Mean value analysis

In queueing theory, a discipline within the mathematical theory of probability, mean value analysis (MVA) is a recursive technique for computing expected queue lengths, waiting time at queueing nodes and throughput in equilibrium for a closed separable system of queues. The first approximate techniques were published independently by Schweitzer[1] and Bard,[2][3] followed later by an exact version by Lavenberg and Reiser published in 1980.[4][5]

It is based on the arrival theorem, which states that when one customer in an M-customer closed system arrives at a service facility he/she observes the rest of the system to be in the equilibrium state for a system with M − 1 customers.

  1. ^ Cite error: The named reference Schweitzer was invoked but never defined (see the help page).
  2. ^ Bard, Yonathan (1979). "Some Extensions to Multiclass Queueing Network Analysis". Proceedings of the Third International Symposium on Modelling and Performance Evaluation of Computer Systems: Performance of Computer Systems. North-Holland Publishing Co. pp. 51–62. ISBN 978-0-444-85332-5.
  3. ^ Adan, I.; Wal, J. (2011). "Mean Values Techniques". Queueing Networks. International Series in Operations Research & Management Science. Vol. 154. pp. 561–586. doi:10.1007/978-1-4419-6472-4_13. ISBN 978-1-4419-6471-7.
  4. ^ Reiser, M.; Lavenberg, S. S. (1980). "Mean-Value Analysis of Closed Multichain Queuing Networks". Journal of the ACM. 27 (2): 313. doi:10.1145/322186.322195. S2CID 8694947.
  5. ^ Reiser, M. (2000). "Mean Value Analysis: A Personal Account". Performance Evaluation: Origins and Directions. Lecture Notes in Computer Science. Vol. 1769. pp. 491–504. doi:10.1007/3-540-46506-5_22. ISBN 978-3-540-67193-0.