National University of Defense Technology

Other

Deke Guo

Lailong Luo

Long Zheng

Siyuan Gu

Guoming Tang

Yahui Wu

Yang Guo

Pengtao Fu

Junjie Xie

Hao Yuan

Shangsen Li

Xinyi Li

Yi Wang

Junxu Xia

Zhong Lai Liu

Xueshan Luo

Bangbang Ren

Jiangfan Li

Chendie Yao

Xiaoqiang Teng

Xiaolei Zhou

Yiting Chen

Xiaofeng Cao

Bowen Sun

Geyao Cheng

Yan Li

A method and system for deduplication caching using an unreliable edge resource include acquiring a total storage capacity of all edge servers, searching for candidate cache files by a similarity-based hierarchical clustering (SHC) method, and acquiring file clusters of all the candidate cache files after clustering, where the candidate cache files each include a deduplicated data chunk, and based on the file clusters and an reliability of all of the edge servers, selecting, by a heuristic algorithm, a file cluster from the file clusters to cache to the edge server until a size of cached content reaches the total storage capacity. The present disclosure makes a trade-off between file availability and space efficiency, thereby effectively improving the cache hit rate in the limited edge caching space.

Unreliable edge

A method and an apparatus for data filtering are provided in this disclosure. The method is applied to a filtering system, including m buckets, each bucket including b storage slots, and each storage slot including a first domain and a second domain. The first domain is configured for recording fingerprint information of an element fingerprint of a data element, and the second domain is configured for matching and recording identifiers corresponding to the fingerprint information stored in the first domain. The method includes: determining an element fingerprint of a data element to be processed in response to an obtained target instruction; and performing a target operation on the data element based on at least the element fingerprint and stored information of the first domain and the second domain in each storage slot. The target operation at least includes one or more of inserting, querying and deleting operations.

Method and apparatus for data filtering

A method for updating a stable cuckoo filter used for membership testing of data streams, executed by a processor, is described. The method includes the steps of: performing a first hash on a first element to be inserted into the stable cuckoo filter to determine a first candidate bucket; performing a second hash on a fingerprint of the first element to determine a second candidate bucket; selecting a target candidate bucket from a group consisting of the first candidate bucket and the second candidate bucket; inserting the first element into the target candidate bucket; updating the stable cuckoo filter according to one or more of a random update strategy, an insertion failure update strategy, a scanning strategy, a skip scanning update strategy, a blocked design strategy and a local time-sensitive update strategy; and obtaining an updated stable cuckoo filter.

Stable cuckoo filter for data streams

A battery energy storage system (BESS) including: a battery storage configured to store surplus renewable energy; a controller coupled to the battery storage and configured to control charging operations and discharging operations of the battery storage; a generation meter coupled to the controller and configured to measure renewable energy; a renewable energy generator coupled to the generation meter and configured to generate renewable energy; and a standard meter coupled to the controller and configured to measure energy provided by a power grid; wherein the controller is configured to manage energy expenditure of the BESS according to the following steps: initializing a replay buffer configured to store state transition samples; initializing a main net configured to generate a current Q-value; initializing a target net configured to generate a target Q-value; obtaining an environment state of the BESS; and selecting an action based on an &#x3f5;-greedy policy.

BESS aided renewable energy supply using deep reinforcement learning for 5G and beyond

A system for streaming data items of a streaming application via a Vertical Cuckoo Filter (VCF), including: one or more computers communicating with a provider via a network; wherein the one or more computers includes: a processor; and a storage device coupled to the processor, wherein the storage device is configured to store the VCF, an insert module, a lookup module, and a delete module, the VCF includes buckets with one or more slots and includes at least two bitmasks, the insert module is configured to perform an insert operation of a first fingerprint of a first item from the provider on the VCF, the lookup module is configured to perform a lookup operation of a second fingerprint of a second item from the provider on the VCF, the delete module is configured to perform a delete operation of a third fingerprint of a third item from the VCF.

Vertical cuckoo filters

A Mobile-Assisted edge computing framework including: one or more requests to be processed; an operator configured to assign the one or more requests to a static edge node; and a cloud configured to cache and pre-fetch services for the one or more requests; wherein the one or more requests include handled requests and unhandled requests, the static edge node is configured to process the handled requests, and one or more mobile edge nodes are configured to process the unhandled requests; and wherein the static edge node is configured to auction the unhandled requests to the one or more mobile edge nodes, the auction including: generating a candidate set of the one or more mobile edge nodes; assigning an unhandled request to a target mobile edge node of the candidate set; and processing the unhandled request via the target mobile edge node.

Mobile-assisted edge computing framework for emerging IoT applications

The present disclosure relates to an online task dispatching and scheduling system. The system includes an end device; an access point (AP) configured to receive a task from the end device; one or more edge servers configured to receive the task from the AP, the one or more edge servers including a task waiting queue, a processing pool, a task completion queue, and a scheduler, wherein the AP further includes a dispatcher utilizing Online Learning (OL) for determining a real-time state of network conditions and server loads; and the AP selects a target edge server from the one or more edge servers to which the task is to be dispatched; and wherein the scheduler utilizes Deep Reinforcement Learning (DRL) in generating a task scheduling policy for the one or more edge servers.

Online task dispatching and scheduling system and method thereof

The present disclosure relates to an edge federation system, wherein the edge federation system includes: an end device; an edge service provider (ESP) configured to contract services from the end device; an edge infrastructure provider (EIP) configured to provide edge computing resources to the contracted services from the ESP; a cloud server configured to provide service to the end device; and a consortium for managing resources between the EIP and the cloud server, wherein the consortium is further configured to calculate available resources of the EIP, calculate available resources of the cloud server, and optimize the distribution of services from the EIP and the cloud server to the end device.

Edge federation system for an integrated service provisioning model and method thereof

Disclosed are a robust and reliable edge storage method for the Internet of Things and a system therefor. A data owner server splits and encrypts raw data into an encrypted data segment, sets a trusted data access control policy and sends it to a third-party proxy server, and sends the encrypted data segment and the trusted data access control policy to a processing server; the processing server stores the encrypted data segment based on a totally local reconstruction code scheme, and forwards the request sent by a data requester server to the third-party proxy server; the third-party proxy server determines whether the data requester server that sends the request is trustable according to the trusted data access control policy, if it is trusted, then sends decrypted information to the data requester server through the processing server; the data requester server decrypts the encrypted data segment according to the decrypted information to obtain the raw data.

Robust and reliable edge storage method and system for the Internet of Things

The invention discloses an implementation method of unstructured data sharing mechanism for edge computing and a system thereof, wherein the method includes the following steps: receive a data index request from a user, collect the switch, port, link and host information through the control plane to obtain the network topology and status; determine the coordinates of the switch and the coordinates of the data index in the virtual space formed by the network topology; construct a switch connection diagram according to the coordinates of the switch; insert the coordinates of the switch and forwarding entries of the switch connection diagram in the forwarding table of the switch; the data plane greedily forwards the coordinates of the data index until being transmitted to the switch corresponding to the switch coordinates closest to the coordinates of the data index in the virtual space.

Implementation method of unstructured data sharing mechanism for edge computing and the system

Provided are a method, an apparatus, and an electronic device for request scheduling of hybrid edge computing, wherein the request scheduling method includes: obtaining situations of a topological structure, computing resources and communication resources of a communication network; determining the number of hybrid edge servers placed in the communication network; dividing a problem of an optimal request scheduling path of the hybrid edge server into sub-problems of Mixed-Integer Non-Linear Programming (MINLP) models according to the situations of the topological structure, the number, the computing resources and the communication resources of the network; establishing the MINLP model according to the sub-problems respectively; converting the MINLP model into a Mixed-Integer Linear Programming (MILP) equation; and solving the MILP equation to obtain a placement node of the hybrid edge server and a target server for processing communication requests. The request scheduling method improves a request scheduling efficiency.

Method, apparatus, device and storage medium for request scheduling of hybrid edge computing

Provided are a robustness verification method and apparatus for a distributed control plane in a software-defined network, including constructing a robustness verification framework, where the robustness verification framework accommodates a failure scenario set and a failure recovery strategy set; selecting a failure recovery strategy, and querying a worst failure scenario under the failure recovery strategy; verifying a utilization rate of a biggest controller in the control plane under the combination of the worst failure scenario and the failure recovery strategy; and verifying the robustness of the control plane based on the utilization rate. The verification problem of the control plane is taken as a robustness optimization problem under different failure cases and failure recovery strategies. After the failure recovery strategy is selected, the worst failure scenario is obtained to determine whether the performance of the control plane satisfies requirements.

Robustness verification method and apparatus for distributed control plane in software-defined network

The present invention discloses an indoor semantic map updating method and system based on semantic information extraction. The method includes: issuing a crowdsourcing task to all mobile terminals; waiting for any mobile terminal to execute the crowdsourcing task, and receiving a task result thereof; preprocessing the task result to obtain a common key frame sequence; extracting an accurate text sequence from the common key frame sequence; and updating an indoor semantic map according to the common key frame sequence and the accurate text sequence. The present invention can encourage the mobile terminal to execute the crowdsourcing task, and update the indoor semantic map and the text semantic information at a lower cost.

Growing community of inventors

Hunan, China

Deke Guo