Garcia-Saavedra, Andres and Rengarajan, Balaji and Serrano, Pablo and Camps-Mur, Daniel and Costa-Perez, Xavier
(2014)
SOLOR: Self-Optimizing WLANs with
Legacy-Compatible Opportunistic Relays.
IEEE/ACM Transactions on Networking, 23 (5).
pp. 1202-1215.
ISSN 1063-6692
Abstract
Current IEEE 802.11 WLANs suffer from the wellknown
rate anomaly problem, which can drastically reduce
network performance. Opportunistic relaying can address this
problem, but three major considerations, typically considered
separately by prior work, need to be taken into account for
an efficient deployment in real-world systems: 1) relaying could
imply increased power consumption, and nodes might be heterogeneous,
both in power source (e.g., battery-powered vs. socketpowered)
and power consumption profile; 2) similarly, nodes
in the network are expected to have heterogeneous throughput
needs and preferences in terms of the throughput vs. energy
consumption trade-off; and 3) any proposed solution should be
backwards-compatible, given the large number of legacy 802.11
devices already present in existing networks.
In this paper, we propose a novel framework, Self-Optimizing,
Legacy-Compatible Opportunistic Relaying (SOLOR), which
jointly takes into account the above considerations and greatly
improves network performance even in systems comprised mostly
of vanilla nodes and legacy access points. SOLOR jointly optimizes
the topology of the network, i.e., which are the nodes
associated to each relay-capable node; and the relay schedules,
i.e., how the relays split time between the downstream nodes
they relay for and the upstream flow to access points. Our
results, obtained for a large variety of scenarios and different
node preferences, illustrate the significant gains achieved by
our approach. Specifically, SOLOR greatly improves network
throughput performance (more than doubling it) and power
consumption (up to 75% reduction) even in systems comprised
mostly of vanilla nodes and legacy access points. Its feasibility
is demonstrated through test-bed experimentation in a realistic
deployment.
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