Open Access
Computation of traffic time series for large populations of IoT devices
(MDPI, 2018) Izal Azcárate, Mikel; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; García-Jiménez, Santiago; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
En este artículo se estudian las tecnicas para clasificar paquetes de tráfico de red en múltiples clases orientadas a la realización de series temporales de tráfico en escenarios de un elevado numero de clases como pueden ser los proveedores de red para dispositivos IoT. Se muestra que usando técnicas basadas en DStries se pueden monitorizar en tiempo real redes con decenas de miles de dispositivos.
Open Access
NATRA: Network ACK-Based Traffic Reduction Algorithm
(IEEE, 2020) García-Jiménez, Santiago; Magaña Lizarrondo, Eduardo; Aracil Rico, Javier; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Traffic monitoring involves packet capturing and processing at a very high rate of packets per second. Typically, flow records are generated from the packet traffic, such as TCP flow records that feature the number of bytes and packets in each direction, flow duration, number of different ports, and other metrics. Delivering such flow records, about network traffic flowing at tens of Gbps is rather challenging in terms of processing power. To address this problem, traffic thinning can be applied to reduce the input load, by swiftly discarding useless packets at the sniffer NIC or driver level, which effectively reduces the load on software layers that handle traffic processing. This work proposes an algorithm that drops empty ACK packets from TCP traffic, thus achieving a significant reduction in the packets per second that must be handled by each traffic module. The tests discussed below show that the algorithm achieves a 25% decrease in the packets per second rate with minimal information loss.
Open Access
TBDClust: time-based density clustering to enable free browsing of sites in pay-per-use mobile Internet providers
(Elsevier, 2017) Torres García, Luis Miguel; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; García-Jiménez, Santiago; Izal Azcárate, Mikel; Automatika eta Konputazioa; Institute of Smart Cities - ISC; Automática y Computación
The World Wide Web has evolved rapidly, incorporating new content types and becoming more dynamic. The contents from a website can be distributed between several servers, and as a consequence, web traffic has become increasingly complex. From a network traffic perspective, it can be difficult to ascertain which websites are being visited by a user, let alone which part of the user's traffic each website is responsible for. In this paper we present a method for identifying the TCP connections involved in the same full webpage download without the need of deep packet inspection. This identification is needed for example to enable free browsing of specific websites in a pay per use mobile Internet access. It could be not only for third party promoted websites but also portals to gubernamental or medical emergency websites. The proposal is based on a modification of the DBSCAN clustering algorithm to work online and over one-dimensional sorted data. In order to validate our results we use both real traffic and packet captures from a controlled environment. The proposal achieves excellent results in consistency (99%) and completeness (92%), meaning that its error margin identifying the webpage downloads is minimal.

García-Jiménez, Santiago

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