2010, TON, Engineering Wireless Mesh Networks-- Joint Scheduling, Routing, Power Control, and Rate A.pdf
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2010, TON, Engineering Wireless Mesh Networks-- Joint Scheduling, Routing, Power Control, and Rate A
IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 18, NO. 5, OCTOBER 2010 1387
Engineering Wireless Mesh Networks:
Joint Scheduling, Routing, Power Control,
and Rate Adaptation
Jun Luo, Member, IEEE, Catherine Rosenberg, and André Girard
Abstract—We present a number of significant engineering in-
sights on what makes a good configuration for medium- to large-
size wireless mesh networks (WMNs) when the objective function is
to maximize the minimum throughput among all flows. For this, we
first develop efficient and exact computational tools using column
generation with greedy pricing that allow us to compute exact so-
lutions for networks significantly larger than what has been pos-
sible so far. We also develop very fast approximations that compute
nearly optimal solutions for even larger cases. Finally, we adapt
our tools to the case of proportional fairness and show that the en-
gineering insights are very similar.
Index Terms—Column generation, power control, rate adapta-
tion, routing, scheduling, wireless mesh networks (WMNs).
I. INTRODUCTION
W IRELESS mesh networks (WMNs) such as IEEE802.16 [2] are seen as a promising alternative to other
(wired) broadband access technologies. In order to offer high
throughput, WMNs will have to be tightly managed. Once an
operator has placed his mesh routers and his gateway to offer
appropriate coverage to a set of end-users, he will need to
engineer his WMN to maximize the network performance. This
means choosing among a number of sometimes conflicting op-
tions with complex interactions that can affect performance to
various degrees. The main objective of this paper is to produce
quantitative measures of the impact of these choices on the
performance of networks of realistic sizes.
We examine these issues in the centralized framework devel-
oped in [3], where we assume that the position of the nodes, the
flows, the interference, and propagation models are known at
a central location where the optimal configuration is computed
and
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