By GCN Staff
Apr 14, 2021
Computer networks and communications systems are increasingly complex, but traditional model-based approaches are still used to manage networks that now span mobile, edge and cloud computing, distributed systems and network stacks along with both wired and wireless systems.
To develop the next generation of high-performance networks, researchers have been relying on machine learning and other data intensive techniques – both of which may require large representative datasets for training and testing the viability of their algorithms and protocols.
In an April 14 Federal Register notice, the National Science Foundation asked the research community what kinds of datasets they need to spur advances in computer and network systems. The request for information seeks input related to data collecting and sharing and leveraging public or private datasets. For example, the NSF’s for Advanced Wireless Research program, which has established urban testbeds for
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