|Title||Designing a Learning-Automata-Based Controller for Client/Server Systems: A Methodology|
|Publication Type||Conference Paper|
|Year of Publication||2000|
Polling policies have been introduced to simplifythe accessing process in client/server systems by acentralized control access scheme. This paper considers aclient/server model which employs a polling policy as itsaccess strategy. We propose a learning-automata-based approachfor polling in order to improve the throughput-delayperformance of the system. Each client has an associatedqueue and the server performs selective polling such thatthe next client to be served is identified by a learning automaton.The learning automaton updates each client’schoice probability according to the feedback information.Under the considered approach, a client’s choice probabilityasymptotically tends to be proportional to the probabilitythat this client is ready. Simulation results have shown thatthe proposed polling policy is beneficial in comparison tothe conventional round-robin polling when operating underbursty traffic conditions. The benefits are significant for thedelay reduction in the considered client/server system.
Designing a Learning-Automata-Based Controller for Client/Server Systems: A Methodology