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Researchers boost efficiency of multi-hop wireless networks

By R&D Editors | April 19, 2012

Multi-hop wireless networks can provide data access for large and
unconventional spaces, but they have long faced significant limits on the
amount of data they can transmit. Now researchers from North Carolina State
University have developed
a more efficient data transmission approach that can boost the amount of data
the networks can transmit by 20% to 80%.

“Our approach increases the average amount of data that can be transmitted
within the network by at least 20% for networks with randomly placed nodes—and
up to 80% if the nodes are positioned in clusters within the network,” says Rudra
Dutta, PhD, an associate professor of computer science at NC State and
co-author of a paper on the research. The approach also makes the network more
energy efficient, which can extend the lifetime of the network if the nodes are
battery powered.

Multi-hop wireless networks use multiple wireless nodes to provide coverage
to a large area by forwarding and receiving data wirelessly between the nodes.
However, these networks have “hot spots”—places in the network where multiple
wireless transmissions can interfere with each other. This limits how quickly
the network can transfer data, because the nodes have to take turns
transmitting data at these congested points.

Data can be transmitted at low power over short distances, which limits the
degree of interference with other nodes. But this approach means that the data
may have to be transmitted through many nodes before reaching its final
destination. Or, data can be transmitted at high power, which means the data
can be sent further and more quickly—but the powerful transmission may
interfere with transmissions from many other nodes.

Dutta and PhD student Parth Pathak developed an approach called centrality-based
power control to address the problem. Their approach uses an algorithm that
instructs each node in the network on how much power to use for each
transmission depending on its final destination.

The algorithm optimizes system efficiency by determining when a powerful
transmission is worth the added signal disruption, and when less powerful
transmissions are needed.

North Carolina State University

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