Learning from Experience: Efficient Decentralized Scheduling for 60GHz Mesh Networks
Published in IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2016
Recommended citation: Gek Hong Sim, Rui Li, Cristina Cano, David Malone, Paul Patras, and Joerg Widmer (2016). " Learning from Experience: Efficient Decentralized Scheduling for 60GHz Mesh Networks." 2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), Coimbra, pp. 1-9 . doi: 10.1109/WoWMoM.2016.7523520 https://ieeexplore.ieee.org/abstract/document/7523520
Abstract: Due to the directionality of transmissions in millimeter wave (mm-wave) networks, wireless stations are usually unable to overhear when other stations access the channel. This makes it hard to design efficient distributed beam coordination and scheduling mechanisms. At the same time, centralized schemes only perform well in relatively simple, static scenarios. In practical settings where links have different channel qualities and in the context of relaying or in-band backhauling, centrally coordinating all stations becomes difficult. In this paper, we propose a low complexity, decentralized, learning-based scheduling algorithm for mm-wave networks that handles heterogeneous link rates and packet sizes efficiently. Compared to state-of-the-art slotted channel access for mm-wave networks, the proposed mechanism achieves throughput gains of up to a factor of 8 in single-hop scenarios and end-to-end throughput improvements of up to a factor of 1.6 in multi-hop topologies.