514 research outputs found

    CASPR: Judiciously Using the Cloud for Wide-Area Packet Recovery

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    We revisit a classic networking problem -- how to recover from lost packets in the best-effort Internet. We propose CASPR, a system that judiciously leverages the cloud to recover from lost or delayed packets. CASPR supplements and protects best-effort connections by sending a small number of coded packets along the highly reliable but expensive cloud paths. When receivers detect packet loss, they recover packets with the help of the nearby data center, not the sender, thus providing quick and reliable packet recovery for latency-sensitive applications. Using a prototype implementation and its deployment on the public cloud and the PlanetLab testbed, we quantify the benefits of CASPR in providing fast, cost effective packet recovery. Using controlled experiments, we also explore how these benefits translate into improvements up and down the network stack

    Resource Allocation Frameworks for Network-coded Layered Multimedia Multicast Services

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    The explosive growth of content-on-the-move, such as video streaming to mobile devices, has propelled research on multimedia broadcast and multicast schemes. Multi-rate transmission strategies have been proposed as a means of delivering layered services to users experiencing different downlink channel conditions. In this paper, we consider Point-to-Multipoint layered service delivery across a generic cellular system and improve it by applying different random linear network coding approaches. We derive packet error probability expressions and use them as performance metrics in the formulation of resource allocation frameworks. The aim of these frameworks is both the optimization of the transmission scheme and the minimization of the number of broadcast packets on each downlink channel, while offering service guarantees to a predetermined fraction of users. As a case of study, our proposed frameworks are then adapted to the LTE-A standard and the eMBMS technology. We focus on the delivery of a video service based on the H.264/SVC standard and demonstrate the advantages of layered network coding over multi-rate transmission. Furthermore, we establish that the choice of both the network coding technique and resource allocation method play a critical role on the network footprint, and the quality of each received video layer.Comment: IEEE Journal on Selected Areas in Communications - Special Issue on Fundamental Approaches to Network Coding in Wireless Communication Systems. To appea

    S-RLNC based MAC Optimization for Multimedia Data Transmission over LTE/LTE-A Network

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    The high pace emergence in communication systems and associated demands has triggered academia-industries to achieve more efficient solution for Quality of Service (QoS) delivery for which recently introduced Long Term Evolution (LTE) or LTE-Advanced has been found as a promising solution. However, enabling QoS and Quality of Experience (QoE) delivery for multimedia data over LTE has always been a challenging task. QoS demands require reliable data transmission with minimum signalling overheads, computational complexity, minimum latency etc, for which classical Hybrid Automatic Repeat Request (HREQ) based LTE-MAC is not sufficient. To alleviate these issues, in this paper a novel and robust Multiple Generation Mixing (MGM) assisted Systematic Random Linear Network Coding (S-RLNC) model is developed to be used at the top of LTE MAC protocol stack for multimedia data transmission over LTE/LTE-A system. Our proposed model incorporated interleaving and coding approach along with MGM to ensure secure, resource efficient and reliable multiple data delivery over LTE systems. The simulation results reveal that our proposed S-RLNC-MGM based MAC can ensure QoS/QoE delivery over LTE systems for multimedia data communication

    Sleep Period Optimization Model For Layered Video Service Delivery Over eMBMS Networks

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    Long Term Evolution-Advanced (LTE-A) and the evolved Multimedia Broadcast Multicast System (eMBMS) are the most promising technologies for the delivery of highly bandwidth demanding applications. In this paper we propose a green resource allocation strategy for the delivery of layered video streams to users with different propagation conditions. The goal of the proposed model is to minimize the user energy consumption. That goal is achieved by minimizing the time required by each user to receive the broadcast data via an efficient power transmission allocation model. A key point in our system model is that the reliability of layered video communications is ensured by means of the Random Linear Network Coding (RLNC) approach. Analytical results show that the proposed resource allocation model ensures the desired quality of service constraints, while the user energy footprint is significantly reduced.Comment: Proc. of IEEE ICC 2015, Selected Areas in Communications Symposium - Green Communications Track, to appea

    Optimized Network-coded Scalable Video Multicasting over eMBMS Networks

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    Delivery of multicast video services over fourth generation (4G) networks such as 3GPP Long Term Evolution-Advanced (LTE-A) is gaining momentum. In this paper, we address the issue of efficiently multicasting layered video services by defining a novel resource allocation framework that aims to maximize the service coverage whilst keeping the radio resource footprint low. A key point in the proposed system mode is that the reliability of multicast video services is ensured by means of an Unequal Error Protection implementation of the Network Coding (UEP-NC) scheme. In addition, both the communication parameters and the UEP-NC scheme are jointly optimized by the proposed resource allocation framework. Numerical results show that the proposed allocation framework can significantly increase the service coverage when compared to a conventional Multi-rate Transmission (MrT) strategy.Comment: Proc. of IEEE ICC 2015 - Mobile and Wireless Networking Symposium, to appea

    5G Radio Access Networks Enabling Efficient Point-to-Multipoint Transmissions

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    © 2019 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.[EN] The first release of 5th Generation (5G) technology from 3rd Generation Project Partnership (3GPP) Rel'15 has been completed in December 2018. An open issue with this release of standards is that it only supports unicast communications in the core network and Point-To-Point (PTP) transmissions in the Radio Access Network (RAN), and does not support multicast/broadcast communications and Point-To-Multipoint (PTM) transmissions, which are 3GPP system requirements for 5G applications in a number of vertical sectors, such as Automotive, Airborne Communications, Internet-of-Things, Media & Entertainment, and Public Warning & Safety systems. In this article, we present novel mechanisms for enhancing the 5G unicast architecture with minimal footprint, to enable efficient PTM transmissions in the RAN, and to support multicast communications in the Rel'15 core as an in-built delivery optimization feature of the system. This approach will enable completely new levels of network management and delivery cost-efficiency.This work was supported in part by the European Commission under the 5G Infrastructure Public Private Partnership project "5G-Xcast: Broadcast and Multicast Communication Enablers for the Fifth Generation of Wireless Systems" (H2020-ICT-2016-2 call, grant 761498). The views expressed here are those of the authors and do not necessarily represent the project.Säily, M.; Barjau, C.; Navrátil, D.; Prasad, A.; Gomez-Barquero, D.; Tesema, FB. (2019). 5G Radio Access Networks Enabling Efficient Point-to-Multipoint Transmissions. IEEE Vehicular Technology Magazine. 14(4):29-37. https://doi.org/10.1109/MVT.2019.2936657S293714
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