The existing graph neural network (GNN) systems adopt sample-based training on large-scale graphs over multiple GPUs. Although they support large-scale graph training, large data loading overhead is still a bottleneck...
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The conventional Levenberg-Marquardt (LM) algorithm is a state-of-the-art trust-region optimization method for solving bundle adjustment problems in the Structure-from-Motion community, which not only takes advantage ...
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Unsupervised visual representation learning has gained much attention from the computer vision community because of the recent contrastive learning achievements. Current work mainly adopts instance discrimination as t...
The development of a basic scalable preprocessing tool is the key routine to accelerate the entire computational fluid dynamics (CFD) workflow toward the exascale computing era. In this work, a parallel preprocessing ...
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Federated Learning (FL) is a distributed machine learning framework in communication network systems. However, the systems’ Non-Independent and Identically distributed (Non-IID) data negatively affect the convergence...
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Abstract: Predicting pollutant leakage and diffusion processes is crucial for ensuring people’s safety. While the deep learning method offers high simulation efficiency and superior generalization, there is currently...
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K-Means algorithm is one of the most common clustering algorithms widely applied in various data analysis applications. Yinyang K-Means algorithm is a popular enhanced K-Means algorithm that avoids most unnecessary ca...
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In various domains, the increasing application of machine learning allows researchers to access inexpensive predictive data, which can be utilized as auxiliary data for statistical inference. Although such data are of...
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Broadcast authentication is a critical security service in wireless sensor networks. A protocol named $\mu\text{TESLA}$ [1] has been proposed to provide efficient authentication service for such networks. However, w...
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Broadcast authentication is a critical security service in wireless sensor networks. A protocol named $\mu\text{TESLA}$ [1] has been proposed to provide efficient authentication service for such networks. However, when applied to applications such as time synchronization and fire alarm in which broadcast messages are sent infrequently, $\mu\text{TESLA}$ encounters problems of wasted key resources and slow message verification. This paper presents a new protocol named GBA (Generalized broadcast authentication), for efficient broadcast authentication in these applications. GBA utilizes the one-way key chain mechanism of $\mu\text{TESLA}$ , but modifies the keys and time intervals association, and changes the key disclosure mechanism according to the message transmission model in these applications. The proposed technique can take full use of key resources, and shorten the message verification time to an acceptable level. The analysis and experiments show that GBA is more efficient and practical than $\mu\text{TESLA}$ in applications with various message transmission models.
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