Privacy-Preserving Deployment Mechanism for Service Function Chains Across Multiple Domains

计算机科学 软件部署 计算机网络 供应 虚拟网络 服务器 分布式计算 网络拓扑 操作系统
作者
Jun Cai,Yang Shi,Zhongwei Huang,Wenlong Dai,F. Richard Yu
出处
期刊:IEEE Transactions on Network and Service Management [Institute of Electrical and Electronics Engineers]
卷期号:: 1-1
标识
DOI:10.1109/tnsm.2023.3311587
摘要

Network function virtualization (NFV) has attracted attention because of its flexible configuration and management of network functions. Based on NFV, the service function chain (SFC) defines a group of virtual network functions (VNFs) connected sequentially, enabling flexible customization and provisioning of network services. In the large-scale and heterogeneous Internet of Things (IoT) environment, e.g., industrial IoT, servers provided by a single infrastructure provider (InP) cannot support the deployment of all VNFs, and SFCs must be deployed across multiple domains. However, SFCs deployed across multiple domains will inevitably bring privacy leakage and resource coordination difficulties, thereby reducing the efficiency of network services. To address these issues, this paper proposes a privacy-preserving deployment mechanism (PPDM) for SFCs that achieves near-optimal SFC deployment across multiple domains while protecting resource and topology privacy. PPDM first performs virtual resource prediction and forms the service intention response matrix (SIRM) based on SFC requests (SFCRs). Second, the multi-domain controller (MDC) discovers a near-optimal SFCs deployment strategy by deep Q-network (DQN) using SIRM as input to protect domains’ privacy. Finally, the learned strategies are distributed to intra-domain controllers (IDCs) to implement specific services. Simulation results demonstrate that the proposed method outperforms privacy-preserving and non-privacy-preserving methods.
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