Analysis of Mean Access Delay in Variable-Window CSM

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Networked sensor/control systems are crucial for industrial automation and monitoring.
• LonWorks/EIA-709 technology is widely used in these systems, necessitating performance analysis.
• Understanding channel load impact on access delay is vital for system reliability.

Purpose of the Study:

• To investigate the mean access delay characteristics in LonWorks/EIA-709 systems concerning channel load.
• To develop and validate a predictive model for network performance under various operational conditions.
• To provide insights into the trade-offs between network load and communication latency.

Main Methods:

• System modeling focused on the Media Access Control (MAC) protocol and Transaction Control Sublayer.
• Application of an analytical approach utilizing Markov chains for stochastic analysis.
• Numerical computation of transition probabilities, successful transmission, and collision probabilities.
• Simulative validation of the developed analytical model.

Main Results:

• The study successfully computed probabilities of successful transmission and collision based on the Markov chain model.
• Numerical results for mean access delay were obtained under specific load scenarios (acknowledged, unicast transactions, collision detection enabled).
• The analytical model's predictions were validated through simulations, confirming its accuracy.

Conclusions:

• The developed Markov chain model accurately predicts mean access delay in LonWorks/EIA-709 systems under varying channel loads.
• The findings offer valuable insights for optimizing network performance and ensuring reliable data transmission.
• This research contributes to the understanding of MAC protocol behavior in industrial control networks.