Exploring Trust Management in Fog Computing: A Comprehensive Review and Future Challenges in Task Offloading

With the proliferation of data-driven services and latency-sensitive applications, fog computing has emerged as a pivotal extension of cloud infrastructure, enabling data processing and resource allocation at the network edge. However, the trustworthiness of task offloading in such decentralized and heterogeneous environments remains insufficiently explored, posing significant concerns related to system reliability, security, and performance. This review aims to address this gap by providing a comprehensive and systematic analysis of current research on trust-based task offloading in fog computing. The study investigates various trust evaluation mechanisms, categorizing them into three major paradigms: Direct Trust-based, Recommended Trust-based, and Comprehensive Trust. Through this classification, the study identifies and examines key trust-related metrics that influence offloading decisions, including task execution accuracy, trust evaluation accuracy, and evaluation latency. A critical assessment of the strengths and limitations of existing approaches reveals ongoing challenges such as dynamic trust management, scalability in large-scale networks, interoperability among diverse nodes, and resilience against malicious behaviours. Based on these insights, the study highlights pressing research opportunities and recommends the development of lightweight, adaptive, and context-aware trust frameworks capable of supporting real-time decision-making in dynamic fog environments. By synthesizing fragmented research and offering a forward-looking perspective, this review contributes a foundational reference for scholars and practitioners seeking to enhance the reliability and security of task offloading in fog computing, thereby supporting the evolution of more robust and efficient edge-based computing infrastructures.

@article{Feng2025,
  title     = {Exploring Trust Management in Fog Computing: A Comprehensive Review and Future Challenges in Task Offloading},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {8},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Liu Feng and Suhaidi Hassan and Mohammed Alsamman},
  doi       = {10.14569/IJACSA.2025.0160815},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160815}
}