Huazhong University of Science and Technology

Huawei Technologies Co., Limited

Atel Technologies Co., Ltd.

Song Wu

Qian Wang

Hai Jin

Xuanhua Shi

Bo Xu

Wei Wang

Kemeng Wang

Yiwen Gong

Feng Lu

Dejin Zhu

Zhuang Xiong

Fei Chen

Zhengyan Mao

Junjian Guan

Chao Niu

Xiaoping Gao

Xin Yu

Xuerong Guo

Hanfeng Qin

Die Hu

Ziqian Shi

Qizhi Tang

Ruoxue Liu

Ximing Chen

Shengwei Bian

Hao Fan

Yulong Zhou

Zhiyi Liu

Zhengdong Jia

A data transmission method is applied to a decoding end of a network audio and video matrix system, and the decoding end is in communication connection with an encoding end and several secondary decoding ends. The data transmission method comprises: acquiring request data signaling from a secondary decoding end, wherein the request data signaling comprises a distribution data signaling receiving address of the secondary decoding end; determining whether a currently occupied distribution capability value reaches a maximum distribution capability value; and if yes, sending a secondary distribution device table to the secondary decoding end, such that the secondary decoding end sends the request data signaling to other secondary decoding ends in the secondary distribution device table, and after the sending of the secondary distribution device table is completed, disconnecting a network connection with the secondary decoding end.

Data transmission method, terminal device, and computer-readable storage medium

The present invention relates to a Docker-container-oriented method for isolation of file system resources, which allocates host file system resources according to access requests from containers and checks lock resources corresponding to the access requests. The method creates a plurality of new containers; allocating the host file system resources according to file resource request parameters required by the new containers; and controlling execution of the file system operation according to an amount of the file system resources that have been allocated to the new containers.

Docker-container-oriented method for isolation of file system resources

The present disclosure discloses a NVM-based method for performance acceleration of containers. The method comprises classifying each image layer of mirror images as either an LAL (Layer above LDL) or an LBL (Layer below LDL) during deployment of containers; storing the LALs into a non-volatile memory and selectively storing each said LBL into one of the non-volatile memory and a hard drive; acquiring hot image files required by the containers during startup and/or operation of the containers and storing the hot image files required by the containers into the non-volatile memory; and sorting the mirror images in terms of access frequency according to at least numbers of times of access to the hot image files so as to release the non-volatile memory currently occupied by the mirror image having the lowest access frequency when the non-volatile memory is short of storage space.

Non-volatile memory (NVM) based method for performance acceleration of containers

The present invention relates to an edge-computing-oriented construction method for a container image, and the construction method for a container image at least comprising steps of: having an image reconstruction module reconstruct an old container image so as to obtain a new container image comprising an index and a set of spare files that correspond to each other, and having an image management module store the index and the spare files separately from each other in an image repository and a spare file storage module respectively; having a download engine module scrape the index from the image repository to a corresponding container in the edge end, so that a container instance service module conducts search in a local file sharing module according to configuration information contained in the index and thereby retrieves a local shared file corresponding to the configuration information, an image file consulting module is configured to download a default file from the spare file storage module that does not exist in the local shared file retrieved according to the configuration information, and a service processor uploads the local shared file and the default file recorded according to the configuration information to the image reconstruction module, so that to match and to generate the index.

Edge-computing-oriented construction method for container mirror image

A network resource isolation method for container networks and a system thereof, including a computation system for network resource isolation, or a system using network resource isolation, or a network resource isolation system for container networks, and methods of implementation thereof. The system provides container overlay networks with a resource isolation scheme that also reduces the use threshold for isolation of network resources and optimizes the utilization rate of network resources.

Network resource isolation method for container network and system thereof

The present invention relates to an acceleration method for an FPGA-based distributed stream processing system, which accomplishes computational processing of stream processing operations through collaborative computing conducted by FPGA devices and a CPU module and at least comprises following steps: building the FPGA-based distributed stream processing system having a master node by installing the FPGA devices on slave nodes; dividing stream applications into first tasks suitable to be executed by the FPGA devices and second tasks suitable to be executed by the CPU module; and where the stream applications submitted to the master node are configured with kernel files that can be compiled and executed by the FPGA devices or with uploading paths of the kernel files, making the master node allocate and schedule resources by pre-processing the stream applications.

Acceleration method for FPGA-based distributed stream processing system

An S.M.A.R.T. threshold optimization method used for disk failure detection includes the steps of: analyzing S.M.A.R.T. attributes based on correlation between S.M.A.R.T. attribute information about plural failed and non-failed disks and failure information and sieving out weakly correlated attributes and/or strongly correlated attributes; and setting threshold intervals, multivariate thresholds and/or native thresholds corresponding to the S.M.A.R.T. attributes based on distribution patterns of the strongly or weakly correlated attributes. As compared to reactive fault tolerance, the disclosed method has no negative effects on reading and writing performance of disks and performance of storage systems as a whole. As compared to the known methods that use native disk S.M.A.R.T. thresholds, the disclosed method significantly improves disk failure detection rate with a low false alarm rate. As compared to disk failure forecast based on machine learning algorithm, the disclosed method has good interpretability and allows easy adjustment of its forecast performance.

S.M.A.R.T. threshold optimization method used for disk failure detection

The present disclosure provides a method for implementation and optimization of an online migration system for Docker containers.

Method for implementation and optimization of online migration system for dockers container

The present invention discloses a container-based mobile code offloading support system in a cloud environment and the offloading method thereof, comprising a front-end processing layer, a runtime layer and a back-end resource layer. The front-end processing layer is responsible for responding to an arrived request and managing a status of a container, which is realized by a request distribution module, a code caching module and a monitoring and scheduling module; the runtime layer provides the same execution environment as that of a terminal, which is realized by a runtime module consisted of a plurality of mobile cloud containers; and the back-end resource layer solves incompatibility of a cloud platform with an mobile terminal environment and provides underlying resource support for a runtime, which is realized by a resource sharing module and an extended kernel module within a host operating system. The present invention utilizes the built mobile cloud container as the runtime environment for offloading code, ensuring execution requirements of offloading tasks and improving the computing performance of a cloud; cooperation between respective modules makes a further optimization to the performance of the platform, guaranteeing an efficient operation for the system.

Container-based mobile code offloading support system in cloud environment and offloading method thereof

The present invention relates to a method for cloudlet-based optimization of energy consumption, comprises: building a cloudlet system that comprises: at least two cloudlets and a mobile device wirelessly connected to the cloudlets, so that the cloudlets provide the mobile device wirelessly connected thereto with cloud computing services; acquiring system data related to the mobile device from the cloudlet system for analyzing a data volume to be handled by the mobile device locally and setting an initial operating frequency Ffor a first processor of the mobile device according to the data volume; and based on a tolerable latency range T of a task queue, dynamically deciding a scheduling strategy for individual task of the task queue using a Markov Decision Process, and setting a present operating frequency Ffor the first processor of the mobile device corresponding to the scheduling strategy, so as to enable the mobile device to complete the tasks within the tolerable latency range T with minimal energy consumption.

Method for cloudlet-based optimization of energy consumption

The present invention involves with a dynamic distributed processing method for stream data, at least comprising: analyzing and predicting an execution mode of at least one data feature block of the data of a user stream data processing program; dynamically adjusting the execution mode based on an average magnitude of queue latency and a threshold of queue latency of the stream data; and processing corresponding said at least one data feature block based on the execution mode. By associating and combining the irrelevant data stream mode and micro-batch mode of stream data computing, the present invention successfully releases automatic shift and data process between the two modes, which advantageously has both the high throughput property and the low latency property.

Distributed dynamic processing method for stream data within a computer system

An antenna equipment includes an antenna and a board on which the antenna is disposed, and includes an area that is disposed on the board and that is not covered by a metal layer. A first edge of the board is a longer edge of the board in two edges of the board that are close to the antenna, a point that is on the first edge and whose distance with a current maximum point on the first edge is &#x3bb;/4 is a first point, the current maximum point is on the first edge and that is closest to a feed point of the antenna, and &#x3bb; is an operating wavelength of the antenna. The area that is not covered by a metal layer includes the first point, and a maximum distance from an edge of the area to the first edge of the board is &#x3bb;/4.

Antenna equipment and terminal

A mixed cache is indexed to main memory and page coloring is applied to map main memory to virtual memory. A nursery array and a mature array are indexed to virtual memory. An access to a virtual page from the mixed cache is recorded by determining an index and a tag of an array address based on a virtual address, following the index to corresponding rows in the nursery and the mature arrays, and determining if the tag in the array address matches any tag in the rows. When there is a match to a tag in the rows, an access count in a virtual page entry corresponding to the matched tags is incremented. When there is no match, a virtual page entry in the row in the nursery array is written with the tag in the array address and an access count in the entry is incremented.

Mixed cache management

In some examples, in a virtual environment, multiple virtual machines may be executing on a physical computing node. Each of the multiple virtual machines may host one or more applications, each of which utilizes at least a portion of a hardware resource of the physical computing node. A hypervisor of the virtual environment may be configured to recognize utilization patterns of the applications and allocate portions of the hardware resource to each of the applications in accordance with respective utilization patterns of the applications.

Growing community of inventors

Hubei, China

Song Wu