Learning automata: an introduction
Learning automata: an introduction
Absorbing stochastic estimator learning automata for S-model stationary environments
Information Sciences—Informatics and Computer Science: An International Journal
Intelligent navigation of autonomous vehicles in an automated highway system: learning methods and interacting vehicles approach
The design and implementation of WiMAX module for ns-2 simulator
WNS2 '06 Proceeding from the 2006 workshop on ns-2: the IP network simulator
An Integrated Uplink Scheduler in IEEE 802.16
EMS '08 Proceedings of the 2008 Second UKSIM European Symposium on Computer Modeling and Simulation
IEEE Transactions on Mobile Computing
ICCEA '10 Proceedings of the 2010 Second International Conference on Computer Engineering and Applications - Volume 02
A QoS Aware Dynamic Scheduling Scheme Using Fuzzy Inference System for IEEE 802.16 Networks
Wireless Personal Communications: An International Journal
Mobile Information Systems
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Worldwide interoperability for microwave access (WiMAX) is one of the most challenging forthcoming technologies providing broadband wireless access (BWA) which promises its users high Quality of Service (QoS) for supporting interactive real-time multimedia services. One of the most important enablers for this is the MAC layer scheduling. For WiMAX, no scheduling algorithm has been standardized and has been left open for the vendors to implement as per their own needs, thereby facilitating the differentiation between their products. Some of the most important metrics for an efficient scheduling algorithm are throughput, delay, jitter (time variation of delay), and packet loss. In this paper, we propose a learning automata (LA)-based scheduling algorithm for WiMAX uplink real-time multimedia interactive traffic in a point to multipoint (PMP) architecture. The main objective of the work presented in the paper is to present the design of an efficient algorithm for providing QoS to real-time uplink traffic. The results of simulation based performance evaluation studies show that the proposed algorithm results in an increase of throughput and decrease in delay and packet loss for real-time service flows as compared to other non-real-time traffic.