Recent Advances in Smart Communication Protocols and Algorithms

This Special Issue includes the selected papers from the third International Workshop on Smart Communication Protocols & Algorithms (SCPA 2013), that took place in Budapest, Hungary, in June 9, 2013. This Workshop was organized in conjunction with the IEEE International Conference on Communications. This paper explains the work included in the best 6 papers of the workshop.Lloret, J. (2013). Recent Advances in Smart Communication Protocols and Algorithms. Recent Advances in Communications and Networking Technology. 2(2):63-64. doi:10.2174/221508110202131221213711S63642

Test bench to test protocols and algorithms for multimedia delivery

Nowadays, the study of Quality of Service (QoS) in multimedia streaming is generally carried out by simulators. However, the results of these tests are not quite real. This forces researchers to work with approximations. In this paper, we implement a test bench to test the performance and assess the protocols and algorithms for multimedia delivery. This test bench let us evaluate the network parameters performance, by manipulating the devices under controlled conditions, and allow us to identify different application cases. We can confirm that the designed test bench gives us more real measures than a simulators, which allows us to do many types of tests with low cost.Jimenez, JM.; Lloret, J.; Díaz Santos, JR.; Lacuesta Gilaberte, R. (2017). Test bench to test protocols and algorithms for multimedia delivery. En Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Verlag. 124-134. doi:10.1007/978-3-319-49580-4_12S124134Lloret, J., Garcia, M., Atenas, M., Canovas, A.: A QoE management system to improve the IPTV network. Int. J. Commun Syst 24(1), 118–138 (2011)Garcia, M., Canovas, A., Edo, M., Lloret, J.: A QoE management system for ubiquitous IPTV devices. In: The Third International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, UBICOMM 2009, Sliema, Malta, 11–16 October 2009Álvarez, A., Pozueco, L., Cabrero, S., García Pañeda, X., García, R., Melendi, D., Díaz Orueta, G.: Adaptive streaming: a subjective catalog to assess the performance of objective QoE metrics. Netw. Protoc. Algorithms 6(2), 123–136 (2014)Jimenez, J.M., Romero, O., Rego, A., Dilendra, A., Lloret, J.: Study of multimedia delivery over software defined networks. Netw. Protoc. Algorithms 7(4), 37–62 (2015)Recomendation UIT/T G.1010: End-user multimedia QoS categories (2001). https://www.itu.int/rec/T-REC-G.1010-200111-I/enRecomendation UIT‑R M.1079-2: Performance and quality of service requirements for International Mobile Telecommunications-2000 (IMT-2000) access networks. https://www.itu.int/dms_pubrec/itu-r/rec/m/R-REC-M.1079-2-200306-I!!PDF-E.pdfGarcia, M., Lloret, J., Edo, M., Lacuesta, R.: IPTV distribution network access system using WiMAX and WLAN technologies. In: Proceedings of the 4th Edition of the UPGRADE-CN Workshop on Use of P2P GRID and Agents for the Development of Content Networks, Munich, Germany, 11–13 June 2009Atenas, M., Sendra, S., Garcia, M., Lloret, J.: IPTV performance in IEEE 802.11 n WLANs. In: IEEE GLOBECOM Workshops 2010, Miami, USA, pp. 929–933, December 2010Cisco Systems Inc. Cisco’s Visual Networking Index Forecast Projects Nearly Half the World’s Population Will Be Connected to the Internet by 2017. http://newsroom.cisco.com/press-release-content?articleId=1197391Lu, X., Tao, S., El Zarki, M., Guérin, R.: Quality based Adaptive Video Over the Internet. Department of ESE, University of Pennsylvania, Philadelphia, PA 19104 (2003)Lee, T.K., Chai, T.Y., Ngoh, L.H., Shao, X., Teo, J.C.M., Zhou, L.: An IMS-based testbed for real-time services integration and orchestration. In: IEEE Asia-Pacific Services Computing Conference (APSCC 2009), Singapore, 7–11 December 2009Mu, M., Mauthe, A., Casson, J., Tyson, G., Garcia, F.: LA1 TestBed: evaluation testbed to assess the impact of network impairments on video quality. In: 5th International Conference on Testbeds and Research Infrastructures for the Development of Networks & Communities and Workshops (TridentCom 2009), Washington, DC, 6–8 April 2009Kuwadekar, A., Al-Begain, K.: User centric quality of experience testing for video on demand over IMS. In: First International Conference on Computational Intelligence, Communication Systems and Networks (CICSYN 2009), Indore, India, 23–25 July 2009Downline Guide, Big Buck Bunny, Sunflower version. http://bbb3d.renderfarming.net/download.htmlFFmpeg. http://www.ffmpeg.org/about.htmlSullivan, G.J., Wiegand, T.: Video compression - from concepts to the H.264/AVC standard. Proc. IEEE 93(1), 18–31 (2005)Estepa, A.J., Estepa, R., Vozmediano, J., Carrillo, P.: Dynamic VoIP codec selection on smartphones. Netw. Protoc. Algorithms 6(2), 22–37 (2014

MHCP: Multimedia Hybrid Cloud Computing Protocol and Architecture for Mobile Devices

[EN] Multimedia cloud computing has appeared as a very attractive environment for the business world in terms of providing cost-effective services with a minimum of entry costs and infrastructure requirements. There are some architecture proposals in the related literature, but there is no multimedia cloud computing architecture with hybrid features specifically designed for mobile devices. In this article, we propose a new multimedia hybrid cloud computing architecture and protocol. It merges existing private and public clouds and combines IaaS, SaaS and SECaaS cloud computing models in order to find a common platform to deliver real time traffic from heterogeneous multimedia and social networks for mobile users. The developed protocol provides suitable levels of QoS, while providing a secure and trusted cloud environment.Jimenez, JM.; Díaz Santos, JR.; Lloret, J.; Romero Martínez, JO. (2019). MHCP: Multimedia Hybrid Cloud Computing Protocol and Architecture for Mobile Devices. IEEE Network. 33(1):106-112. https://doi.org/10.1109/MNET.2018.1300246S10611233

Deep Learning Model for Multimedia Quality of Experience Prediction Based on Network Flow Packets

[EN] Quality of experience (QoE) is the overall acceptability of an application or service, as perceived subjectively by the end user. In particular, for video quality the QoE is dependent of video transmission parameters. To monitor and control these parameters is critical in modern network management systems, but it would be better to be able to monitor the QoE itself (in terms of both interpretation and accuracy) rather than the parameters on which it depends. In this article we present the first attempt to predict video QoE based on information directly extracted from the network packets using a deep learning model. The QoE detector is based on a binary classifier (good or bad quality) for seven common classes of anomalies when watching videos (blur, ghost, etc.). Our classifier can detect anomalies at the current time instant and predict them at the next immediate instant. This classifier faces two major challenges: first, a highly unbalanced dataset with a low proportion of samples with video anomaly, and second, a small amount of training data, since it must be obtained from individual viewers under a controlled experimental setup. The proposed classifier is based on a combination of a convolutional neural network (CNN), recurrent neural network, and Gaussian process classifier. Image processing, which is the common domain for a CNN, has been expanded to QoE detection. Based on a detailed comparison, the proposed model offers better performance metrics than alternative machine learning algorithms, and can be used as a QoE monitoring function in edge computingThis work has been funded by the Ministerio de Economia y Competitividad del Gobierno de Espana and the Fondo de Desarrollo Regional (FEDER) within the project "Inteligencia distribuida para el control y adaptacion de redes dinamicas definidas por software, Ref: TIN2014-57991-C3-2-P," and also by the Ministerio de Economia y Competitividad in the Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de Conocimiento with the projects "Distribucion inteligente de servicios multimedia utilizando redes cognitivas adaptativas definidas por software, Ref: TIN2014-57991-C3-1-P" and "Red Cognitiva Definida por Software Para Optimizar y Securizar Trafico de Internet de las Cosas con Informacion Critica, Ref TIN2017-84802-C2-1-P."Lopez-Martin, M.; Carro, B.; Lloret, J.; Egea, S.; Sánchez-Esguevillas, A. (2018). Deep Learning Model for Multimedia Quality of Experience Prediction Based on Network Flow Packets. IEEE Communications Magazine. 56(9):110-117. https://doi.org/10.1109/MCOM.2018.170115611011756

Adaptive Video Streaming Testbed Design for Performance Study and Assessment of QoE

[EN] Hypertext Transfer Protocol adaptive streaming switches between different video qualities, adapting to the network conditions, and avoids stalling streamed frames over high¿oscillation client's throughput improving the users' quality of experience (QoE). Quality of experience has become the most important parameter to lead the service providers to know about the end¿user feedback. Implementing Hypertext Transfer Protocol adaptive streaming applications to find out QoE in real¿life scenarios of vast networks becomes more challenging and complex task regarding to cost, agile, time, and decisions. In this paper, a virtualized network testbed to virtualize various machines to support implementing experiments of adaptive video streaming has been developed. Within the test study, the metrics which demonstrate performance of QoE are investigated, respectively, including initial delay (ie, startup delay at the beginning of playback a video), frequency switches (ie, number of times the quality is changed), accumulative video time (ie, number and length of stalls), CPU usage, and battery energy consumption. Furthermore, the relation between effective parameters of QoS on the aforementioned metrics for different segment length is investigated. Experimental results show that the proposed virtualized system is agile, easy to install and use, and costs less than real testbeds. Moreover, the subjective and objective performance studies of QoE evaluation in the system have proven that the segment lengths of 6 to 8 seconds were faired and more efficient than others according to the investigated parameters.Ministerio de Economia y Competitividad, Grant/Award Number: TIN2014-57991-C3-1-PAbdullah, MTA.; Lloret, J.; Ali, A.; García-García, L. (2018). Adaptive Video Streaming Testbed Design for Performance Study and Assessment of QoE. International Journal of Communication Systems. 1-15. https://doi.org/10.1002/dac.3551S11

A Network Coding Based Routing Protocol for Underwater Sensor Networks

Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs). Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR).We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC) comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime

Review to the implementation of IPTV service over wireless and mobiles networks with Quality of Service (QoS)

In the Internet Protocol Television (IPTV) the quality of content delivered to users is affected by different parameters of network performance that must be secured at their minimum values to guarantee the quality perceived by users. The IPTV service deployment on wireless and mobile networks has been facing serious challenges due to limited bandwidth, low reliability and the quality of wireless communication links and user mobility. However, the latest broadband wireless technologies are emerging as suitable networks for the deployment of this service since they are all-IP architectures capabilities to provide end to-end Quality of Service (QoS) and increase the access speed. So, in this paper, we review the work that has been made for the IPTV implementation over wireless and mobile networks with QoS.En IPTV (Internet Protocol Television) la calidad de los contenidos entregados a los usuarios se ve afectada por diferentes parámetros de desempeño de la red que deben ser asegurados en sus valores mínimos para garantizar la calidad percibida por los usuarios. El despliegue del servicio de IPTV sobre redes inalámbricas y móviles ha enfrentado serios desafíos debido a las limitaciones de ancho de banda, a la baja fabilidad y calidad de los enlaces de comunicaciones inalámbricos y a la movilidad de los terminales. Sin embargo, las últimas tecnologías inalámbricas de banda ancha se perflan como redes idóneas para el despliegue de este servicio toda vez que son arquitecturas completamente IP (all-IP) con capacidades de ofrecer Calidad de Servicio (QoS, Quality of Service) de extremo a extremo e incrementan la velocidad de acceso. Por tanto, en este artículo se realiza la revisión de los trabajos que se han realizado para la implementación de la IPTV sobre redes inalámbricas y móviles con QoS

Review to the implementation of IPTV service over wireless and mobiles networks with Quality of Service (QoS)

In the Internet Protocol Television (IPTV) the quality of content delivered to users is affected by different parameters of network performance that must be secured at their minimum values to guarantee the quality perceived by users. The IPTV service deployment on wireless and mobile networks has been facing serious challenges due to limited bandwidth, low reliability and the quality of wireless communication links and user mobility. However, the latest broadband wireless technologies are emerging as suitable networks for the deployment of this service since they are all-IP architectures capabilities to provide end to-end Quality of Service (QoS) and increase the access speed. So, in this paper, we review the work that has been made for the IPTV implementation over wireless and mobile networks with QoS.En IPTV (Internet Protocol Television) la calidad de los contenidos entregados a los usuarios se ve afectada por diferentes parámetros de desempeño de la red que deben ser asegurados en sus valores mínimos para garantizar la calidad percibida por los usuarios. El despliegue del servicio de IPTV sobre redes inalámbricas y móviles ha enfrentado serios desafíos debido a las limitaciones de ancho de banda, a la baja fabilidad y calidad de los enlaces de comunicaciones inalámbricos y a la movilidad de los terminales. Sin embargo, las últimas tecnologías inalámbricas de banda ancha se perflan como redes idóneas para el despliegue de este servicio toda vez que son arquitecturas completamente IP (all-IP) con capacidades de ofrecer Calidad de Servicio (QoS, Quality of Service) de extremo a extremo e incrementan la velocidad de acceso. Por tanto, en este artículo se realiza la revisión de los trabajos que se han realizado para la implementación de la IPTV sobre redes inalámbricas y móviles con QoS