Greening Big Data Networks: Velocity Impact

The authors investigate the impact of big data's velocity on greening IP over WDM networks. They classify the

processing velocity of big data into two modes: expedited-data and relaxed-data modes. Expedited-data demands higher

amount of computational resources to reduce the execution time compared with the relaxed-data. They developed a mixed

integer linear programming model to progressively process big data at strategic locations, dubbed processing nodes (PNs), built

into the network along the path from the source to the destination. The extracted information from the raw traffic is smaller in

volume compared with the original traffic each time the data is processed, hence, reducing network power consumption. The

results showed that up to 60% network power saving is achieved when nearly 100% of the data required relaxed processing. In

contrast, only 15% of network power saving is gained when nearly 100% of the data required expedited processing. The authors

obtained around 33% power saving in the mixed modes (i.e. when ∼50% of the data is processed in the relaxed mode and 50%

of the data is processed in expedited mode), compared with the classical approach where all the processing is achieved inside

the centralised data centres only.