SCYLLA: QoE-aware continuous mobile vision with FPGA-based dynamic deep neural network reconfiguration

S Jiang, Z Ma, X Zeng, C Xu, M Zhang… - … -IEEE Conference on …, 2020 - ieeexplore.ieee.org
Continuous mobile vision is becoming increasingly important as it finds compelling
applications which substantially improve our everyday life. However, meeting the …

Scheduling massive camera streams to optimize large-scale live video analytics

C Rong, JH Wang, J Liu, J Wang, F Li… - … /ACM Transactions on …, 2021 - ieeexplore.ieee.org
In smart cities, more and more government departments will make use of live analytics of
videos from surveillance cameras in their tasks, such as vehicle traffic monitoring and …

Effect: Energy-efficient fog computing framework for real-time video processing

X Zhang, A Pal, S Debroy - 2021 IEEE/ACM 21st International …, 2021 - ieeexplore.ieee.org
Energy efficient task offloading within a fog computing environment comprising of end-
devices and edge servers remains a challenging problem to solve, especially for real-time …

Microservice-based edge device architecture for video analytics

SY Jang, B Kostadinov, D Lee - 2021 IEEE/ACM Symposium on Edge …, 2021 - computer.org
With today's ubiquitous deployment of video cameras and other edge devices, progress in
edge computing is happening at an incredible speed. Yet, one aspect of real-time video …

User allocation in mobile edge computing: A deep reinforcement learning approach

SP Panda, A Banerjee… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
In recent times, the need for low latency has made it necessary to deploy application
services physically and logically close to the users rather than using the cloud for hosting …

A random walk based load balancing algorithm for fog computing

R Beraldi, C Canali, R Lancellotti… - 2020 Fifth international …, 2020 - ieeexplore.ieee.org
The growth of large scale sensing applications (as in the case of smart cities applications) is
a main driver of the fog computing paradigm. However, as the load for such fog …

WaterEdge: Edge–Cloud Collaborative Intelligent Coagulation System for Group-Level Water Treatment Plants

Y Wang, S Yang, X Ren, S Guo, C Zhao… - IEEE Systems …, 2023 - ieeexplore.ieee.org
Providing an intelligent coagulation solution for group-level water treatment plants (WTPs) is
of great significance to improve coagulation efficiency. Existing solutions are devoted to …

Power of random choices made efficient for fog computing

R Beraldi, GP Mattia - IEEE Transactions on Cloud Computing, 2020 - ieeexplore.ieee.org
In this article, we consider a load balancing protocol based on the power of random choices
that is adapted to a fog deploy in which several independent fog nodes equipped with a set …

Age-aware scheduling for asynchronous arriving jobs in edge applications

J Zhong, W Zhang, RD Yates… - IEEE INFOCOM 2019 …, 2019 - ieeexplore.ieee.org
Age of information has been proposed recently to measure information freshness, especially
for a class of real-time video applications. These applications often demand timely updates …

Smotec: An edge computing testbed for adaptive smart mobility experimentation

Z Nezami, E Pournaras, A Borzouie… - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Smart mobility becomes paramount for meeting net-zero targets. However, autonomous, self-
driving and electric vehicles require more than ever before an efficient, resilient and …