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The recent trend of edge computing extends cloud computing and the Internet of Things (IoT) to the edge of the network. Similar to most systems, an intrusion-detection system (IDS) is commonly used to mitigate cybersecurity threats in edge computing. Due to the limitations in edge nodes (e.g., in terms of computational and storage capabilities), efficient and fair resource allocation within an IDS is challenging. This article studies IDS architecture and resource allocation in edge computing. Specifically, the proposed system is designed to facilitate multiple resources sharing and heterogeneous resource-demanding allocation. A general edge computing IDS architecture is presented, and we use this as the basis for our model for allocating resources. Then, a single-layer dominant and max-min fair (SDMMF) allocation is used, which has been theoretically proven to satisfy all hierarchical resource allocation properties, and a multilayer resource allocation scheme in our system, the multilayer dominant and max-min fair (MDMMF) allocation is used to cope with the multiple resources fair allocation in multiple layers.
Lin et al. (Mon,) studied this question.