基于深度学习架构的多任务并行移动边缘计算策略优化

IF 0.9 4区计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Design Automation for Embedded Systems Pub Date : 2019-07-12 DOI:10.1007/s10617-019-09222-5

Zongkai Liu, Xiaoqiang Yang, J. Shen

引用次数: 6

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Optimization of multitask parallel mobile edge computing strategy based on deep learning architecture

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来源期刊

Design Automation for Embedded Systems 工程技术-计算机：软件工程

CiteScore

2.60

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Embedded (electronic) systems have become the electronic engines of modern consumer and industrial devices, from automobiles to satellites, from washing machines to high-definition TVs, and from cellular phones to complete base stations. These embedded systems encompass a variety of hardware and software components which implement a wide range of functions including digital, analog and RF parts. Although embedded systems have been designed for decades, the systematic design of such systems with well defined methodologies, automation tools and technologies has gained attention primarily in the last decade. Advances in silicon technology and increasingly demanding applications have significantly expanded the scope and complexity of embedded systems. These systems are only now becoming possible due to advances in methodologies, tools, architectures and design techniques. Design Automation for Embedded Systems is a multidisciplinary journal which addresses the systematic design of embedded systems, focusing primarily on tools, methodologies and architectures for embedded systems, including HW/SW co-design, simulation and modeling approaches, synthesis techniques, architectures and design exploration, among others. Design Automation for Embedded Systems offers a forum for scientist and engineers to report on their latest works on algorithms, tools, architectures, case studies and real design examples related to embedded systems hardware and software. Design Automation for Embedded Systems is an innovative journal which distinguishes itself by welcoming high-quality papers on the methodology, tools, architectures and design of electronic embedded systems, leading to a true multidisciplinary system design journal.