University of Electronic Science and Technology of China

Gang Sun

Hongfang Yu

Dan Liao

Du Xu

Chongxi Ma

Peng Zhao

Qing Li

Jing Ren

Tie Ma

Guanghua Yang

Yunhan Xie

Yueyue Dai

Jian Sun

Yuhui Wang

Long Luo

Qingwei Ji

Dongcheng Zhao

Bing Qiu

Linjian Yu

A hierarchical proxy deployment method includes: performing information collection and information interaction in a hierarchical proxy deployment architecture to obtain bandwidths and latencies of all inter-node communication links; and selecting an optimal proxy deployment solution from all feasible proxy deployment solutions based on the bandwidths and latencies of all the inter-node communication links. According to the method, a hierarchical proxy deployment architecture is used. An optimal proxy deployment solution is formed by selecting the optimal location and the optimal number of proxies for deployment to meet the transmission performance requirement of network applications in 5G/B5G networks. Therefore, transmission performance requirements are satisfied by a proxy deployment with a minimized number of proxies, thereby reducing network overheads and resource waste.

Hierarchical proxy deployment method

A network emulation system supporting a flexible and efficient dynamic experiment emulates a network based on container, veth-pair, traffic control (TC), and other technologies and sets a network state management model based on a key-value pair, thereby constructing a network emulation system supporting a flexible and efficient dynamic experiment. The system flexibly realizes the dynamic performance of a plurality of dimensions, namely, dynamic node start/stop, dynamic node attribute configuration, dynamic link start/stop, and dynamic link attribute configuration. Based on the network state management model, the network emulation system provides a concise and unified dynamic application programming interface (API) for an upper layer. Researchers can call the API in their network innovation programs at any time after an emulation network is deployed to achieve efficient, batch-processing, and programmable dynamic management. The network emulation system greatly facilitates the experimental work of the researchers in a dynamic scenario of the network.

Network emulation system supporting flexible and efficient dynamic experiment

A dynamic network resource allocation method based on network slicing is provided. A historical resource demand dataset of an accessed network slice is inputted into a first neural network for training. Based on a trained first neural network and the historical resource demand of the accessed network slice, a resource demand prediction information corresponding to the accessed network slice in a first prediction time period is determined. Resources are pre-allocated to the accessed network slice based on the resource demand prediction information, and resources are allocated to the accessed network slice when the first prediction time period arrives. In this way, the service provider can reasonably allocate network resources for network slices without violating the SLA, thus avoiding the waste of network resources.

Dynamic network resource allocation method based on network slicing

The present invention discloses an energy-saving deployment method of a virtual CDN. According to the historical flow data of the virtual CDN and the prediction model (ARIMA) in the controller, the network peak flow in the next time period is predicted. Next, the scale of the virtual CDN system at the next moment is calculated according to the peak flow. Meanwhile, several redundant servers are added to correct the prediction error. The network flow is aggregated to the desired virtual servers based on the calculation of the controller through a load balancer. In this way, the utilization rate of the virtual CDN system can be increased, and the energy consumed due to the higher utilization rate of the CDN system is saved.

Energy-saving deployment method of virtual CDN

The present invention provides a method for associating a user with a base station based on backhaul capacity in heterogeneous cellular network. First, an available base station set is obtained through the SINRs, and the downlink data rate between the new user and each base station in the available base station set is calculated according to the SINR between them; Then, the usable link capacity factor of each base station is calculated based on the used link capacity and the backhaul capacity; Finally, the optimal base station is selected for the new user i under a constraint which is constructed by the bandwidth of the new user and the usable link capacity factor. The backhaul capacity of each base station is taken into account in selecting the optimal base station to associate with for the new user, thus the real time of user association and the overall performance of heterogeneous cellular network can be guaranteed.

Method for associating a user with a base station based on backhaul capacity in heterogeneous cellular network

The present invention provides a method for accessing internet via a vehicle network. Vehicle terminal equipment can access OBU by means of the wireless AP on OBU, and realize the mutual communication with internet with the help of VANET network composed by OBU and RSU. Not only the normal communication between the OBU and RSU is guaranteed, but also the communication between vehicle terminal equipment and internet can be realized. Moreover, the present invention has the characteristics of anti-interference, convenience and real-time performance, and can adapt to the demand of the current network.

Method for accessing internet via a vehicle network

Growing community of inventors

Chengdu, China

Gang Sun