In this chapter, we studied the impact of multiple rates, interference, candidate selection and prioritization on the maximum end-to-end throughput of OR. Taking into consideration wireless interference, we proposed a new method of constructing transmission conflict graphs, and present a methodology for computing the end-to-end throughput bounds (capacity) of OR. We formulated the maximum end-to-end throughput problem of OR as a maximum-flow linear programming problem subject to the transmission conflict constraints and effective forwarding rate on each link. To the best of our knowledge, this is the first theoretical work on capacity problem of OR for multihop and multirate wireless networks.
We also proposed two metrics for OR under the multirate scenario. One is expected medium time (EMT) and the other is expected advancement rate (EAR). Based on these metrics, we proposed the distributed and local rate and candidate selection schemes: LMTOR and MGOR, respectively. We validated the analysis results by simulation, and compared the throughput capacity of multirate OR with single-rate ones under different settings, such as different topologies, source–destination distances, number of forwarding candidates and node densities. We showed that OR has great potential to improve the end-to-end throughput under different settings, and our proposed multirate OR schemes achieve higher throughput bound than any single-rate GOR. We observed some insights of OR: 1. The end-to-end capacity gained decreases when the number of forwarding candidates is increased. When the number of forwarding candidates is larger than 3, the end-to-end throughput bound remains almost unchanged. 2. There exists a node density threshold, higher than which 24 mbps GOR performs better than 12 mbps GOR, and lower than which the opposite is the case. The threshold is about 5.5 and 10.9 neighbors per node on 12 mbps for line and square topologies, respectively.