Huawei Technologies Co., Ltd.

Key-value stores in Cloud environments can contain more than 2⁴⁵ unique elements and be larger than 100 PByte. B⁺-Trees are well suited for these larger-than-memory datasets and seamlessly index data stored on thousands of secondary storage devices. ...

RDMA-based in-memory storage systems offer high performance but are restricted by the capacity of physical memory. In this article, we propose TeRM to extend RDMA-attached memory with SSD. TeRM achieves fast remote access on the SSD-extended memory by ...

Traditional click-through rate (CTR) prediction models convert the tabular data into one-hot vectors and leverage the collaborative relations among features for inferring the user’s preference over items. This modeling paradigm discards essential semantic ...

Configuring intelligent surface (IS) or passive antenna array without any channel knowledge, namely blind beamforming, is a frontier research topic in the wireless communication field. Existing methods in the previous literature for blind beamforming ...

The future B5G/6G wireless networks are required to intelligently operate and optimize in all ranges of scenarios, however, most of the functions in self-organizing network (SON) architectures are rule-based and reactive, these rigid functions can not ...

Graph Neural Networks (GNNs) have aroused increasing research attention for their effectiveness on graph mining tasks. However, full-batch training methods based on stochastic gradient descent (SGD) require substantial resources since all gradient-...

Automated container terminals are complex systems where multiple subsystems are deeply interconnected. To enhance overall efficiency, integrating the scheduling of these subsystems is crucial. While most existing literature emphasizes scheduling ...

• Proposes a system-thinking optimization for integrated scheduling in automated container terminals without relying on specific processing and setup times.
• Introduces a complex network model, transforming scheduling issues into a ...

Convolutional Neural Network (CNN) operators, mostly based on mathematical linear computations, are of vital importance to developing CNN-based software. Existing studies reveal that these operators are prone to floating-point precision problems (FPPs). ...

Large language models (LLMs), such as ChatGPT released by OpenAI, have attracted significant attention from both industry and academia due to their demonstrated ability to generate high-quality content for various tasks. Despite the impressive ...

The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), fueling a paradigm shift in information acquisition. Nevertheless, LLMs are prone to hallucination, generating plausible yet ...

Accurately predicting user mobility is crucial for effectively assigning spatiotemporal crowdsensing tasks to appropriate mobile users, thereby enhancing task completion rates. While prior studies have proposed various trajectory-based mobility ...

Accurate and efficient localization of root cause instances in large-scale microservice systems is of paramount importance. Unfortunately, prevailing methods face several limitations. Notably, some recent methods rely on supervised learning which ...

Nowadays, optimized cost-per-click (OCPC) has been widely adopted in online advertising. In OCPC, the advertiser sets an expected cost-per-conversion and pays per click, while the platform automatically adjusts the bid on each click to meet advertiser’s ...

With the rapid development of online services and web applications, recommender systems (RS) have become increasingly indispensable for mitigating information overload and matching users’ information needs by providing personalized suggestions over items. ...

Legal case retrieval is an important task in information retrieval that aims to retrieve relevant cases for given query cases. Conversational search paradigms have been shown to improve the search experience in legal case retrieval. However, there are two ...

With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the field of software engineering (SE) has also witnessed a paradigm shift. These models, by leveraging the power of deep learning and massive amounts of data, have ...

Proper naming of methods can make program code easier to understand, and thus enhance software maintainability. Yet, developers may use inconsistent names due to poor communication or a lack of familiarity with conventions within the software development ...

Multitopology routing (MTR) provides an attractive alternative to segment routing (SR) for traffic engineering when network devices cannot be upgraded. However, due to a high overhead in terms of link state messages exchanged by topologies and ...

Our main contribution, virtual MTR (vMTR), generates virtual topologies by combining existing interior gateway protocol (IGP) topologies with the aim of limiting overhead and improving QoS satisfaction. An operator can combine IGP topologies to produce ...

Graph neural networks (GNN) have achieved remarkable success in a wide range of tasks by encoding features combined with topology to create effective representations. However, the fundamental problem of understanding and analyzing how graph ...