在雾网络中调度实时安全感知任务

Ashutosh Kumar Singh, Nitin Auluck, Omer F. Rana, S. Nepal
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引用次数: 1

摘要

雾计算扩展了云服务的功能,以支持对延迟敏感的应用程序。在数据生成/驱动源附近添加雾计算节点可以支持具有严格截止日期限制的数据分析任务。我们引入了一种实时的、安全感知的调度算法,该算法可以在雾环境中执行[1,2]。我们考虑的应用程序包括:(i)交互式应用程序,其计算强度较低,但需要更快的响应时间;(ii)计算密集的批处理应用程序,可以容忍一些执行延迟。从安全角度来看,应用程序分为三类:公共、私有和半私有,它们必须托管在可信、半可信和不可信的资源上。我们提出了用于雾计算的分布式编排器的体系结构和实现,能够将任务需求(性能和安全性)和资源属性结合起来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scheduling Real Tim Security Aware Tasks in Fog Networks
Fog computing extends the capability of cloud services to support latency sensitive applications. Adding fog computing nodes in proximity to a data generation/ actuation source can support data analysis tasks that have stringent deadline constraints. We introduce a real time, security-aware scheduling algorithm that can execute over a fog environment [1 , 2] . The applications we consider comprise of: (i) interactive applications which are less compute intensive, but require faster response time; (ii) computationally intensive batch applications which can tolerate some delay in execution. From a security perspective, applications are divided into three categories: public, private and semi-private which must be hosted over trusted, semi-trusted and untrusted resources. We propose the architecture and implementation of a distributed orchestrator for fog computing, able to combine task requirements (both performance and security) and resource properties.
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