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A very common method in embedded systems is to schedule jobs manually. This can for example be done in a time-multiplexed fashion. Sometimes the kernel is divided in three or more parts: Manual scheduling, preemptive and interrupt level. Exact methods for scheduling jobs are often proprietary. No resource starvation problems
Scheduling is the process of arranging, controlling and optimizing work and workloads in a production process or manufacturing process. Scheduling is used to allocate plant and machinery resources, plan human resources , plan production processes and purchase materials.
A Round Robin preemptive scheduling example with quantum=3. Round-robin (RR) is one of the algorithms employed by process and network schedulers in computing. [1] [2] As the term is generally used, time slices (also known as time quanta) [3] are assigned to each process in equal portions and in circular order, handling all processes without priority (also known as cyclic executive).
The basic form of the problem of scheduling jobs with multiple (M) operations, over M machines, such that all of the first operations must be done on the first machine, all of the second operations on the second, etc., and a single job cannot be performed in parallel, is known as the flow-shop scheduling problem.
Different methods can be applied to testing a scheduling System in a real-time system. Some methods include: input/output verifications and code analysis. One method is by testing each input condition and performing observations of the outputs. Depending on the number of inputs this approach could result in a lot of effort.
Probabilistic planning can be solved with iterative methods such as value iteration and policy iteration, when the state space is sufficiently small. With partial observability, probabilistic planning is similarly solved with iterative methods, but using a representation of the value functions defined for the space of beliefs instead of states.