Maximal throughput scheduling based on the physical interference model using learning automata

Wireless link scheduling is one of the major challenging issues in multi hop wireless networks when they need to be designed in distributed fashion. In this work we improve the general randomized scheduling method by using learning automata based framework that allows throughput optimal scheduling algorithms could be developed in distributed fashion. We propose a distributed scheduling algorithm that operates on the more realistic conflict graph based on physical interference model. It uses a combination of a distributed learning automata based pick algorithm and an algorithm that compares successive scheduling solutions. The comparison is done by creating spanning tree on the conflict graph of the two consecutive schedules. Briefly we propose a distributed scheduling schemes that (i) is throughput optimal (ii) intelligently choose links for new schedule (iii) message and time complexity is in O(n).