Autor segons l'article: Millan P; Molina C; Dimogerontakis E; Navarro L; Meseguer R; Braem B; Blondia C
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: Millán Marco, Pedro
Paraules clau: Time-series analysis End-to-end quality prediction Community networks
Resum: © 2015 IEEE. Community networks are an emergent model with mottos like 'a free net for everyone is possible' or 'don't 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 large scale, 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.
Àrees temàtiques: Electrical and electronic engineering Artificial intelligence
ISSN: 9781467381031
Adreça de correu electrònic de l'autor: pere.millan@urv.cat
Identificador de l'autor: 0000-0002-4132-7099
Data d'alta del registre: 2024-06-22
URL Document de llicència: http://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Proceedings - 2015 International Conference On Future Internet Of Things And Cloud, Ficloud 2015 And 2015 International Conference On Open And Big Data, Obd 2015. 794-799
Referència de l'ítem segons les normes APA: Millan P; Molina C; Dimogerontakis E; Navarro L; Meseguer R; Braem B; Blondia C (2015). Tracking and Predicting End-to-End Quality in Wireless Community Networks.
DOI de l'article: 10.1109/FiCloud.2015.96
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2015
Tipus de publicació: Proceedings Paper
Repositori URV