A Distributed Algorithm for Optimal Throughput and Fairness in Wireless Networks with a General Interference Model

In multi-hop wireless networks, earlier research on joint scheduling and congestion control has suggested that MAClayer scheduling is the bottleneck. Distributed scheduling for maximal throughput is difficult since the conflicting relationship between different links is complex. Existing works on maximalthroughput scheduling usually assumes synchronized time slots, and in each slot, a maximal-weighted “independent set” needs to be found or approximated. However, this is hard to implement in distributed networks. On the other hand, a distributed greedy protocol similar to IEEE 802.11 can only achieve a fraction of the throughput region. In this paper, we introduce an adaptive CSMA algorithm, which can achieve the maximal throughput distributedly under some assumptions. The intuitive idea is that each link should adjust its aggressiveness of transmission based on its backlog. Furthermore, we combine the algorithm with endto-end flow control to achieve fairness among competing flows. The effectiveness of the algorithm is verified by simulations. We show that the proposed CSMA scheduling is a modular MAClayer algorithm and demonstrate its combination with optimal routing and optimal channel selection. Finally, we considered some implementation issues in the setting of 802.11 networks.