Internet of Things for Smart Manufacturing System: Trust Issues in Resource Allocation

IEEE Internet of Things Journal(2018)

引用 70|浏览18
暂无评分
摘要
In industrial Internet of Things (IIoT) applications for smart manufacturing system, efficient allocation of the carrier and computing resources is crucial. However, existing resource assignment schemes in smart manufacturing system cannot provide timely provision of resources to the inherently dynamic and bursty user demands. To reflect real-time supply and demand for smart manufacturing resources, several research results on auction-style resource assignments have been introduced; however, security, privacy, and trust computing related issues are not actively discussed in the results. The resources should be assigned to devices according to the system policy, which depends on the information provided by IIoT devices. If there are any resource demanding devices, they can report manipulated malicious information for their own interest to obtain more resources. That is, the smart manufacturing system may be vulnerable due to selfish smart manufacturing devices’ behaviors. This reduces the efficiency of the entire system and moreover ceases the plant-wide process. While many research contributions related to the trust computing aim at detecting malicious nodes, this paper presents a novel view of trust computing by showing why devices inside the smart manufacturing system have to act honestly. In this paper, a Vickrey–Clarke–Groves auction-based hierarchical trust computing algorithm is proposed for: 1) computing carrier resources required for wireless communication between IIoT devices and gateways and 2) distributing CPU resources for processing data at central processing controller. Last, simulation results demonstrate that the utilities of each participant are maximized when the IIoT devices and gateways are trustful.
更多
查看译文
关键词
Logic gates,Smart manufacturing,Task analysis,Wireless communication,Cloud computing,Internet of Things,Wireless sensor networks,Industrial control
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要