By dividing a single optical signal from a central Optical Line Terminal (OLT) into multiple outputs for Optical Network Terminals (ONTs) at users' homes, splitters eliminate the need for dedicated fibers to each residence—slashing infrastructure costs while scaling network reach. Bandwidth is shared amongst customers in a PON, and the bandwidth received by a customer is not related to the power received at the optical network terminal (ONT) as long as the power is high enough so the ONT can operate. Federated Learning (FL) is a decentralized machine learning method in which individual devices compute local models based on their data. In FL, devices periodically share newly trained updates with the central server, rather than submitting their raw data. Then related to two categories of bandwidth allocation methods as Static and Dynamic, I make a framework for classifying bandwidth allocation methods in three categories as Fix, Router-Based and Windows-Based. Optical splitters play an important role in FTTH PON networks where a single optical input is split into multiple output, thus allowing a single PON interface to be shared among many subscribers.
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