Abstract:
The application discloses a load evaluation system for virtual machines in a cloud environment, comprising: a monitored data collecting module which is configured to collect monitored data from one or more virtual machines in a cloud data center; a monitored data processing module which is coupled with the monitored data collecting module and is configured to: perform aggregated grouping on the monitored data by using a first KMeans algorithm for each of the one or more virtual machines, each group having a center point coordinate, and calculate a performance characteristic of each virtual machine of the one or more virtual machines according to the grouping and the center point coordinates of individual groups, i.e., a first characteristic value; perform aggregated grouping on the one or more virtual machines using a second KMeans algorithm based on the first characteristic value of each virtual machine, thus determining the characteristic type and performance load value of each virtual machine of the one or more virtual machines. The application also discloses a load evaluation method for virtual machines in a cloud environment as well as a service node.
Abstract:
An online payment system comprises a payment server and a payment client. The payment server is configured to generate a unique identifier of a commodity/order and a random number as a challenge code, and to generate a two-dimensional code based on the unique identifier of the commodity/order and the challenge code, and is further configured to display the two-dimensional code on a display device. The payment client is configured to read the unique identifier of the commodity/order and the challenge code in the two-dimensional code from the display device, and is further configured to send a payment account, the unique identifier of the commodity/order, and a reply code to the payment server, and to perform a payment operation on the basis of the payment account, the unique identifier of the commodity/order, and the reply code.
Abstract:
Transaction processing method, apparatus, device, medium and system are disclosed in the embodiments of the present application. The method includes: acquiring biometric characteristic information of a user; transmitting the biometric characteristic information to a target biometric information server, so that the target biometric information server determines card information of the user according to the biometric characteristic information for feedback; receiving the card information of the user fed back by the target biometric information server; transmitting a transaction request to an authorization server corresponding to the card information, so that the authorization server performs authorization verification on a transaction corresponding to the transaction request; receiving a transaction authorization verification result fed back by the authorization server; and performing the transaction according to the transaction authorization verification result.
Abstract:
A method for sample alignment is applied to a first participant system, where a first trusted execution environment is deployed at the first participant system. The method includes, in the first trusted execution environment, obtaining at least one first sample identifier of the first participant system; through the first trusted execution environment, obtaining at least one second sample identifier of the second participant system from the second trusted execution environment, where the second trusted execution environment is deployed at the second participant system; in the first trusted execution environment, determining the first initial intersection of the at least one first sample identifier and the at least one second sample identifier and performing the shuffle processing on all first target sample identifiers in the first initial intersection to obtain the first target intersection; and based on the first target intersection, determining the first sample alignment result.
Abstract:
In embodiments, a server receives an HTTP protocol-based access request sent by the client; when the server determines that the access request comprises a preset identifier and the current identifier value corresponding to the preset identifier matches any of historical identifier values in a historical identifier set stored in the server, the server determines a user seed from the historical identifier set according to the current identifier value, the historical identifier set comprising a corresponding relationship between historical identifier values and user seeds, the any of historical identifier values being generated by the server on the basis of a user seed and a random number corresponding to the historical identifier value, and the user seed being used for identifying a same user recognized by the server on the basis of the access request; the server tracks an access behavior of the user seed.
Abstract:
A blockchain based numerical value ranking method includes: using, by a first participant, a public key of the first participant to encrypt a private value of the first participant to obtain an encrypted text of the first participant; obtaining encrypted texts of other participants, and generating a challenge value having a preset bit length; based on the challenge value and the private value of the first participant, and the encrypted texts and public keys of the other participants, determining mixed results of the first participant with respect to the other participants; and determining a numerical value ranking result between the first participant and a second participant based on the mixed result of the second participant with respect to the first participant.