ANALYTICAL MODEL OF RANDOM MULTIPLE ACCESS PROTOCOL PREDICTIVE P-PERSISTENT CSMA
DOI:
https://doi.org/10.15588/1607-3274-2019-1-18Keywords:
protocol model, random multiple access, probabilistic and temporal characteristics, information transmission, industrial network, sensor network, LonWorks, fieldbus, predictive p-persistent CSMA.Abstract
Context. New model and quantification method of probable and time characteristics of information-control network with carrier sense random multiple access protocol and predicting network load of predictive p-persistent CSMA had been created. The object of the research was the process of information exchange in Fieldbus-networks LonWorks, BacNet with the analyzed protocol.
Objective. The aim of the research is to increase the accuracy of quantitative estimates of the characteristics of time and delivery reliability of information messages in the network with the analyzed protocol.
Method. The method of probability theory has been used there to solve the problem of creating a new correct model. The analysis of the functioning principles of the predictive p-persistent CSMA protocol is performed and the parameters influencing its work are set (on the example of the LonTalk stack). A graph of states and transitions of the protocol model describing the principles of
transmission of information messages over a network with a software communication medium, considering the allocated significant network and protocol parameters. A method for calculating the graph is offered and new analytical relations are obtained to estimate the main model probabilistic and temporal characteristic: the average delay time of message transmission, the average load of the communication channel, the probability of successful/unsuccessful transmission and data loss in the network.
Results. The developed model and method of quantitative assessment of probabilistic and temporal characteristics of data transmission in a network with multiple access protocol predictive p-persistent CSMA. The results are mostly differ from analogs by correct accounting of sporadic and diverse network load by the node delivery services.
Conclusions. The held experiments have confirmed the work capacity of the proposed mathematical support and allow to recommend it for solving the assessment characteristics problems of information exchange in the design of analyzed networks with given probabilistic and temporal characteristics.
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