Wu Jun, Su Zhou, Wang Shen, Li Jianhua
School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China.
Sensors (Basel). 2017 Jul 30;17(8):1744. doi: 10.3390/s17081744.
Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on "friend" relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.
雾计算将智能和资源从远程云转移到边缘网络，有可能为从传感数据源到用户的通信提供低延迟。对于从物联网（IoT）到云的对象而言，对象之间建立类似社交的关系是一种新趋势，这有效地将发达的社交性优势带入复杂环境。随着雾服务变得更加复杂，雾用户通过社交网络共享自己的服务、资源和数据将变得更加方便。同时，高效的社会组织能够实现更灵活、安全和协作的网络。上述优势使社交网络成为雾计算系统的一种潜在架构。在本文中，我们设计了一种社交雾计算架构，其中雾的服务基于“朋友”关系来提供。据我们所知，这是首次尝试基于社交模型构建有组织的雾计算系统。同时，社交网络增加了雾计算服务的复杂性和安全风险，给社交雾计算中的安全服务推荐带来困难。为解决这一问题，我们提出了一种新颖的支持群体感知的安全服务供应方法，以在社交雾计算系统中准确推荐安全服务。仿真结果表明了支持群体感知的安全服务推荐方法在社交雾计算系统中的可行性和有效性。
