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Edge and IoT

Serverless computing has generated enthusiasm [1] in the areas of edge computing [2] and the Internet of Things (IoT) [3]. IoT envisions embedded computing and communication in sensors, actuators, and everyday electronic items. IoT devices are often resource-constrained, so they may benefit from offloading computation over the network. Edge computing makes it possible to do this while maintaining low latency: It augments the cloud resources in centralized data centers with compute, storage, or other resources placed at the “edge” of the network, i.e., near devices. Combining edge computing and IoT presents challenges since devices may move and because the resources available at a particular edge location can become oversubscribed. These are the sorts of challenges that serverless computing is equipped for.

This is an active area of research that includes numerous works. Hall et al. [4] suggest an execution model for FaaS at the edge. Gand et al. [5] describe a containerized management solution for deploying serverless code. Pinto et al. [6] propose dynamically moving functions between an IoT device and the edge. Apollo [7] provides a system for runtime function composition and flexible placement, whereas Costless [8] describes an approach to optimization that includes function fusion. LaSS [9] focuses on meeting the needs of latency-sensitive edge applications. Aske and Zhao describe work on supporting multi-provider serverless computing at the edge [10]. In addition to processing data generated at the edge, serverless models can be applied to disseminating information sourced from centralized data centers, as Facebook does with Bladerunner [11].

  • [1]Mohammad S. Aslanpour, Adel N. Toosi, Claudio Cicconetti, Bahman Javadi, Peter Sbarski, Davide Taibi, Marcos Assuncao, Sukhpal Singh Gill, Raj Gaire, and Schahram Dustdar. 2021. Serverless Edge Computing: Vision and Challenges. In 2021 Australasian Computer Science Week Multiconference, 1–10.
  • [2]Weisong Shi, Jie Cao, Quan Zhang, Youhuizi Li, and Lanyu Xu. 2016. Edge Computing: Vision and Challenges. IEEE Internet of Things Journal 3, 5 (2016), 637–646.
  • [3]Luigi Atzori, Antonio Iera, and Giacomo Morabito. 2010. The Internet of Things: A Survey. Computer Networks 54, 15 (2010), 2787–2805.
  • [4]Adam Hall and Umakishore Ramachandran. 2019. An Execution Model for Serverless Functions at the Edge. In Proceedings of the International Conference on Internet of Things Design and Implementation, 225–236.
  • [5]Fabian Gand, Ilenia Fronza, Nabil El Ioini, Hamid R. Barzegar, and Claus Pahl. 2020. Serverless Container Cluster Management for Lightweight Edge Clouds. In CLOSER, 302–311.
  • [6]Duarte Pinto, João Pedro Dias, and Hugo Sereno Ferreira. 2018. Dynamic Allocation of Serverless Functions in IoT Environments. In 2018 IEEE 16th international conference on embedded and ubiquitous computing (EUC), IEEE, 1–8.
  • [7]Fedor Smirnov, Behnaz Pourmohseni, and Thomas Fahringer. 2020. Apollo: Modular and Distributed Runtime System for Serverless Function Compositions on Cloud, Edge, and Iot Resources. In Proceedings of the 1st Workshop on High Performance Serverless Computing, 5–8.
  • [8]Tarek Elgamal. 2018. Costless: Optimizing Cost of Serverless Computing Through Function Fusion and Placement. In 2018 IEEE/ACM Symposium on Edge Computing (SEC), IEEE, 300–312.
  • [9]Bin Wang, Ahmed Ali-Eldin, and Prashant Shenoy. 2020. LaSS: Running Latency Sensitive Serverless Computations at the Edge. In Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing, 239–251.
  • [10]Austin Aske and Xinghui Zhao. 2018. Supporting Multi-Provider Serverless Computing on the Edge. In Proceedings of the 47th International Conference on Parallel Processing Companion, 1–6.
  • [11]Jeff Barber, Ximing Yu, Laney Kuenzel Zamore, Jerry Lin, Vahid Jazayeri, Shie Erlich, Tony Savor, and Michael Stumm. 2021. Bladerunner: Stream Processing at Scale for a Live View of Backend Data Mutations at the Edge. In Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles, 708–723.