Definition
Little’s Law says that in the long-term, steady state of a production system, the average number of items L in the system is the product of the average arrival rate λ and the average time W that an item spends in the system, that is,
Discussion
At first glance, Little’s Law looks like common sense. If items arrive faster than the system can process them, the system will overflow. Perhaps the earliest mention of the relation is by A. Cobham in 1954, and he states it as a fact without proof [2]. However, the law is insightful in two ways. First, it does not depend on the probability distributions of any of the variables. Second, since arrival rates are generally less than maximum processing rates, it says what the capacity of the system must be to handle the queue in a system design.
Figure 1 shows a visualization of a queue in steady state that explains Little’s Law:
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Bibliography
Bailey DH (1997) Little’s law and high performance computing. RNR Technical Report, NAS applications and tools group, NASA Ames Research Center. At http://crd.lbl.gov/~dhbailey/dhbpapers/little.pdf
Cobham A (1954) Priority assignment in waiting line problems Oper Res 2(1):70–76
Jewell WS (1967) A simple proof of L = λW. Oper Res 15(6): 1109–1116
Little JDC (1961) A proof of the queueing formula L = λW. Oper Res 9:383–387
Little JDC, Graves SC (2008) Little’s law. In: Chhajed D, Lowe TJ (eds) Building intuition: insights from basic operations management models and principles. MIT Press, Cambridge. Available at http://web.mit.edu/sgraves/www/papers/Little's Law-Published.pdf
Morse PM (1958) Queues, inventories and maintenance: the analysis of operational systems. Original edition by Wiley, New York. ISBN 0-86-3914-. Reprinted by Dover Phoenix Editions, 2004
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Gustafson, J.L. (2011). Little’s Law. In: Padua, D. (eds) Encyclopedia of Parallel Computing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09766-4_79
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