A traffic distribution scheme for 5G resilient backhauling using integrated satellite networks

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Resilience and high availability are being considered as essential requirements in 5G networks. To fullfil these requirements, the integration of a satellite component within mobile backhaul networks is regarded as a compelling proposition to provide backup connectivity to critical cell sites and divert traffic from congested areas so that a limited capacity in their terrestrial links could be supplemented during peak-time or even replaced in case of total/partial failure or maintenance. Sustained in an architectural framework that enables the integration and management of the satellite capacity as a constituent part of a SDN-based traffic engineered mobile backhaul network, this paper develops and assesses a traffic distribution strategy that exploits the dynamically steerable satellite capacity provisioned for resilience purposes to maximize a network utility function under both failure and non-failure conditions in the terrestrial links.Peer ReviewedPostprint (author's final draft

An Efficient Framework of Congestion Control for Next-Generation Networks

The success of the Internet can partly be attributed to the congestion control algorithm in the Transmission Control Protocol (TCP). However, with the tremendous increase in the diversity of networked systems and applications, TCP performance limitations are becoming increasingly problematic and the need for new transport protocol designs has become increasingly important.Prior research has focused on the design of either end-to-end protocols (e.g., CUBIC) that rely on implicit congestion signals such as loss and/or delay or network-based protocols (e.g., XCP) that use precise per-flow feedback from the network. While the former category of schemes haveperformance limitations, the latter are hard to deploy, can introduce high per-packet overhead, and open up new security challenges. This dissertation explores the middle ground between these designs and makes four contributions. First, we study the interplay between performance and feedback in congestion control protocols. We argue that congestion feedback in the form of aggregate load can provide the richness needed to meet the challenges of next-generation networks and applications. Second, we present the design, analysis, and evaluation of an efficient framework for congestion control called Binary Marking Congestion Control (BMCC). BMCC uses aggregate load feedback to achieve efficient and fair bandwidth allocations on high bandwidth-delaynetworks while minimizing packet loss rates and average queue length. BMCC reduces flow completiontimes by up to 4x over TCP and uses only the existing Explicit Congestion Notification bits.Next, we consider the incremental deployment of BMCC. We study the bandwidth sharing properties of BMCC and TCP over different partial deployment scenarios. We then present algorithms for ensuring safe co-existence of BMCC and TCP on the Internet. Finally, we consider the performance of BMCC over Wireless LANs. We show that the time-varying nature of the capacity of a WLAN can lead to significant performance issues for protocols that require capacity estimates for feedback computation. Using a simple model we characterize the capacity of a WLAN and propose the usage of the average service rate experienced by network layer packets as an estimate for capacity. Through extensive evaluation, we show that the resulting estimates provide good performance

V2X-d: a Vehicular Density Estimation System that combines V2V and V2I Communications

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Road traffic is experiencing a drastic increase, and vehicular traffic congestion is becoming a major problem, especially in metropolitan environments throughout the world. Additionally, in modern Intelligent Transportation Systems (ITS) communications, the high amount of information that can be generated and processed by vehicles will significantly increase message redundancy, channel contention, and message collisions, thus reducing the efficiency of message dissemination processes. In this work, we present a V2X architecture to estimate traffic density on the road that relies on the advantages of combining V2V and V2I communications. Our proposal uses both the number of beacons received per vehicle (V2V) and per RSU (V2I), as well as the roadmap topology features to estimate the vehicle density. By using our approach, modern Intelligent Transportation Systems will be able to reduce traffic congestion and also to adopt more efficient message dissemination protocols.This work was partially supported by the Ministerio de Ciencia e Innovación, Spain, under Grant TIN2011-27543-C03-01, by the Fundación Universitaria Antonio Gargallo and the Obra Social de Ibercaja, under Grant 2013/B010, as well as the Government of Aragón and the European Social Fund (T91 Research Group).Barrachina Villalba, J.; Sangüesa, JA.; Fogue, M.; Garrido, P.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.... (2013). V2X-d: a Vehicular Density Estimation System that combines V2V and V2I Communications. IEEE. https://doi.org/10.1109/WD.2013.6686518

Implementation issues in source coding

An edge preserving image coding scheme which can be operated in both a lossy and a lossless manner was developed. The technique is an extension of the lossless encoding algorithm developed for the Mars observer spectral data. It can also be viewed as a modification of the DPCM algorithm. A packet video simulator was also developed from an existing modified packet network simulator. The coding scheme for this system is a modification of the mixture block coding (MBC) scheme described in the last report. Coding algorithms for packet video were also investigated

Self-Evolving Integrated Vertical Heterogeneous Networks

6G and beyond networks tend towards fully intelligent and adaptive design in order to provide better operational agility in maintaining universal wireless access and supporting a wide range of services and use cases while dealing with network complexity efficiently. Such enhanced network agility will require developing a self-evolving capability in designing both the network architecture and resource management to intelligently utilize resources, reduce operational costs, and achieve the coveted quality of service (QoS). To enable this capability, the necessity of considering an integrated vertical heterogeneous network (VHetNet) architecture appears to be inevitable due to its high inherent agility. Moreover, employing an intelligent framework is another crucial requirement for self-evolving networks to deal with real-time network optimization problems. Hence, in this work, to provide a better insight on network architecture design in support of self-evolving networks, we highlight the merits of integrated VHetNet architecture while proposing an intelligent framework for self-evolving integrated vertical heterogeneous networks (SEI-VHetNets). The impact of the challenges associated with SEI-VHetNet architecture, on network management is also studied considering a generalized network model. Furthermore, the current literature on network management of integrated VHetNets along with the recent advancements in artificial intelligence (AI)/machine learning (ML) solutions are discussed. Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are identified. Finally, the potential future research directions for advancing the autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table

Quality of experience-centric management of adaptive video streaming services : status and challenges

Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming ( HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years