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On trade-off between computational efficiency and prediction accuracy in bandwidth traffic estimation
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Journal Article
On trade-off between computational efficiency and prediction accuracy in bandwidth traffic estimation
2014
Overview
The increasing demand for wireless broadband services poses the need for efficient utilisation of the backhaul network resources. To this end, schemes that use artificial neural networks in order to predict the forthcoming network traffic demand and proactively request the commitment of the necessary resources have been proposed. However, an up-to-date prediction model, required by these schemes, necessitates a regularly held training process, which incurs a high computational cost. This reported work investigates the trade-off between prediction accuracy and computational efficiency by employing evolutionary game theory and a novel scheme is proposed that can achieve both the aspects.
Publisher
The Institution of Engineering and Technology,Institution of Engineering and Technology,John Wiley & Sons, Inc
Subject
/ bandwidth traffic estimation
/ Computer science; control theory; systems
/ Computer systems and distributed systems. User interface
/ Connectionism. Neural networks
/ Demand
/ Exact sciences and technology
/ Information and communications
/ Networks
/ Software
/ Systems, networks and services of telecommunications
