Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

A Hybrid of Adaptation and Dynamic Routing based on SDN for Improving QoE in HTTP Adaptive VBR Video Streaming

Recently, HTTP Adaptive Streaming HAS has received significant attention from both industry and academia based on its ability to enhancing media streaming services over the Internet. Recent research solutions that have tried to improve HAS by adaptation at the client side only may not be completely effective without interacting with routing decisions in the upper layers. In this paper, we address the aforementioned issue by proposing a dynamic bandwidth allocation and management architecture for streaming video flows to improve users satisfaction. We also introduce an initial cross layer hybrid method that combines quality adaptation of variable bitrate video streaming over the HTTP protocol at the client side and SDN based dynamical routing. This scheme is enabled by the Software Defined Networking architecture that is now being considered as an emerging paradigm that disassociates the forwarding process from the routing process. SDN brings flexibility and the ability to flexibly change routing solutions, in turn resulting in dynamically improving the services provided in the application layer. Our experimental results show that the proposed solution offers significantly higher overall bitrates as well as smoother viewing experience than existing methods.Comment: 14 pages, 17 figures, IJCSNS International Journal of Computer Science and Network Security, http://paper.ijcsns.org/07_book/201907/20190708.pd

Using artificial intelligence to support emerging networks management approaches

In emergent networks such as Internet of Things (IoT) and 5G applications, network traffic estimation is of great importance to forecast impacts on resource allocation that can influence the quality of service. Besides, controlling the network delay caused with route selection is still a notable challenge, owing to the high mobility of the devices. To analyse the trade-off between traffic forecasting accuracy and the complexity of artificial intelligence models used in this scenario, this work first evaluates the behavior of several traffic load forecasting models in a resource sharing environment. Moreover, in order to alleviate the routing problem in highly dynamic ad-hoc networks, this work also proposes a machine-learning-based routing scheme to reduce network delay in the high-mobility scenarios of flying ad-hoc networks, entitled Q-FANET. The performance of this new algorithm is compared with other methods using the WSNet simulator. With the obtained complexity analysis and the performed simulations, on one hand the best traffic load forecast model can be chosen, and on the other, the proposed routing solution presents lower delay, higher packet delivery ratio and lower jitter in highly dynamic networks than existing state-of-art methods

New Challenges in Quality of Services Control Architectures in Next Generation Networks

A mesura que Internet i les xarxes IP s'han anat integrant dins la societat i les corporacions, han anat creixent les expectatives de nous serveis convergents així com les expectatives de qualitat en les comunicacions. Les Next Generation Networks (NGN) donen resposta a les noves necessitats i representen el nou paradigma d'Internet a partir de la convergència IP. Un dels aspectes menys desenvolupats de les NGN és el control de la Qualitat del Servei (QoS), especialment crític en les comunicacions multimèdia a través de xarxes heterogènies i/o de diferents operadors. A més a més, les NGN incorporen nativament el protocol IPv6 que, malgrat les deficiències i esgotament d'adreces IPv4, encara no ha tingut l'impuls definitiu.Aquesta tesi està enfocada des d'un punt de vista pràctic. Així doncs, per tal de poder fer recerca sobre xarxes de proves (o testbeds) que suportin IPv6 amb garanties de funcionament, es fa un estudi en profunditat del protocol IPv6, del seu grau d'implementació i dels tests de conformància i interoperabilitat existents que avaluen la qualitat d'aquestes implementacions. A continuació s'avalua la qualitat de cinc sistemes operatius que suporten IPv6 mitjançant un test de conformància i s'implementa el testbed IPv6 bàsic, a partir del qual es farà la recerca, amb la implementació que ofereix més garanties.El QoS Broker és l'aportació principal d'aquesta tesi: un marc integrat que inclou un sistema automatitzat per gestionar el control de la QoS a través de sistemes multi-domini/multi-operador seguint les recomanacions de les NGN. El sistema automatitza els mecanismes associats a la configuració de la QoS dins d'un mateix domini (sistema autònom) mitjançant la gestió basada en polítiques de QoS i automatitza la negociació dinàmica de QoS entre QoS Brokers de diferents dominis, de forma que permet garantir QoS extrem-extrem sense fissures. Aquesta arquitectura es valida sobre un testbed de proves multi-domini que utilitza el mecanisme DiffServ de QoS i suporta IPv6.L'arquitectura definida en les NGN permet gestionar la QoS tant a nivell 3 (IP) com a nivell 2 (Ethernet, WiFi, etc.) de forma que permet gestionar també xarxes PLC. Aquesta tesi proposa una aproximació teòrica per aplicar aquesta arquitectura de control, mitjançant un QoS Broker, a les noves xarxes PLC que s'estan acabant d'estandarditzar, i discuteix les possibilitats d'aplicació sobre les futures xarxes de comunicació de les Smart Grids.Finalment, s'integra en el QoS Broker un mòdul per gestionar l'enginyeria del tràfic optimitzant els dominis mitjançant tècniques de intel·ligència artificial. La validació en simulacions i sobre un testbed amb routers Cisco demostra que els algorismes genètics híbrids són una opció eficaç en aquest camp.En general, les observacions i avenços assolits en aquesta tesi contribueixen a augmentar la comprensió del funcionament de la QoS en les NGN i a preparar aquests sistemes per afrontar problemes del món real de gran complexitat.A medida que Internet y las redes IP se han ido integrando dentro de la sociedad y las corporaciones, han ido creciendo las expectativas de nuevos servicios convergentes así como las expectativas de calidad en las comunicaciones. Las Next Generation Networks (NGN) dan respuesta a las nuevas necesidades y representan el nuevo paradigma de Internet a partir de la convergencia IP. Uno de los aspectos menos desarrollados de las NGN es el control de la Calidad del Servicio (QoS), especialmente crítico en las comunicaciones multimedia a través de redes heterogéneas y/o de diferentes operadores. Además, las NGN incorporan nativamente el protocolo IPv6 que, a pesar de las deficiencias y agotamiento de direcciones IPv4, aún no ha tenido el impulso definitivo.Esta tesis está enfocada desde un punto de vista práctico. Así pues, con tal de poder hacer investigación sobre redes de prueba (o testbeds) que suporten IPv6 con garantías de funcionamiento, se hace un estudio en profundidad del protocolo IPv6, de su grado de implementación y de los tests de conformancia e interoperabilidad existentes que evalúan la calidad de estas implementaciones. A continuación se evalua la calidad de cinco sistemas operativos que soportan IPv6 mediante un test de conformancia y se implementa el testbed IPv6 básico, a partir del cual se realizará la investigación, con la implementación que ofrece más garantías.El QoS Broker es la aportación principal de esta tesis: un marco integrado que incluye un sistema automatitzado para gestionar el control de la QoS a través de sistemas multi-dominio/multi-operador siguiendo las recomendaciones de las NGN. El sistema automatiza los mecanismos asociados a la configuración de la QoS dentro de un mismo dominio (sistema autónomo) mediante la gestión basada en políticas de QoS y automatiza la negociación dinámica de QoS entre QoS brokers de diferentes dominios, de forma que permite garantizar QoS extremo-extremo sin fisuras. Esta arquitectura se valida sobre un testbed de pruebas multi-dominio que utiliza el mecanismo DiffServ de QoS y soporta IPv6. La arquitectura definida en las NGN permite gestionar la QoS tanto a nivel 3 (IP) o como a nivel 2 (Ethernet, WiFi, etc.) de forma que permite gestionar también redes PLC. Esta tesis propone una aproximación teórica para aplicar esta arquitectura de control, mediante un QoS Broker, a las noves redes PLC que se están acabando de estandardizar, y discute las posibilidades de aplicación sobre las futuras redes de comunicación de las Smart Grids.Finalmente, se integra en el QoS Broker un módulo para gestionar la ingeniería del tráfico optimizando los dominios mediante técnicas de inteligencia artificial. La validación en simulaciones y sobre un testbed con routers Cisco demuestra que los algoritmos genéticos híbridos son una opción eficaz en este campo.En general, las observaciones y avances i avances alcanzados en esta tesis contribuyen a augmentar la comprensión del funcionamiento de la QoS en las NGN y en preparar estos sistemas para afrontar problemas del mundo real de gran complejidad.The steady growth of Internet along with the IP networks and their integration into society and corporations has brought with it increased expectations of new converged services as well as greater demands on quality in communications. The Next Generation Networks (NGNs) respond to these new needs and represent the new Internet paradigm from the IP convergence. One of the least developed aspects in the NGNs is the Quality of Service (QoS) control, which is especially critical in the multimedia communication through heterogeneous networks and/or different operators. Furthermore, the NGNs natively incorporate the IPv6 protocol which, despite its shortcomings and the depletion of IPv4 addresses has not been boosted yet.This thesis has been developed with a practical focus. Therefore, with the aim of carrying out research over testbeds supporting the IPv6 with performance guarantees, an in-depth study of the IPv6 protocol development has been conducted and its degree of implementation and the existing conformance and interoperability tests that evaluate these implementations have been studied. Next, the quality of five implementations has been evaluated through a conformance test and the basic IPv6 testbed has been implemented, from which the research will be carried out. The QoS Broker is the main contribution to this thesis: an integrated framework including an automated system for QoS control management through multi-domain/multi-operator systems according to NGN recommendations. The system automates the mechanisms associated to the QoS configuration inside the same domain (autonomous system) through policy-based management and automates the QoS dynamic negotiation between peer QoS Brokers belonging to different domains, so it allows the guarantee of seamless end-to-end QoS. This architecture is validated over a multi-domain testbed which uses the QoS DiffServ mechanism and supports IPv6.The architecture defined in the NGN allows QoS management at level 3 (IP) as well as at level 2 (e.g. Ethernet, WiFi) so it also facilitates the management of PLC networks. Through the use of a QoS Broker, this thesis proposes a theoretical approach for applying this control architecture to the newly standardized PLC networks, and discusses the possibilities of applying it over the future communication networks of the Smart Grids.Finally, a module for managing traffic engineering which optimizes the network domains through artificial intelligence techniques is integrated in the QoS Broker. The validations by simulations and over a Cisco router testbed demonstrate that hybrid genetic algorithms are an effective option in this area.Overall, the advances and key insights provided in this thesis help advance our understanding of QoS functioning in the NGNs and prepare these systems to face increasingly complex problems, which abound in current industrial and scientific applications

QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks

Multimedia networks utilize low-power scalar nodes to modify wakeup cycles of high-performance multimedia nodes, which assists in optimizing the power-to-performance ratios. A wide variety of machine learning models are proposed by researchers to perform this task, and most of them are either highly complex, or showcase low-levels of efficiency when applied to large-scale networks. To overcome these issues, this text proposes design of a Q-learning based iterative sleep-scheduling and fuses these schedules with an efficient hybrid bioinspired multipath routing model for large-scale multimedia network sets. The proposed model initially uses an iterative Q-Learning technique that analyzes energy consumption patterns of nodes, and incrementally modifies their sleep schedules. These sleep schedules are used by scalar nodes to efficiently wakeup multimedia nodes during adhoc communication requests. These communication requests are processed by a combination of Grey Wolf Optimizer (GWO) & Genetic Algorithm (GA) models, which assist in the identification of optimal paths. These paths are estimated via combined analysis of temporal throughput & packet delivery performance, with node-to-node distance & residual energy metrics. The GWO Model uses instantaneous node & network parameters, while the GA Model analyzes temporal metrics in order to identify optimal routing paths. Both these path sets are fused together via the Q-Learning mechanism, which assists in Iterative Adhoc Path Correction (IAPC), thereby improving the energy efficiency, while reducing communication delay via multipath analysis. Due to a fusion of these models, the proposed Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks (QIBMRMN) is able to reduce communication delay by 2.6%, reduce energy consumed during these communications by 14.0%, while improving throughput by 19.6% & packet delivery performance by 8.3% when compared with standard multimedia routing techniques

QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks

Multimedia networks utilize low-power scalar nodes to modify wakeup cycles of high-performance multimedia nodes, which assists in optimizing the power-to-performance ratios. A wide variety of machine learning models are proposed by researchers to perform this task, and most of them are either highly complex, or showcase low-levels of efficiency when applied to large-scale networks. To overcome these issues, this text proposes design of a Q-learning based iterative sleep-scheduling and fuses these schedules with an efficient hybrid bioinspired multipath routing model for large-scale multimedia network sets. The proposed model initially uses an iterative Q-Learning technique that analyzes energy consumption patterns of nodes, and incrementally modifies their sleep schedules. These sleep schedules are used by scalar nodes to efficiently wakeup multimedia nodes during adhoc communication requests. These communication requests are processed by a combination of Grey Wolf Optimizer (GWO) & Genetic Algorithm (GA) models, which assist in the identification of optimal paths. These paths are estimated via combined analysis of temporal throughput & packet delivery performance, with node-to-node distance & residual energy metrics. The GWO Model uses instantaneous node & network parameters, while the GA Model analyzes temporal metrics in order to identify optimal routing paths. Both these path sets are fused together via the Q-Learning mechanism, which assists in Iterative Adhoc Path Correction (IAPC), thereby improving the energy efficiency, while reducing communication delay via multipath analysis. Due to a fusion of these models, the proposed Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks (QIBMRMN) is able to reduce communication delay by 2.6%, reduce energy consumed during these communications by 14.0%, while improving throughput by 19.6% & packet delivery performance by 8.3% when compared with standard multimedia routing techniques

Evolution of High Throughput Satellite Systems: Vision, Requirements, and Key Technologies

High throughput satellites (HTS), with their digital payload technology, are expected to play a key role as enablers of the upcoming 6G networks. HTS are mainly designed to provide higher data rates and capacities. Fueled by technological advancements including beamforming, advanced modulation techniques, reconfigurable phased array technologies, and electronically steerable antennas, HTS have emerged as a fundamental component for future network generation. This paper offers a comprehensive state-of-the-art of HTS systems, with a focus on standardization, patents, channel multiple access techniques, routing, load balancing, and the role of software-defined networking (SDN). In addition, we provide a vision for next-satellite systems that we named as extremely-HTS (EHTS) toward autonomous satellites supported by the main requirements and key technologies expected for these systems. The EHTS system will be designed such that it maximizes spectrum reuse and data rates, and flexibly steers the capacity to satisfy user demand. We introduce a novel architecture for future regenerative payloads while summarizing the challenges imposed by this architecture