Resource Management for Secure Computation Offloading in Softwarized Cyber-Physical Systems

【Author】 Wang, Dan; Zhao, Ning; Song, Bin; Lin, Peng; Yu, F. Richard

【Source】IEEE INTERNET OF THINGS JOURNAL

【影响因子】10.238

【Abstract】The evolution of the Internet of Things (IoT) makes an increased emphasis on extending their computing and storage capabilities by relying particularly on the cloud/edge computing (EC) for cyber-physical systems (CPSs). Especially, in software-defined CPS (SD-CPS), different software-defined networking (SDN) controllers share information and cooperate to make global decisions. To further enhance system security during the information sharing process, we introduce blockchain technology into SD-CPS. However, because many security-related decisions are sensitive to latency, it is vital to minimize the system latency in blockchain-empowered SD-CPS. In this article, a blockchain-empowered distributed SD-CPS framework is proposed to realize consensus and distributed resource management by offloading data in a hybrid network paradigm that combines cloud computing and EC. Moreover, to adaptively implement offloading and control strategies while guaranteeing data security, we design a resource management scheme for reducing system latency and provide the flexibility of cooperation. To foster intelligence, we formulate the joint communication, computation, and consensus problems as a Markov decision process and use deep reinforcement learning to balance resource allocation, reduce latency, and guarantee data security. Compared with other schemes, simulation results verify the effectiveness of the proposed scheme, which performs better on self-adaptation decision making and system delay reduction.

【Keywords】Task analysis; Cloud computing; Resource management; Internet of Things; Blockchain; Handheld computers; Servers; Blockchain; cloud; edge computing (EC); reinforcement learning (RL); software-defined cyber– physical systems (SD-CPSs)

【发表时间】2021 44713

【收录时间】2022-01-02

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