Resource Management for Secure Computation Offloading in Softwarized Cyber-Physical Systems
Resource Management for Secure Computation Offloading in Softwarized Cyber-Physical Systems
复制标题
软件化网络物理系统中安全计算卸载的资源管理
DOI：
10.1109/jiot.2021.3057594
复制
发表时间：
2021-06-01
影响因子：
10.6
通讯作者：
Yu, F. Richard
中科院分区：
文献类型：
--
作者：
Wang, Dan;Zhao, Ning;Yu, F. Richard
物联网 (IoT) 的发展越来越强调通过网络物理系统 (CPS) 的云/边缘计算 (EC) 来扩展其计算和存储能力。特别是，在软件定义的CPS（SD-CPS）中，不同的软件定义网络（SDN）控制器共享信息并协作做出全局决策。为了进一步增强信息共享过程中的系统安全性，我们将区块链技术引入SD-CPS。然而，由于许多与安全相关的决策对延迟很敏感，因此在区块链支持的 SD-CPS 中最小化系统延迟至关重要。本文提出了一种基于区块链的分布式SD-CPS框架，通过在云计算和EC相结合的混合网络范式中卸载数据来实现共识和分布式资源管理。此外，为了在保证数据安全的同时自适应地实施卸载和控制策略，我们设计了一种资源管理方案来减少系统延迟并提供合作的灵活性。为了促进智能，我们将联合通信、计算和共识问题制定为马尔可夫决策过程，并使用深度强化学习来平衡资源分配、减少延迟并保证数据安全。与其他方案相比，仿真结果验证了该方案的有效性，在自适应决策和降低系统时延方面表现更好。
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.