research-article

Robust Searching-Based Gradient Collaborative Management in Intelligent Transportation System

Authors:

Haibing GuanAuthors Info & Claims

ACM Transactions on Multimedia Computing, Communications and Applications, Volume 20, Issue 2

Article No.: 34, Pages 1 - 23

https://doi.org/10.1145/3549939

Published: 27 September 2023 Publication History

Abstract

With the rapid development of big data and the Internet of Things (IoT), traffic data from an Intelligent Transportation System (ITS) is becoming more and more accessible. To understand and simulate the traffic patterns from the traffic data, Multimedia Cognitive Computing (MCC) is an efficient and practical approach. Distributed Machine Learning (DML) has been the trend to provide sufficient computing resources and efficiency for MCC tasks to handle massive data and complex models. DML can speed up computation with those computing resources but introduces communication overhead. Gradient collaborative management or gradient aggregation in DML for MCC tasks is a critical task. An efficient managing algorithm of the communication schedules for gradient aggregation in ITS can improve the performance of MCC tasks. However, existing communication schedules typically rely on specific physical connection matrices, which have low robustness when a malfunction occurs. In this article, we propose Robust Searching-based Gradient Collaborative Management (RSGCM) in Intelligent Transportation System, a practical ring-based gradient managing algorithm for communication schedules across devices to deal with ITS malfunction. RSGCM provides solutions of communication schedules to various kinds of connection matrices with an acceptable amount of training time. Our experimental results have shown that RSGCM can deal with more varieties of connection matrices than existing state-of-the-art communication schedules. RSGCM also increases the robustness of ITS since it can restore the system’s functionality in an acceptable time when device or connection breakdown happens.

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cover image ACM Transactions on Multimedia Computing, Communications, and Applications

ACM Transactions on Multimedia Computing, Communications, and Applications Volume 20, Issue 2

February 2024

548 pages

EISSN:1551-6865

DOI:10.1145/3613570

Editor:
Abdulmotaleb El Saddik
Mohamed Bin Zayed University of Artificial Intelligence, UAE and University of Ottawa, Canada

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Publication History

Published: 27 September 2023

Online AM: 21 July 2022

Accepted: 13 July 2022

Revised: 04 July 2022

Received: 14 February 2022

Published in TOMM Volume 20, Issue 2

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National NSF of China
Shanghai Key Laboratory of Scalable Computing and Systems
Innovative Research Foundation of Ship General Performance
SJTU Library-Jiangsu Jiatu Future Library Smart Service Joint R&D Center
Key Laboratory of PK System Technologies Research of Hainan

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