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This is a sub-category of Category:Scheduling algorithms, focusing on heuristic algorithms for scheduling tasks (jobs) to processors (machines). For optimization problems related to scheduling, see Category:Optimal scheduling.
In packet-switched computer networks and other statistical multiplexing, the notion of a scheduling algorithm is used as an alternative to first-come first-served queuing of data packets. The simplest best-effort scheduling algorithms are round-robin, fair queuing (a max-min fair scheduling algorithm), proportional-fair scheduling and maximum ...
The LPT algorithm works as follows: Order the jobs by descending order of their processing-time, such that the job with the longest processing time is first. Schedule each job in this sequence into a machine in which the current load (= total processing-time of scheduled jobs) is smallest. Step 2 of the algorithm is essentially the list ...
Algorithms for scheduling tasks and processes by process schedulers and network packets by network schedulers in computing and communications systems. Subcategories This category has the following 4 subcategories, out of 4 total.
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 ...
List scheduling is a greedy algorithm for Identical-machines scheduling.The input to this algorithm is a list of jobs that should be executed on a set of m machines. The list is ordered in a fixed order, which can be determined e.g. by the priority of executing the jobs, or by their order of arrival.
On the other hand, if a new user starts a process on the system, the scheduler will reapportion the available CPU cycles such that each user gets 20% of the whole (100% / 5 = 20%). Another layer of abstraction allows us to partition users into groups, and apply the fair share algorithm to the groups as well.
The algorithm puts parent processes in the same task group as child processes. [7] (Task groups are tied to sessions created via the setsid() system call. [8]) This solved the problem of slow interactive response times on multi-core and multi-CPU systems when they were performing other tasks that use many CPU-intensive threads in those tasks.