Dependability in Edge Computing
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Abstract (arXiv)
Edge computing is the practice of placing computing resources at the edges of the Internet in close proximity to devices and information sources. This, much like a cache on a CPU, increases bandwidth and reduces latency for applications but at a potential cost of dependability and capacity. This is because these edge devices are often not as well maintained, dependable, powerful, or robust as centralized server-class cloud resources. This article explores dependability and deployment challenges in the field of edge computing, what aspects are solvable with today's technology, and what aspects call for new solutions. The first issue addressed is failures, both hard (crash, hang, etc.) and soft (performance-related), and real-time constraint violation. In this domain, edge computing bolsters real-time system capacity through reduced end-to-end latency. However, much like cache misses, overloaded or malfunctioning edge computers can drive latency beyond tolerable limits. Second, decentralized management and device tampering can lead to chain of trust and security or privacy violations. Authentication, access control, and distributed intrusion detection techniques have to be extended from current cloud deployments and need to be customized for the edge ecosystem. The third issue deals with handling multi-tenancy in the typically resource-constrained edge devices and the need for standardization to allow for interoperability across vendor products. We explore the key challenges in each of these three broad issues as they relate to dependability of edge computing and then hypothesize about promising avenues of work in this area.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Oct 2017.
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Citing papers per year: 2022: 3; 2023: 1.
4 papers.
- 2022DRAGON: Decentralized Fault Tolerance in Edge Federationscited by 2
- 2022DeepFT: Fault-Tolerant Edge Computing using a Self-Supervised Deep Surrogate Modelcited by 2
- 2023Edge AI for Internet of Energy: Challenges and Perspectivescited by 1
- 2022ACE: Towards Application-Centric Edge-Cloud Collaborative Intelligencecited by 0
- 2023Edge AI for Internet of Energy: Challenges and Perspectives28 Nov 2023
- 2022DeepFT: Fault-Tolerant Edge Computing using a Self-Supervised Deep Surrogate Model2 Dec 2022
- 2022DRAGON: Decentralized Fault Tolerance in Edge Federations16 Aug 2022
- 2022ACE: Towards Application-Centric Edge-Cloud Collaborative Intelligence24 Mar 2022