Recently proposed wireless mesh routing metrics
based on awareness of congestion, load or interference typically
employ queue occupancy of a node's wireless interface to
estimate traffic load. Queue occupancy, however, does not
directly reflect the impact of channel contention from neighbor
nodes. We propose an alternative called the channel load-aware
(CLAW) routing metric that takes into consideration not only
the traffic load within the node itself, but also the degree of
interference and contention within the channel. CLAW uses
local information from a node's MAC layer to estimate channel
busyness and contention levels. It does not require complex
computations, nor the exchange of link-level statistics with
neighbors. Our preliminary results show that CLAW can
identify congested regions within the network and thus enable
the determination of routes around these congested areas. We
present the results of simulations we conducted to evaluate the
use of CLAW in mesh-wide routing.
Recently proposed wireless mesh routing metrics
based on awareness of congestion, load or interference typically
employ queue occupancy of a node's wireless interface to
estimate traffic load. Queue occupancy, however, does not
directly reflect the impact of channel contention from neighbor
nodes. We propose an alternative called the channel load-aware
(CLAW) routing metric that takes into consideration not only
the traffic load within the node itself, but also the degree of
interference and contention within the channel. CLAW uses
local information from a node's MAC layer to estimate channel
busyness and contention levels. It does not require complex
computations, nor the exchange of link-level statistics with
neighbors. Our preliminary results show that CLAW can
identify congested regions within the network and thus enable
the determination of routes around these congested areas. We
present the results of simulations we conducted to evaluate the
use of CLAW in mesh-wide routing.