Journal ArticleDOI
An edge computing-enabled computation offloading method with privacy preservation for internet of connected vehicles
TLDR
A privacy preservation method, named ECO, with privacy preservation for IoV is proposed in this paper and NSGA-II (non-dominated sorting genetic algorithm II) is adopted to realize multi-objective optimization to reduce the execution time and energy consumption of ECDs and prevent privacy conflicts of the computing tasks.About:
This article is published in Future Generation Computer Systems.The article was published on 2019-07-01. It has received 194 citations till now. The article focuses on the topics: Computation offloading & Edge computing.read more
Citations
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Journal ArticleDOI
Deep Learning Models for Real-time Human Activity Recognition with Smartphones
TL;DR: A smartphone inertial accelerometer-based architecture for HAR is designed and a real-time human activity classification method based on a convolutional neural network (CNN) is proposed, which uses a CNN for local feature extraction on the UCI and Pamap2 datasets.
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An Edge Traffic Flow Detection Scheme Based on Deep Learning in an Intelligent Transportation System
TL;DR: A real-time vehicle tracking counter for vehicles that combines the vehicle detection and vehicle tracking algorithms to realize the detection of traffic flow is proposed.
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Cognitive computing and wireless communications on the edge for healthcare service robots
TL;DR: This paper reviews several state-of-the-art technologies, such as the human–robot interface, environment and user status perceiving, navigation, robust communication and artificial intelligence, of a mobile healthcare robot and discusses in details the customized demands over offloading the computation and communication tasks.
Journal ArticleDOI
5G support for Industrial IoT Applications - Challenges, Solutions, and Research gaps
Pal Varga,Jozsef Peto,Attila Franko,David Balla,David Haja,Ferenc Nandor Janky,Gabor Soos,Daniel Ficzere,Markosz Maliosz,Laszlo Toka +9 more
TL;DR: This paper identifies current research challenges and solutions in relation to 5G-enabled Industrial IoT, based on the initial requirements and promises of both domains, and provides meaningful comparisons for each of these areas to draw conclusions on current research gaps.
Journal ArticleDOI
Link prediction in paper citation network to construct paper correlation graph
TL;DR: A link prediction approach that combines time, keywords, and authors’ information and optimizes the existing paper citation network is proposed and a number of experiments demonstrate the feasibility and achieve good performance.
References
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Journal ArticleDOI
Edge Computing: Vision and Challenges
TL;DR: The definition of edge computing is introduced, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge Computing.
Journal ArticleDOI
Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
TL;DR: In this article, a game theoretic approach for computation offloading in a distributed manner was adopted to solve the multi-user offloading problem in a multi-channel wireless interference environment.
Journal ArticleDOI
Mobile Edge Computing: A Survey on Architecture and Computation Offloading
Pavel Mach,Zdenek Becvar +1 more
TL;DR: In this paper, the authors present a survey of the research on computation offloading in mobile edge computing (MEC), focusing on user-oriented use cases and reference scenarios where the MEC is applicable.
Journal ArticleDOI
Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices
TL;DR: In this paper, a low-complexity online algorithm is proposed, namely, the Lyapunov optimization-based dynamic computation offloading algorithm, which jointly decides the offloading decision, the CPU-cycle frequencies for mobile execution, and the transmit power for computing offloading.
Posted Content
Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
TL;DR: This paper designs a distributed computation offloading algorithm that can achieve a Nash equilibrium, derive the upper bound of the convergence time, and quantify its efficiency ratio over the centralized optimal solutions in terms of two important performance metrics.