115 results about "Job stream" patented technology

A printing system capable of concurrently processing a plurality of job streams and including one or more marking engines and multiple print media destinations is controlled by a controller that includes a jobs scheduler for determining a schedule for processing queued print jobs using the plurality of concurrent job streams. The job scheduler determines the schedule using a method including: determining a utility function dependent at least upon user preference weighting values, a system model of capabilities of the parallel printing system, and the schedule of the queued print jobs; and optimizing the utility function respective to the schedule of queued print jobs.

In a task cooperative processing system that allows a plurality of task processing devices to execute a plurality of tasks performed on document data as a job flow, task processing devices that can execute a task included in the job flow are decided as candidate task processing devices (S82). A task processing device that can execute the largest number of tasks is decided as a primary task processing device from among the candidate task processing devices (S83). If there is a task that DETERMINE CANDIDATE TASK S82 can be executed by the primary task PROCESSING DEVICE processing device if the primary task processing device obtains a license of the task, the primary task processing device obtains the license from another device, and executes the task (S84).

The present invention includes the process of dividing the multiuser multimedia jobs of different transmission rate and different QoS requirement into several child job streams; channel multiple connection of the present invention to form closed-loop power control child channels of different QoS requirement; and performing cloed-loop power control to the child job streams. Adopting the closed-loop power control of the present invention multimedia CDMA communication system can meet the requirement of the multimedia jobs in different transmission rates and different QoS while minimizing emittedpower and interference and increasing system capacity.

A system and method are provided for adaptively controlling print options in a print system. The method comprises: accepting an imaging job; determining the imaging job characteristics; determining an imaging system's capabilities; matching system capabilities to job characteristics; and, performing the job on an imaging device. Determining job characteristics may involve determining the optimal print media, ink chemistry, or image processing. The imaging job characteristics may be determined by examining the print driver print stream to determine the file type, enacting a user interface dialog with the user, receiving pre-determined imaging job characteristics from a device driver embedded in a PRN image file, or-receiving pre-determined imaging job characteristics from a device driver embedded in a job stream. Determining the system capabilities may include determining the available print media, available inks, available image processes, or imaging device firmware.

An input image capture device, capable of sampling the color density and gloss of the fused printed image (thus not requiring the printing of density patches on a separate calibration page), may compare the printed image's color density and gloss to a predicted value. Then, appearance control may be achieved by changing fuser parameters (such as fuser nip width, fuser roller temperature and the like) and other electrophotographic element control parameters (such as exposure, off-set development voltage, charger voltage and the like) to maintain a desirable constant appearance (density, gloss, etc.) of images consistently in print engine usage (within a print run and between print runs), even if different media substrates are used on the same print job. Therefore, no waste calibration sheet is needed, and a print job operator may receive more timely feedback relating to the current printing job stream.

A device for facilitating verification of an electronic signature in an exchange of instructions between an in-house server and an outside server. Each server which is to execute a partial process of a cooperative service has, in a key storage unit (206), secret keys corresponding to public key certificates issued by an in-house CA and by an outside public CA. A signature key selection unit 216 judges whether a server which is to execute a process next is a device within or outside the company and selects an in-house secret key when the next server is an in-house device and an outside secret key when the next server is an outside device. A signature creation unit (218) calculates a value of an electronic signature for an job flow instruction to the next server using the selected secret key. An instruction division/integration unit (204) transmits to the next server the job flow instruction with the electronic signature value attached.

The invention discloses a step specification visual recognition judgment method and system based on deep learning. The method comprises the steps: obtaining a standard operation video of a worker, extracting a standard operation track in a corresponding monitoring region according to a target detection model, and segmenting the standard operation track into a plurality of steps according to an operation specification; obtaining a current worker operation video, and judging whether the current operation track of the worker in the monitoring area is matched with the standard operation track or not; giving a corresponding judgment result and/or information prompt according to the matching result; the system comprises a video stream receiving module, a client configurator module, a video stream analysis module, a step guide client and a main control computer, according to the embodiment of the invention, the system executes the method, compares the current operation track of the worker with the standard operation track, gives the corresponding judgment result and/or information prompt to guide the operation process of the worker and judge and standardize the operation omission and errors, effectively prevents the operation error problem, and improves the yield.

To create a job flow having machine type dependence and commonly usable among different types of devices, a CPU of a client PC displays first task information relating to tasks usable in a first print processing device and creates a first task cooperative job flow executable in the first print processing device. Then, the CPU of the client PC creates definition information of the first task cooperative job flow based on an edit instruction entered using the first task information. Furthermore, the CPU of the client PC produces definition information of a second task cooperative job flow executable in a second task processing device based on the definition information of the created first cooperative job flow as well as based on second task information relating to tasks usable in the second print processing device.

The invention relates to the technical field of safety monitoring, and provides a fault recovery method, computer equipment and a storage medium, and the method comprises the steps of obtaining the identification information of a server after the fault of the server is monitored; identifying the fault type of the fault; after a fault recovery operation flow identifier corresponding to the fault type is matched, forming a first fault alarm instruction; hooking the first fault alarm instruction by using a hook function, and sending a second fault alarm instruction carrying the identification information of the server and the fault recovery operation flow identification to the fault automatic processing system, so that the fault automatic processing system feeds back the fault recovery instruction; and calling a fault recovery workflow script in the fault recovery instruction through a client of the server to execute the fault recovery instruction. According to the invention, the solutioncorresponding to the fault is packaged into the fault recovery workflow script, and the monitoring system triggers the fault automatic processing system to call the fault recovery workflow script when the fault occurs, so that the fault is automatically solved.

A library of jobs is created, with the jobs performing predetermined functions. The jobs include a termination indication, which is success or failure. Input file formats of known file types are determined and a job stream to process the input files is constructed of the jobs linked according to the termination success or failure of the preceding job.

The invention relates to a streaming computing method and device based on DAG interaction, and relates to the field of data processing and cloud computing. The streaming computing method based on directed acyclic graph (DAG) interaction comprises the following steps: generating first DAG job flow description information according to a first DAG node graph consisting of DAG nodes belonging to a first type set; converting the first DAG workflow description information into second DAG workflow description information by adapting DAG nodes belonging to a first type set into DAG nodes belonging toa second type set and suitable for an Flink engine; packaging the second DAG workflow description information into a DAG execution packet, wherein the DAG execution packet comprises the second DAG workflow description information and operational logic of nodes in the second DAG workflow description information; and sending the DAG execution packet to the job running cluster.

The invention provides a method for job stream control. The method is used for a job stream control device in a distributed job stream control device cluster. The method comprises: after a job stream starting request is received, obtaining job stream template data and job stream initialization data, and according to the job stream initialization data, instantiating the job stream template data and generating job stream instance data, then, sending the job stream template data, the job stream initialization data, and the job stream instance data to a distributed memory cluster to store. Through the method, when any job stream control device is abnormal, other job stream control devices can read the data which is stored in the distributed memory cluster by the abnormal job stream control device from the distributed memory cluster, and recover and execute the job stream thereof, to ensure smooth execution of a job stream and prevent a problem of failure of a whole task caused by abnormity of one job stream control device.

The invention discloses a method for displaying a standard operation flow in a server production process, which comprises the following steps: obtaining a model number of a server to be assembled; Searching a standard operation flow video file set of the model server generated in advance, wherein the standard operation flow video file set includes installation video files of various accessories ofthe model server; Receiving an input device code of an accessory of a server to be assembled; calling the installation video file corresponding to the accessories in the standard operation flow videofile set for playback and display. The application adopts the mode of dynamic video to make the demonstration of the server assembly production process vivid, simple and intuitive, clear in organization, convenient for operators to understand and remember, greatly reducing the rework rate of the installation error, and effectively improving the assembly production efficiency. The invention also discloses a display device, a device and a computer-readable storage medium of a standard operation flow in the production process of a server, which also has the above-mentioned beneficial effects.

The invention provides a data processing method and device, computer equipment and a storage medium. The method comprises the following steps: determining a target plug-in matched with a data processing demand of a target service system in at least one plug-in; generating a job for performing data processing on the target service system in response to an editing operation on the job attribute in the configuration page of the target plug-in; generating a job flow of the target service system according to at least one job used for performing data processing on the target service system; under the condition that the user sending the data processing request has the processing authority to the target service system, the target operation flow of the target service system indicated by the data processing request is called to process the data of the target service system pulled in the database cluster. According to the method, data processing of various data processing scenes is realized through a unified data development system, so that the development difficulty can be reduced, the development efficiency can be improved, and the online data processing capability can be improved on the basis of simplifying the data processing operation.

The invention relates to the technical field of computer software. The standard operation flow management system comprises at least one operation flow input terminal, a file manager connected with theoperation flow input terminal, at least one main control computer connected with the file manager, and at least one playing device connected with the main control computer and controlled by the maincontrol computer. According to the method, the SOP is played in the forms of pictures and images and is matched with brief character instructions, so that the operation process can be timely, effectively and comprehensively used for guiding production, and an operator can understand the SOP visually and clearly at a high speed and is not prone to making mistakes.

The invention relates to a decentralized big data job flow scheduling method and device. The workflow scheduling method comprises the following steps: S1, a workflow is created, the workflow is converted into a process instance, an operation command is executed on the process instance, and the operation command is written into a workflow command table; S2, an Master cluster competes to obtain commands in the workflow command table, analyzes corresponding process instances, splits the process instances into task instances, and writes the task instances into a task queue; and S3, the Worker cluster competes to obtain the batch tasks in the task queue, instantiates the batch tasks and then executes the batch tasks. The Master cluster and the Worker cluster are arranged in a decentralized mode, meanwhile, one server is selected as a manager to execute a task by adopting a distributed lock, all nodes can serve as Maste/Worker functions, a single manager different from other nodes does not exist, and the reliability of the system is improved. The situation that the whole big data job scheduling is stopped due to the fact that the centralized Master node breaks down is avoided, and the stability and robustness of the system are improved.

The invention discloses a cross-domain job stream scheduling method and system. The method comprises: selecting a job stream scheduling cluster A in a collaborative scheduling network to receive a data processing service demand sent by an application provider; arranging the job stream according to the logic of the data processing service demand, and dividing into a plurality of data service processing blocks; allocating the plurality of data service processing block a plurality of job stream scheduling clusters in the collaborative scheduling network for processing according to the arranging logic of the job stream; each of the plurality of job stream scheduling clusters processing the corresponding allocated data service processing block and generating data; and outputting the generated data to the predetermined job stream scheduling cluster through a federated data channel and storing the data in a corresponding database. The method and system achieve multi-engine parallel cross-domain data scheduling by adopting a non-master-slave cooperative scheduling network, and improve the processing speed and avoid the risk caused by single point failure through parallel processing.

The invention relates to the field of intelligent decision making, realizes automatic configuration of an operation process according to user operation behaviors, and specifically discloses a configuration updating method and device based on behavior analysis, equipment and a storage medium. The method comprise: obtaining burying point record data of a target user terminal, wherein the burying point record data comprise statistical data of a plurality of burying point events; based on a function completion rate model of each target event node, determining a function completion rate of each target event node according to statistical data in the burying point record data, wherein the target event node is an event node in a decision tree model; determining a target event flow according to thefunction completion rate of each target event node based on the decision tree model, wherein the target event flow comprises at least one target event node; and determining configuration data according to the target event flow, and sending the configuration data to the target user terminal, so that the target user terminal updates configuration according to the configuration data.

The invention discloses a deep learning programming method and system based on a digital twin DaaS platform, and the method comprises the steps: obtaining the equipment operation data of each sub-operation process in the business processes of different terminal devices, and enabling the equipment operation data to comprise the process number of each sub-operation process, and performing data modeling on the equipment operation data of each sub-operation process in the different terminal equipment, performing comparative analysis, judging whether the terminal equipment needs to be upgraded and optimized or not based on an analysis result, performing deep learning programming on the equipment operation data of each sub-operation process based on a trained time sequence programming model, and if not, performing deep learning programming on the equipment operation data of each sub-operation process. A target operation code is automatically generated, the target operation code is upgraded to the corresponding terminal equipment in a distributed mode, and the time sequence programming model is constructed based on equipment operation data, collected in advance, of all sub-operation processes corresponding to service processes in different terminal equipment. According to the method and the device, the problems of relatively low business process and equipment optimization upgrading efficiency and relatively high labor cost are solved.

The invention discloses a digital twin station system, a job scheduling method based on the system and application. The job scheduling method comprises: inputting processed static data and dynamic data of a physical station into a trained prediction model to obtain job prediction parameters; inputting the operation prediction parameters into a digital twin station simulation model, and performing operation process simulation to obtain simulation operation indexes; and making a scheduling decision based on the simulation operation index. According to the invention, a digital twin station system in which a physical station and a virtual station cooperatively interact is constructed, real-time connection and dynamic feedback between a physical system and a digital system are formed, and efficient and accurate prediction, simulation and decision scheduling can be carried out on station operation.

The embodiment of the invention belongs to the field of big data, and relates to a task scheduling method, which comprises the steps of obtaining dependency relationship and scheduling moments of all to-be-executed tasks, each to-be-executed task at least comprising one scheduling moment; according to the scheduling moments and the dependency relationship, constructing multiple layers of to-be-processed job streams of the to-be-executed task, and storing all the to-be-processed job streams in a preset database; and when a task execution instruction is received, calling a coordinator corresponding to the task execution instruction, and calling a target job stream corresponding to the task execution instruction from the to-be-processed job stream to an execution machine based on the coordinator, so that the execution machine executes the target job stream. The invention further provides a task scheduling device, computer equipment and a storage medium. In addition, the invention also relates to a blockchain technology, and the to-be-processed job stream can be stored in the blockchain. According to the invention, accurate scheduling and execution of multi-period tasks is realized.