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Optimized Policies for the Retransmission Probabilities in Slotted Aloha

¹ Department of Computer Science and Engineering, National Institute of Technology Durgapur, Durgapur 713 209, India
² Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560 012, India

^* To whom correspondence should be addressed. E-mail: shalabh{at}csa.iisc.ernet.in.

	Abstract

In this paper, we study the behaviour of the slotted Aloha multiple access scheme with a finite number of users under different traffic loads and optimize the retransmission probability q_r for various settings, cost objectives and policies. First, we formulate the problem as a parameter optimization problem and use certain efficient smoothed functional algorithms for finding the optimal retransmission probability parameter. Next, we propose two classes of multi-level closed-loop feedback policies (for finding in each case the retransmission probability q_r that now depends on the current system state) and apply the above algorithms for finding an optimal policy within each class of policies. While one of the policy classes depends on the number of backlogged nodes in the system, the other depends on the number of time slots since the last successful transmission. The latter policies are more realistic as it is difficult to keep track of the number of backlogged nodes at each instant. We investigate the effect of increasing the number of levels in the feedback policies. We also investigate the effects of using different cost functions (with and without penalization) in our algorithms and the corresponding change in the throughput and delay using these. Both of our algorithms use two-timescale stochastic approximation. One of the algorithms uses one simulation while the other uses two simulations of the system. The two-simulation algorithm is seen to perform better than the other algorithm. Optimal multi-level closed-loop policies are seen to perform better than optimal open-loop policies. The performance further improves when more levels are used in the feedback policies.

First published on September 18, 2009
SIMULATION 2009, doi:10.1177/0037549709349324


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