{"title":"Analysis of an asymmetric data network node with priority call flows","authors":"R. Rindzevičius, V. Pilkauskas, K. Gvergzdys","doi":"10.1109/ITI.2005.1491175","DOIUrl":null,"url":null,"abstract":"The analysis of system performance measures is fairly simple if there is only one or several channels with identical service times and arranged in parallel with exponentially distributed inter arrival time of packets and service time. However, heterogeneous multiple channels often occur in practice and here the channels have different service times. It is therefore useful to be able to calculate the performance measures of such systems. We shall take an exact analytical model of the asymmetric data network node and assume that the arrival process is Poisson of two priority flows with different rates and two channels with different service times distributed exponentially and in case with determine service time. In symmetric queuing systems, the response time depends only on whether an arrival message finds some free channel. An asymmetric multiple channel system differs since which of the channels processes the message. It is very important to take analysis of different strategies for selecting a free channel. In a system with heavy traffic there is usually all channels are occupied and therefore a channel selection strategy is not so efficient. The transmission order is from high-priority packet to low-priority packet. Two priority packets queues share a limited size single buffer. The each priority packet is dropped if the queue length exceeds a capacity of buffer. Network node performance measures such as packet losses, packet delay, channel utilization are evaluated by means of analytical and simulation models. Some calculated system performance measures results are presented in figures.","PeriodicalId":392003,"journal":{"name":"27th International Conference on Information Technology Interfaces, 2005.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"27th International Conference on Information Technology Interfaces, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITI.2005.1491175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The analysis of system performance measures is fairly simple if there is only one or several channels with identical service times and arranged in parallel with exponentially distributed inter arrival time of packets and service time. However, heterogeneous multiple channels often occur in practice and here the channels have different service times. It is therefore useful to be able to calculate the performance measures of such systems. We shall take an exact analytical model of the asymmetric data network node and assume that the arrival process is Poisson of two priority flows with different rates and two channels with different service times distributed exponentially and in case with determine service time. In symmetric queuing systems, the response time depends only on whether an arrival message finds some free channel. An asymmetric multiple channel system differs since which of the channels processes the message. It is very important to take analysis of different strategies for selecting a free channel. In a system with heavy traffic there is usually all channels are occupied and therefore a channel selection strategy is not so efficient. The transmission order is from high-priority packet to low-priority packet. Two priority packets queues share a limited size single buffer. The each priority packet is dropped if the queue length exceeds a capacity of buffer. Network node performance measures such as packet losses, packet delay, channel utilization are evaluated by means of analytical and simulation models. Some calculated system performance measures results are presented in figures.