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Earliest deadline first (EDF) or least time to go is a dynamic priority scheduling algorithm used in real-time operating systems to place processes in a priority queue. Whenever a scheduling event occurs (task finishes, new task released, etc.) the queue will be searched for the process closest to its deadline.
Queues may be implemented as a separate data type, or maybe considered a special case of a double-ended queue (deque) and not implemented separately. For example, Perl and Ruby allow pushing and popping an array from both ends, so one can use push and shift functions to enqueue and dequeue a list (or, in reverse, one can use unshift and pop ...
A min-priority queue is an abstract data type that provides 3 basic operations: add_with_priority(), decrease_priority() and extract_min(). As mentioned earlier, using such a data structure can lead to faster computing times than using a basic queue. Notably, Fibonacci heap [19] or Brodal queue offer optimal implementations for those 3 ...
In the code above, the PooledObject has properties for the time it was created, and another, that can be modified by the client, that is reset when the PooledObject is released back to the pool. Shown is the clean-up process, on release of an object, ensuring it is in a valid state before it can be requested from the pool again.
However, the implementation of the leaky bucket as a meter (or token bucket) in a traffic shaping function described above is an exact equivalent to the description of the leaky bucket as a queue: [3] the delay element of the meter version is the bucket of the queue version; the bucket of the meter version is the process that services the queue ...
Fair queuing uses one queue per packet flow and services them in rotation, such that each flow can "obtain an equal fraction of the resources". [1] [2]The advantage over conventional first in first out (FIFO) or priority queuing is that a high-data-rate flow, consisting of large packets or many data packets, cannot take more than its fair share of the link capacity.
Skip lists are also used in distributed applications (where the nodes represent physical computers, and pointers represent network connections) and for implementing highly scalable concurrent priority queues with less lock contention, [17] or even without locking, [18] [19] [20] as well as lock-free concurrent dictionaries. [21]
Python's heapq module implements a binary min-heap on top of a list. Java's library contains a PriorityQueue class, which implements a min-priority-queue as a binary heap. .NET's library contains a PriorityQueue class, which implements an array-backed, quaternary min-heap.