The Journal of Supercomputing

, Volume 71, Issue 3, pp 871–893 | Cite as

A learning automata-based adaptive uniform fractional guard channel algorithm

  • Hamid Beigy
  • M. R. Meybodi


In this paper, we propose an adaptive call admission algorithm based on learning automata. The proposed algorithm uses a learning automaton to specify the acceptance/rejection of incoming new calls. It is shown that the given adaptive algorithm converges to an equilibrium point which is also optimal for uniform fractional channel policy. To study the performance of the proposed call admission policy, the computer simulations are conducted. The simulation results show that the level of QoS is satisfied by the proposed algorithm and the performance of given algorithm is very close to the performance of uniform fractional guard channel policy which needs to know all parameters of input traffic. The simulation results also confirm the analysis of the steady-state behaviour.


Reinforcement learning Learning automata Uniform fractional guard channel policy Adaptive uniform fractional guard channel policy 



The authors would like to thank the anonymous reviewers for their valuable comments and suggestions which improved the paper.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Computer EngineeringSharif University of TechnologyTehranIran
  2. 2.Department of Computer EngineeringAmirkabir University of TechnologyTehranIran

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