Approximation algorithms for throughput maximization in wireless networks with delay constraints

We study the problem of throughput maximization in multi-hop wireless networks with end-to-end delay constraints for each session. This problem has received much attention starting with the work of Grossglauser and Tse (2002), and it has been shown that there is a significant tradeoff between the end-to-end delays and the total achievable rate. We develop algorithms to compute such tradeoffs with provable performance guarantees for arbitrary instances, with general interference models. Given a target delay-bound Δ(c) for each session c, our algorithm gives a stable flow vector with a total throughput within a factor of O (logΔ_m/log log Δ_m) of the maximum, so that the per-session (end-to-end) delay is O ((logΔ_m/log log Δ_m Δ(c))²), where Δ_m = max_c{Δ(c)}; note that these bounds depend only on the delays, and not on the network size, and this is the first such result, to our knowledge.