The MetaRing is a Medium Access Control (MAC) protocol for high-speed LANs and MANs. The MetaRing MAC protocol offers its users synchronous, and asynchronous types of services and can operate under two basic access control modes: buffer insertion for variable size packets, and slotted for fixed length packets (i.e., cells). The latter mode of operation is considered in this paper, which only reports performance results of an analysis related to the asynchronous type of service. In this paper we propose and solve a specific worst-case model that enables us to calculate quantiles of the queue length distribution at cell departure time as a function of the offered load, and for three different arrival processes: Poisson, Batch Poisson (B-Poisson), and Batch Markov Modulated Poisson Process (BMMPP). The model proposed is a discrete time discrete state Markov chain of M/G/1-Type, and hence we used a matrix analytic methodology to solve it. Exploitation of the structure of the blocks belonging to the transition probability matrix considerably reduces the computational costs. Our results show that the more realistic the arrival process is, the longer the tail of the queue length distribution.
Performance evaluation of a worst case model of the MetaRing MAC protocol withglobal fairness
ANASTASI, GIUSEPPE;LENZINI, LUCIANO;MEINI, BEATRICE
1997-01-01
Abstract
The MetaRing is a Medium Access Control (MAC) protocol for high-speed LANs and MANs. The MetaRing MAC protocol offers its users synchronous, and asynchronous types of services and can operate under two basic access control modes: buffer insertion for variable size packets, and slotted for fixed length packets (i.e., cells). The latter mode of operation is considered in this paper, which only reports performance results of an analysis related to the asynchronous type of service. In this paper we propose and solve a specific worst-case model that enables us to calculate quantiles of the queue length distribution at cell departure time as a function of the offered load, and for three different arrival processes: Poisson, Batch Poisson (B-Poisson), and Batch Markov Modulated Poisson Process (BMMPP). The model proposed is a discrete time discrete state Markov chain of M/G/1-Type, and hence we used a matrix analytic methodology to solve it. Exploitation of the structure of the blocks belonging to the transition probability matrix considerably reduces the computational costs. Our results show that the more realistic the arrival process is, the longer the tail of the queue length distribution.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
