Autor segons l'article: Millan, Pere Aliagas, Caries Molina, Carlos Dimogerontakis, Emmanouil Meseguer, Roc
Departament: Enginyeria Informàtica i Matemàtiques
e-ISSN: 2079-9292
Autor/s de la URV: Aliagas Castell, Carlos / Millán Marco, Pedro / Molina Clemente, Carlos María
Paraules clau: Time-series analysis End-to-end quality prediction Community networks
Resum: Community Networks have been around us for decades being initially deployed in the USA and Europe. They were designed by individuals to provide open and free “do it yourself” Internet access to other individuals in the same community and geographic area. In recent years, they have evolved as a viable solution to provide Internet access in developing countries and rural areas. Their social impact is measurable, as the community is provided with the right and opportunity of communication. Community networks combine wired and wireless links, and the nature of the wireless medium is unreliable. This poses several challenges to the routing protocol. For instance, Link-State routing protocols deal with End-to-End Quality tracking to select paths that maximize the delivery rate and minimize traffic congestion. In this work, we focused on End-to-End Quality prediction by means of time-series analysis to foresee which paths are more likely to change their quality. We show that it is possible to accurately predict End-to-End Quality with a small Mean Absolute Error in the routing layer of large-scale, distributed, and decentralized networks. In particular, we analyzed the path ETX behavior and properties to better identify the best prediction algorithm. We also analyzed the End-to-End Quality prediction accuracy some steps ahead in the future, as well as its dependency on the hour of the day. Besides, we quantified the computational cost of the prediction. Finally, we evaluated the impact of the usage for routing of our approach versus a simplified OLSR (ETX + Dijkstra) on an overloaded network.
Àrees temàtiques: Signal processing Physics, applied Hardware and architecture Engineering, electrical & electronic Engenharias iv Electrical and electronic engineering Control and systems engineering Computer science, information systems Computer networks and communications
Accès a la llicència d'ús: thttps://creativecommons.org/licenses/by/3.0/es/
ISSN: 08834989
Adreça de correu electrònic de l'autor: carles.aliagas@urv.cat carles.aliagas@urv.cat pere.millan@urv.cat carlos.molina@urv.cat
Identificador de l'autor: 0000-0002-4132-7099 0000-0003-1955-0128
Data d'alta del registre: 2024-06-22
Volum de revista: 8
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://www.mdpi.com/2079-9292/8/5/578
URL Document de llicència: http://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Electronics. 8 (5): 578-
Referència de l'ítem segons les normes APA: Millan, Pere Aliagas, Caries Molina, Carlos Dimogerontakis, Emmanouil Meseguer, Roc (2019). Time Series Analysis to Predict End-to-End Quality of Wireless Community Networks. Electronics, 8(5), 578-. DOI: 10.3390/electronics8050578
DOI de l'article: 10.3390/electronics8050578
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2019
Tipus de publicació: Journal Publications
Repositori URV