Adaptive Fault-Tolerant Strategy for Latency-Aware IoT Application Executing in Edge Computing Environment
Abstract
Edge computing has recently evolved that offers to execute jobs efficiently by pushing cloud capabilities to edge of the network, this improves the quality of services to latency-oriented Internet of Things (IoT) applications when compared with cloud computing. By using current smart devices as edge nodes, edge computing can provide elastic resources that allow distributed data processing in a decentralized way. Still these smart devices are resource constrained in nature and tends to face a high failure rate than traditional distributed systems, the implementation of a fault-tolerant system that ensures the reliability and application availability becomes a key requirement. In this article, we propose a fault-tolerance methodology based on checkpointing and replication for the edge computing. Our proposed system uses a smart checkpointing for the IoT application tasks executing in a distributed edge network, and by replicating the checkpoint files on alternative edge nodes in the vicinity allowed to increase the system reliability. The experimental results show that our approach is effective in terms of reliability and availability of tasks executing in the edge network along with meeting deadlines of an IoT application.
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Edge nodes are vulnerable to faults arising from power instability, network disturbances, and adverse environmental conditions.
“Edge nodes—frequently implemented on commodity single-board computers—are vulnerable to faults arising from power instability, network disturbances, and adverse environmental conditions [7,8].”
From Digital Twins at the Edge: A High-Availability Framework for Resilient Data Processing in IoT Sensor Networks (2026) · cites this paper as [7]
ACR [7], DTFR [19], and PureEdge [20] rely primarily on simulation-based validation.
“ACR [7], DTFR [19], and PureEdge [20], rely primarily on simulation-based validation”
From Digital Twins at the Edge: A High-Availability Framework for Resilient Data Processing in IoT Sensor Networks (2026) · cites this paper as [7]
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- Authors
- Mudassar, M., Zhai, Y., & Lejian, L.
- Affiliations
- Beijing Institute of Technology (CN)
- Beijing Institute of Technology, School of Computer Science, Beijing, China
- Venue
- IEEE Internet of Things Journal
- Published
- 2022-08-01
- Volume
- 9
- Issue
- 15
- Pages
- 13250-13262
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W4205373754
- Cited by
- 59
- References
- 32
- Citations by year
- 2026: 9 · 2025: 23 · 2024: 16 · 2023: 9 · 2022: 2
- FWCI
- 5.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- Funders
- Equipment Pre-Research Field Foundation (61400010104)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed systems and fault tolerance
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Keywords
- fault tolerance, edge computing, IoT applications, checkpointing, data replication, task reliability, availability, deadline constraints, resource-constrained devices
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