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Optimal job scheduling is a class of optimization problems related to scheduling. The inputs to such problems are a list of jobs (also called processes or tasks) and a list of machines (also called processors or workers). The required output is a schedule – an assignment of jobs to machines. The schedule should optimize a certain objective ...
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.
That is, EDF can guarantee that all deadlines are met provided that the total CPU utilization is not more than 100%. Compared to fixed-priority scheduling techniques like rate-monotonic scheduling, EDF can guarantee all the deadlines in the system at higher loading. Note that use the schedulability test formula under deadline as period.
Problems involving weighted interval scheduling are equivalent to finding a maximum-weight independent set in an interval graph. Such problems can be solved in polynomial time. [3] Assuming the vectors are sorted from earliest to latest finish time, the following pseudocode determines the maximum weight of a single-interval schedule in Θ(n) time:
Conceptually, it repeatedly selects a source of the dependency graph, appends it to the current instruction schedule and removes it from the graph. This may cause other vertices to be sources, which will then also be considered for scheduling. The algorithm terminates if the graph is empty. To arrive at a good schedule, stalls should be prevented.
Step 2 of the algorithm is essentially the list-scheduling (LS) algorithm. The difference is that LS loops over the jobs in an arbitrary order, while LPT pre-orders them by descending processing time. LPT was first analyzed by Ronald Graham in the 1960s in the context of the identical-machines scheduling problem. [1]
Identical-machines scheduling is an optimization problem in computer science and operations research. We are given n jobs J 1 , J 2 , ..., J n of varying processing times, which need to be scheduled on m identical machines, such that a certain objective function is optimized, for example, the makespan is minimized.
The scheduler is an operating system module that selects the next jobs to be admitted into the system and the next process to run. Operating systems may feature up to three distinct scheduler types: a long-term scheduler (also known as an admission scheduler or high-level scheduler), a mid-term or medium-term scheduler, and a short-term scheduler.