32results about How to "Flexible migration" patented technology

The invention provides a MySQL database horizontal-sharding method. The method includes: distributing a data ID range (Min(n), Max(n)) for a database in a database cluster according to a preset data ID range distribution strategy; and storing MySQL data to each database with the data ID range including data IDs according to the data IDS of the MySQL data. The letter N is a total of the databases in the database cluster, the Min(n) is a minimum boundary value of the data ID range of the n-th database, and the Max(n) is a maximum boundary value of the data ID range of the n-th database. Through the method, the MySQL databases can be sharded and transferred flexibly and extensibility is improved.

The invention discloses a two-level management method for a hybrid desktop cloud service platform. The two-level management method for the hybrid desktop cloud service platform comprises the following steps: building a hybrid desktop cloud data center; sending a login request to a central management node (Vmm-Server) by a server node; receiving and processing the login request of the server node by the central management node; uniformly receiving user requests by the central management node through a service interface layer; responding to the user requests by the central management mode according to a two-tier scheduling method; maintaining system load balance by the central management node according to the current system state and the running state of a virtual machine. According to the two-level management method disclosed by the invention is designed and realized upon the open system architecture of a hybrid desktop cloud server, and the scheduling and migration efficiency of the virtual machine can be improved.

The invention provides a data recovery and migration method and device. The method includes: a configuration step, configuring data recovery and migration tasks, and setting parameters associated with the tasks; a data reading step, according to the parameters, sequentially reading historical data in batches, and reading for each batch The historical data of the data file is separately generated and buffered, and the data range and read data mark of each data file are stored in Redis; and the data writing step is to obtain each batch of data to be restored from Redis according to the parameters Range and read data mark, if the read data is marked as failure, then terminate, otherwise, according to the data range, the buffered historical data will be restored to the source database or migrated to the target database in batches, and the data of each data file Range and write data tags are stored in Redis.

The present invention relates to the technical field of communication networks. Disclosed are a compute node migration method and device, capable of flexibly and concurrently migrating a compute node according to the load of each compute node in a compute cluster. In an embodiment of the present invention, the method comprises: obtaining the current load sequence of each compute node in a compute cluster; determining the compute node having the least but not zero load in the load sequence as a compute node to be currently subjected to first analog migration; conducting analog migration on a virtual machine managed by the compute node to be currently subjected to first analog migration to the target compute node of the first analog migration; determining the compute node having an original load less than the load of the compute node to be currently subjected to first analog migration as the first batch of compute nodes to be concurrently migrated; and then conducting first concurrent migration on the first batch of compute nodes to be concurrently migrated. The solution provided in the embodiment of the present invention is suitable for compute node migration.

The invention discloses a dependable virtual platform and a construction method thereof, a data migration method among platforms. The dependable virtual platform comprises a hardware security chip, a virtual machine monitor (VMM), an administrative domain, a user domain and a dependable serving domain (TSD), wherein an expanded trust chain is used by the TSD for users to establish dependable operating environment. The construction method includes: building the TSD; then establishing secure communication mechanisms between the managing domain and the TSD and between the managing domain and a domestic user domain; accomplishing calls of security application of the user domain to a dependable function by the user domain through interaction with the managing domain, accomplishing transmission and treatments of dependable orders by the managing domain through the interaction of the TSD; interacting a source platform migration engine and a goal platform migration engine; migrating migration data which is produced and based on the hardware security chip and the TSD to a goal platform, and recovering data on the goal platform, accomplishing quick migration of the TSD and a virtual machine. The dependable virtual platform and the construction method thereof, the data migration method among platforms are capable of improving safety of dependable service and providing flexible operation and deployment mechanisms for the platforms.

The invention discloses an anti-adversarial attack camera source recognition method based on local smooth projection, comprising the steps of: 1) camera image preprocessing; 2) constructing a camera source recognition feature extraction network; 3) generating a noise image block set; 4) Define a local smooth projection loss function; 5) Construct a front-end defense network for camera source recognition; 6) Apply a recognition model. The invention utilizes a local smooth projection to effectively suppress the adversarial noise in the feature extraction process of the camera source recognition so as to extract features with adversarial robustness, thereby realizing defense against adversarial attacks in the camera source recognition. At the same time, the present invention adopts a camera source recognition pre-defense network, which separates the feature extraction process from the defense process, which is not only easy to train, but also can be transferred to different camera source recognition networks. The invention takes into account the accuracy, robustness and transferability of the camera source recognition method based on the deep neural network.