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Optical functionality is being used to realize new data center architectures that minimize electronic switching overheads, pushing the processing to the edge of the network. A challenge in optically interconnected data center networks is to identify the large, bandwidthhungry flows (i.e., elephants) and efficiently establish the optical circuits. Moreover, the amount of optical resources to be provisioned...
We optimize flow placement for a hybrid network implementing an adaptive neural network classifier. We predict elephant flows with high accuracy on anonymized university network traffic. We also demonstrate the capability to perform highly complex actions at 40 Gbps using less than 5% of co-processor capacity. This shows that it is possible to implement intelligent actions such as a neural network...
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