Fog based energy efficient ubiquitous systems
Fog based energy efficient ubiquitous systems
复制标题
基于雾的节能泛在系统
DOI：
--
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Tanima Dutta
中科院分区：
文献类型：
--
作者：
Surbhi Saraswat;Hari Prabhat Gupta;Tanima Dutta
日益普及的计算系统产生大量数据，这些数据需要强大的处理能力。必须对数据进行处理，以便在预定义的时间内生成结果，同时使系统的能耗最小化。云具有足够的处理能力来处理数据，但将这些数据转发到云会消耗大量能源。雾环境通过在普适计算系统附近进行处理解决了这个问题。普适计算应用中使用的机器学习技术被分为多个步骤，这些步骤可在不同层执行。我们的工作考虑了一种由边缘层、雾层和云层组成的分层架构。不同层的设备在处理和转发数据时所消耗的功率是不同的。现在面临的挑战是确定在哪个层执行哪些机器学习步骤，以使能耗最小化，并且所遇到的延迟保持在给定阈值内。对不同层的不同设备的能耗进行了数学分析。
Growing ubiquitous computing systems generate large data that require large processing power. The data must be processed such that result is generated within a predefined time and also minimize the energy consumption of the system. The Cloud has sufficient processing power to process the data, but forwarding this data to the Cloud consumes huge energy. Fog environment solves this problem by performing processing near the ubiquitous computing system. Machine learning techniques used in the ubiquitous computing applications are divided into steps which can be performed at different layers. Our work considers a layered architecture comprising of Edge, Fog, and Cloud layers. The power consumed in processing and forwarding the data by devices at different layers is different. The challenge now arises to identify which machine learning steps to be performed at which layer such that energy consumption is minimized and the delay encountered remains within a given threshold. Mathematical analysis is presented for energy consumption by different devices at different layers.