According to some embodiments, described herein is a system and method for classifying and grouping users of a task database system based on their activities in completing tasks defined in the task database system. A cloud server communicatively coupled to the task database system receives task data from the task database system, receives a request for ranking users under a particular level in a user hierarchy, gathers user activity data from an activity data server, uses a predetermined algorithm calculate a raw score for each user based on the user's activity, normalizes the raw score, and generates a ranking of the users based on their normalized scores. The ranking can be used as an indicator for determining which users need additional training in communicating with outside parties in completing assigned tasks.

Disclosed herein are various embodiments for a data movement and monitoring system. A variety of embodiments operate by determining a move time and a run time associated with a job configured to move a set of data from a table of a first system to one or more tables of a second system. A job deadline is calculated, and it is determined that a job is delayed based on the job deadline being prior to the current time and an absence of the set of data from a status table that indicates which data has been moved from the first system to the second system. A record in the status table is updated to indicate the job is delayed, and a notification that the job is delayed is provided to the one or more accounts.

This disclosure relates generally to system and methods for dynamic scheduling and rescheduling using heterogeneous multi-agent fleet. The embodiments of present disclosure herein address unresolved problem of task allocation using a single solution which is not sufficient for handling various scenarios of multi-agent task allocation problems. For instance, the task allocation becomes more challenging in a scenario where each task has a deadline associated with it and execution time of the tasks cannot be pre-computed as they are dependent on previous tasks. The method of present disclosure provides a scalable solution for dynamic scheduling and rescheduling that handles tasks with multiple pickup and drop locations and dynamic execution time using the agents with heterogeneous speed in a more efficient manner, reducing indirect operating costs and increasing revenue potential while minimizing additional penalty due to run time delays that an agent may encounter.

The present disclosure provides a process execution order determining program and a process execution order determining method for supporting work in determining the execution order of a plurality of processes when designing the plurality of processes to be executed in controlled devices. The process execution order determining program causes a computer to execute a decision process for determining an execution order of a plurality of processes to be executed in controlled devices; and a first determination process for monitoring elements that appear in a connection path formed in the decision process, and determining whether same elements appear in the connection path.

A computer implemented method for managing jobs using job processing pools. A computer system receives a job having a job type. The computer system identifies a job processing pool in the job processing pools for running the jobs of the job type, wherein the job processing pool comprises job processors for running the jobs of the job type and wherein another job processing pool in the job processing pools comprises other job processors for running the jobs of a different job type. The computer system runs the job having the job type using a job processor of the job type in the job processing pool for the job type. According to other illustrative embodiments, a computer system and a computer program product for managing jobs are provided. As a result, the illustrative embodiments can provide a technical effect of increasing the performance in running jobs in a computer system in which wait times for running jobs can be reduced.

A method for integrating infrastructure software functions and automotive applications on an automotive electronic control unit (ECU) device. The ECU device includes a hardware architecture and a software architecture, wherein the hardware architecture includes two or more system-on-chips, at least two of which each comprise two or more processing cores and means to communicate with at least one other system-on-chip. The hardware architecture includes memory and means to communicate with other ECU devices. The software architecture includes one, two, or more virtual machine monitors, each of which executes one, two, or more virtual machines. At least two of said virtual machines each execute an operating system, which executes one, two, or more tasks, and the execution of two or more of the tasks uses the time-triggered paradigm. The tasks are tasks of automotive applications from at least two different automotive domains and are tasks of infrastructure software functions.

Described embodiments provide systems and detecting and predicting virtual CPU resource starvation of a virtual machine. One or more processors can determine, within a time period, a count of a number of delays in occurrences of a timer interrupt scheduled for a virtual processor of a virtual machine executing an application. The one or more processors can compare the count of the number of delays with a threshold established for the time period. The one or more processors can execute a process to migrate the application to a second one or more processors based at least on the comparison of the count of the number of delays with the threshold.

A multi-machine and performance based continuous production planning global optimization scheduling method and device are disclosed. The device for multi-machine and performance-based continuous production planning global optimization scheduling may include a data pre-processing module configured to generate a multi-machine list on performable multiple machines through pre-processing scheduling target data, a scheduling module configured to generate a scheduling result by setting a processing time for a machine related to a single machine list, wherein the single machine list is selected from the multi-machine list, and a data post-processing module configured to store the scheduling result in a database.

An improved real-time operating system (RTOS) design that uses cycle-based scheduling rather than tick-based scheduling is described herein. Using cycle-based scheduling, versus the traditional tick-based scheduling, provides technical benefits to embedded systems. For example, the cycle-based scheduling can change the basic unit of time of the embedded system by increasing the resolution of scheduling. Instead of relying on the system tick used in typical RTOS implementations (e.g., a tick that occurs every 1 millisecond), the improved RTOS design described herein uses CPU cycles internally for some or all operations. Operations such as task delays, timeouts, and/or software timers, which were specified in units of system ticks in typical RTOS implementations, can now be specified in CPU cycles.

The apparatus includes a section extraction module configured to receive an automation scenario including a plurality of sections, and to extract one or more sections of a plurality of job types, from among the plurality of sections, the one or more sections being executable in parallel, a section optimization module configured to generate a parallel execution section list by sorting the one or more sections based on priorities predetermined for the plurality of job types and a job scheduler configured to generate an idle bot list including an idle bot having an idle state between an execution start time and an execution end time of the automation scenario, and to match the idle bot included in the idle bot list to each of the one or more sections included in the parallel execution section list with reference to the at least one expected execution time period and the priorities.