTATTER P，FRANGOUDIS P A，DUSTDAR S.Pushing serverless to the edge with WebAssembly runtimes[C]//2022 22nd IEEE International Symposium on Cluster，Cloud and Internet Computing（CCGrid），2022：140-149.
[34] HALL A，RAMACHANDRAN U.An execution model for serverless functions at the edge[C]//Proceedings of the International Conference on Internet of Things Design and Implementation，2019：225-236.
[35] TIWARY M，MISHRA P，JAIN S，et al.Data aware Web-assembly function placement[C]//Companion Proceedings of the Web Conference 2020，2020.
[36] SEBRECHTS M，RAMLOT T，BORNY S，et al.Adapting Kubernetes controllers to the edge：on-demand control planes using Wasm and WASI[J].arXiv：2209.01077，2022.
[37] GADEPALLI P K，MCBRIDE S，PEACH G，et al.Sledge：a serverless-first，light-weight Wasm runtime for the edge[C]//Proceedings of the 21st International Middleware Conference，2020：265-279.
[38] GADEPALLI P K，PEACH G，CHERKASOVA L，et al.Challenges and opportunities for efficient serverless computing at the edge[C]//2019 38th Symposium on Reliable Distributed Systems（SRDS），2019.
[39] MCBRIDE S P.SledgeEDF：deadline-driven serverless for the edge[D].The George Washington University，2021.
[40] LYU X，CHERKASOVA L，AITKEN R，et al.Towards efficient processing of latency-sensitive serverless DAGs at the edge[C]//Proceedings of the 5th International Workshop on Edge Systems，Analytics and Networking，2022：49-54.
[41] RAC S，BRORSSON M.At the edge of a seamless cloud experience[J].arXiv：2111.06157，2021.
[42] NURUL-HOQUE M，HARRAS K A.Nomad：cross-platform computational offloading and migration in femtoclouds using WebAssembly[C]//2021 IEEE International Conference on Cloud Engineering（IC2E），2021：168-178.
[43] JEONG H J，SHIN C H，SHIN K Y，et al.Seamless offloading of web App computations from mobile device to edge clouds via html5 web worker migration[C]//Proceedings of the ACM Symposium on Cloud Computing，2019：38-49.
[44] NIEKE M，ALMSTEDT L，KAPITZA R.Edgedancer：secure mobile WebAssembly services on the edge[C]//Proceedings of the 4th International Workshop on Edge Systems，Analytics and Networking，2021：13-18.
[45] MéNéTREY J，PASIN M，FELBER P，et al.WebAssembly as a common layer for the cloud-edge continuum[C]//Proceedings of the 2nd Workshop on Flexible Resource and Application Management on the Edge，2022：3-8.
[46] POP V A B，NIEMI A，MANEA V，et al.Towards securely migrating webassembly enclaves[C]//Proceedings of the 15th European Workshop on Systems Security，2022：43-49.
[47] GEISLER W.Reliable migration of WebAssembly trusted applications[D].Helsinki：Aalto University，2022.
[48] CABRERA ARTEAGA J，LAPERDRIX P，MONPERRUS M，et al.Multi-variant execution at the edge[J].arXiv：2108.08125，2021.
[49] BANAEI A，SHARIFI M.ETAS：predictive scheduling of functions on worker nodes of Apache OpenWhisk platform[J].The Journal of Supercomputing，2022，78（4）：5358-5393.
[50] SHAHRAD M，FONSECA R，GOIRI í，et al.Serverless in the wild：characterizing and optimizing the serverless workload at a large cloud provider[C]//2020 USENIX Annual Technical Conference（USENIX ATC 20），2020：205-218.
[51] AGARWAL S，RODRIGUEZ M A，BUYYA R.A reinforcement learning approach to reduce serverless function cold start frequency[C]//2021 IEEE/ACM 21st International Symposium on Cluster，Cloud and Internet Computing（CCGrid），2021：797-803.
[52] JEON H，SHIN S，CHO C，et al.Deep reinforcement learning for QoS-aware package caching in serverless edge computing[C]//2021 IEEE Global Communications Conference（GLOBECOM），2021：1-6.
[53] LOWE R，WU Y I，TAMAR A，et al.Multi-agent actor-critic for mixed cooperative-competitive environments[C]//Advances in Neural Information Processing Systems，2017.