Huawei

About: Huawei is a company organization based out in Shenzhen, China. It is known for research contribution in the topics: Terminal (electronics) & Signal. The organization has 41417 authors who have published 44698 publications receiving 343496 citations. The organization is also known as: Huawei Technologies & Huawei Technologies Co., Ltd..

Peer-to-peer network system, proxy service peer, and method for peer interworking between overlay networks

Abstract: The present invention relates to a P2P network system. The P2P network system includes: multiple local overlay networks, each comprising multiple proxy service peers; a global overlay network composed of the proxy service peers of all local overlay networks. The proxy service peer is adapted to respond to the request of the requesting peer, query the local overlay network or global overlay network, and return the address information of the requested peer or the requested proxy service peer to the requesting peer. The present invention also relates to a proxy service peer applicable to the foregoing network system, and a method of peer interworking between P2P overlay networks based on the foregoing system. The present invention relieves the load of the proxy service peer, avoids blindness of the requesting peer in selecting the proxy service peer, and achieves load balance between proxy service peers.

NEZHA: Neural Contextualized Representation for Chinese Language Understanding.

Abstract: The pre-trained language models have achieved great successes in various natural language understanding (NLU) tasks due to its capacity to capture the deep contextualized information in text by pre-training on large-scale corpora. In this technical report, we present our practice of pre-training language models named NEZHA (NEural contextualiZed representation for CHinese lAnguage understanding) on Chinese corpora and finetuning for the Chinese NLU tasks. The current version of NEZHA is based on BERT with a collection of proven improvements, which include Functional Relative Positional Encoding as an effective positional encoding scheme, Whole Word Masking strategy, Mixed Precision Training and the LAMB Optimizer in training the models. The experimental results show that NEZHA achieves the state-of-the-art performances when finetuned on several representative Chinese tasks, including named entity recognition (People's Daily NER), sentence matching (LCQMC), Chinese sentiment classification (ChnSenti) and natural language inference (XNLI).

Dynamic Network Function Instance Scaling Based on Traffic Forecasting and VNF Placement in Operator Data Centers

Abstract: Traffic in operator networks is time varying Conventional network functions implemented by black-boxes should satisfy the peak traffic requirement, and hence result in low resource utilization Thanks to the emergence of Virtual Network Function (VNF), which is realized by running networking software on Virtual Machines (VMs), the operator can dynamically scale in or scale out the VNF instances and hence save the required resources In this paper, we introduce how the dynamic VNF scaling is implemented in practical operator Data Center Networks (DCNs) First, we analyze the traffic characteristics in our operator networks, and introduce how the VNFs are organized in a common operator DCN Based on these backgrounds, we not only propose a traffic forecasting method, but also design two VNF placement algorithms to guide the dynamic VNF instance scaling Through both the implementation in a real operator network and extensive real trace driven simulations, we demonstrate that our dynamic VNF instance scaling system can achieve higher service availability and save the VNF resources (eg, CPU and memory) by up to 30 percent

Data Transmission Method, Device and System

Abstract: A data transmission method, device and system to improve reliability of a data link. When the sender side detects erroneous data, the erroneous data is discarded and a data retransmission request is sent to the sender side to ensure correctness of received data and improve reliability of the data link; and, when the sender side detects the erroneous data and a bit error rate is greater than a preset bit error rate threshold, the data link gets into auto recovery, and data transmission is resumed after the recovery succeeds, thereby avoiding an excessively high bit error rate, preventing an excessively high probability of omitted checks (the higher the bit error rate is, the higher probability of omitted checks is), and further improving reliability of the data link.