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In-network Computing to the Rescue of Faulty Links.

NetComputeSIGCOMM(2018)

Cited 35|Views108
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Abstract
Failing network links are usually disabled, and packets are routed around them until the links are repaired. While it is often possible to utilize some of a failing link's capacity, losing what remains of a link's capacity is typically deemed preferable to the erratic effect that unreliable links can have on application-level behavior. We describe a new network function that relies on in-network computing to limit the erratic effect of failing network links, to enable the continued use of those links until they can be repaired. We explore the design space using ns-3, and evaluate our implementation on a physical test-bed that includes programmable switches and reconfigurable hardware. Our current hardware prototype can almost saturate a 10GbE link while using around 10% of our FPGA's resources.
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Key words
Network Architecture,Machine Learning for Networking,Information-Centric Networking
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