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| M/M/1 대기열: 단일 서버 대기열 모델× | 리틀의 법칙 (L = λW)× | |
|---|---|---|
| 분야 | 경영과학 | 경영과학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1953 | 1961 |
| 창시자≠ | A. K. Erlang; David Kendall (notation) | John D. C. Little |
| 유형≠ | Stochastic queueing model | Exact queueing identity |
| 원전≠ | Kendall, D. G. (1953). Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded Markov chain. The Annals of Mathematical Statistics, 24(3), 338–354. DOI ↗ | Little, J. D. C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383–387. DOI ↗ |
| 별칭 | Single-Server Markovian Queue, Birth-Death Queue, Poisson Queue, M/M/1 Kuyruk Modeli | L = λW Theorem, Little's Theorem, Little's Result, Little Yasası |
| 관련 | 3 | 3 |
| 요약≠ | The M/M/1 queue is the foundational single-server queueing model in which customers arrive according to a Poisson process with rate λ, are served one at a time by a single server with exponentially distributed service times at rate μ, and wait in an infinite-capacity first-come-first-served queue. Formalized within the Kendall notation framework by David Kendall in 1953, building on A. K. Erlang's early twentieth-century telephone traffic work, it yields closed-form steady-state performance measures when the traffic intensity ρ = λ/μ is less than one. | Little's Law is a fundamental theorem in queueing theory that relates the long-run average number of items in a stable system (L) to the long-run average arrival rate (λ) and the long-run average time an item spends in the system (W), expressed as L = λW. Introduced and rigorously proved by John D. C. Little in 1961, the law holds for virtually any stable stochastic system, requiring no assumptions about arrival distributions, service distributions, or queue disciplines. |
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