Tracking and predicting end-to-end quality in wireless community networks
Faculty of Sciences. Mathematics and Computer Science
Publication type
S.l. , [*]
Computer. Automation
Source (book)
FiCloud 2015 : the 3rd International Conference on Future Internet of Things and Cloud, August 24-26, Rome, Italy
Target language
English (eng)
University of Antwerp
Community networks are an emergent model with mottos like a free net for everyone is possible or dont buy the network, be the network. Their social impact is measurable, as the community is provided with the right and opportunity of communication. The combination of wired and wireless links in these networks, and the unreliable nature of the wireless medium, poses several challenges to the routing protocol. End-to- End quality tracking helps the routing layer to select paths that maximize the delivery rate and minimize traffic congestion. We believe that End-to-End quality prediction can be a technique that surpasses End-to-End quality tracking by foreseeing which paths are more likely to change quality. In this work, we focus on End-to-End quality prediction by means of time-series analysis. We apply this prediction technique in the routing layer of largescale, distributed, and decentralized networks. We demonstrate that it is possible to accurately predict End-to-End Quality with an average Mean Absolute Error of just 2.4%. Particularly, we analyze the path properties and path ETX behavior to identify the best prediction algorithm. Moreover, we analyze the EtEQ prediction accuracy some steps ahead in the future and also its dependency of the time of the day.
Full text (open access)