MAC Scheduling With Low Overheads by Learning Neighborhood Contention Patterns

Aggregate traffic loads and topology in multi-hop wireless networks may vary slowly, permitting MAC protocols to `learn' how to spatially coordinate and adapt contention patterns. Such an approach could reduce contention, leading to better throughput. To that end we propose a family of MAC scheduling algorithms and its general conditions, if satisfied, ensure latticethroughput-optimality (i.e., achieving any rate-point on a uniform discrete-lattice within the throughput-region). This general framework for lattice-throughput-optimality allows us to design MAC protocols which meets various objectives and conditions. In this paper, as instances of such a lattice-throughput-optimal family, we propose distributed, synchronous contention-based scheduling algorithms under graph and physical interference model that (i) is lattice-throughput-optimal, (ii) does not require node location information, and (iii) has a signaling complexity that does not depend on network size. Thus, it is amena...

• Type: Journal
• Year: 2010
• Where: TON
• Authors: Yung Yi, Gustavo de Veciana, Sanjay Shakkottai
• Keywords: Aggregate Traffic Loads, MAC Protocols, Multi-hop Wireless Networks, TON 2010