47 research outputs found

    A UAV-Based Content Delivery Architecture for Rural Areas and Future Smart Cities

    Full text link
    [EN] Content delivery in vehicular environments can serve multiple purposes, such as safety, entertainment, and news delivery that can be geographically relevant to vehicles traveling within a certain area. The traditional approach to address this problem, based on fixed networking infrastructure, suffers from the following two drawbacks: First, the efficient delivery of large-sized contents to multiple moving receivers simultaneously can be hard to achieve, and second, most of the roads outside the main urban areas lack such fixed infrastructures due to economic reasons. In this paper, we tackle both these issues by proposing rapidly deployable wireless access infrastructures combining RaptorQ-protected content diffusion and unmanned aerial vehicles (UAVs). We performed experiments using actual vehicles and UAVs, and our results showed that RaptorQ-based content dissemination mechanisms is highly efficient when transmitting to multiple moving receivers simultaneously, and UAVs can serve as cheap, effective, and rapidly deployable mobile wireless access elements.Ortiz-Mayordomo, S.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P.; Toh, C. (2019). A UAV-Based Content Delivery Architecture for Rural Areas and Future Smart Cities. IEEE Internet Computing. 23(1):29-36. https://doi.org/10.1109/MIC.2018.2884277S293623

    Network coding meets multimedia: a review

    Get PDF
    While every network node only relays messages in a traditional communication system, the recent network coding (NC) paradigm proposes to implement simple in-network processing with packet combinations in the nodes. NC extends the concept of "encoding" a message beyond source coding (for compression) and channel coding (for protection against errors and losses). It has been shown to increase network throughput compared to traditional networks implementation, to reduce delay and to provide robustness to transmission errors and network dynamics. These features are so appealing for multimedia applications that they have spurred a large research effort towards the development of multimedia-specific NC techniques. This paper reviews the recent work in NC for multimedia applications and focuses on the techniques that fill the gap between NC theory and practical applications. It outlines the benefits of NC and presents the open challenges in this area. The paper initially focuses on multimedia-specific aspects of network coding, in particular delay, in-network error control, and mediaspecific error control. These aspects permit to handle varying network conditions as well as client heterogeneity, which are critical to the design and deployment of multimedia systems. After introducing these general concepts, the paper reviews in detail two applications that lend themselves naturally to NC via the cooperation and broadcast models, namely peer-to-peer multimedia streaming and wireless networkin

    ๋ฌด์„  ํ†ต์‹  ๋„คํŠธ์›Œํฌ ํ™˜๊ฒฝ์—์„œ์˜ ํšจ๊ณผ์ ์ธ ๋น„๋””์˜ค ์ŠคํŠธ๋ฆฌ๋ฐ ๊ธฐ๋ฒ• ์—ฐ๊ตฌ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐ์ •๋ณด๊ณตํ•™๋ถ€, 2013. 8. ์ตœ์„ฑํ˜„.์˜ค๋Š˜๋‚  ๋ฌด์„  ๋„คํŠธ์›Œํฌ ํ†ต์‹  ๊ธฐ์ˆ ์˜ ๋ฐœ๋‹ฌ๋กœ ์ธํ•ด ๊ณ ํ’ˆ์งˆ์˜ ๋น„๋””์˜ค ์ŠคํŠธ๋ฆฌ๋ฐ ์„œ๋น„์Šค์— ๋Œ€ํ•œ ์š”๊ตฌ๊ฐ€ ๊ธ‰์ฆํ•˜๊ณ  ์žˆ๋‹ค. ์ƒˆ๋กœ์šด 60~GHz ๊ด‘๋Œ€์—ญ ๊ณ ์† ๋ฌด์„  ํ†ต์‹  ๊ธฐ์ˆ ์€ ๊ธฐ์กด์˜ ๋ฌด์„  ํ†ต์‹  ๊ธฐ์ˆ ์—์„œ๋Š” ๋ถˆ๊ฐ€๋Šฅํ–ˆ๋˜, ๊ณ ํ’ˆ์งˆ์˜ ๋ฌด์••์ถ• ๋น„๋””์˜ค ์ŠคํŠธ๋ฆฌ๋ฐ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•œ๋‹ค. ์ œํ•œ๋œ ๋ฌด์„  ์ž์› ํ™˜๊ฒฝ์—์„œ ๊ณ ํ’ˆ์งˆ์˜ ๋น„๋””์˜ค ์„œ๋น„์Šค๋ฅผ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•ด ์ฃผ์–ด์ง„ ์ฑ„๋„ ํ™˜๊ฒฝ์—์„œ ์ ์ ˆํ•œ ๋ณ€์กฐ ๋ฐ ์ฝ”๋”ฉ ๊ธฐ์ˆ ์„ ์„ ํƒํ•˜๋Š” ํšจ์œจ์ ์ธ ๋งํฌ ์ ์‘ ๊ธฐ๋ฒ•์ด ํ•„์š”ํ•˜๋‹ค. ๋น„๋””์˜ค ์ŠคํŠธ๋ฆฌ๋ฐ์˜ ํ’ˆ์งˆ์„ ์ˆ˜์น˜๋กœ ํ‰๊ฐ€ํ•˜๋Š” ePSNR์„ ์ •์˜ํ•˜๊ณ , ๋ถˆํ‰๋“ฑ ์˜ค๋ฅ˜ ๋ณดํ˜ธ ๊ธฐ๋ฒ•(UEP)์„ ์ถ”๊ฐ€๋กœ ๋„์ž…ํ•˜์—ฌ ๋ณด๋‹ค ์„ธ๋ฐ€ํ•œ ๋งํฌ ์ ์‘ ๊ธฐ๋ฒ•์„ ๊ฐ€๋Šฅ์ผ€ ํ•œ๋‹ค. ์ •์˜ํ•œ ePSNR์„ ๊ธฐ๋ฐ˜์œผ๋กœ (1) ์ฃผ์–ด์ง„ ๋ฌด์„  ์ž์›์—์„œ ๋น„๋””์˜ค ํ’ˆ์งˆ์„ ์ตœ๋Œ€ํ™”, ํ˜น์€ (2) ๋ชฉํ‘œ ๋น„๋””์˜ค ํ’ˆ์งˆ์„ ๋งŒ์กฑํ•˜๋Š” ๋ฌด์„  ์ž์› ์‚ฌ์šฉ์„ ์ตœ์†Œํ™”, ํ•˜๋Š” ๋‘๊ฐ€์ง€ ๋งํฌ ์ ์‘ ๊ธฐ๋ฒ•๋“ค์„ ์ œ์•ˆํ•œ๋‹ค. ๋‹ค์–‘ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด, ์ •์˜ํ•œ ePSNR์ด ๋น„๋””์˜ค ํ’ˆ์งˆ์„ ์ž˜ ํ‘œํ˜„ํ•˜๊ณ  ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ œ์•ˆํ•œ ๋งํฌ ์ ์‘ ๊ธฐ๋ฒ•๋“ค์ด ๋น„๋””์˜ค ์ŠคํŠธ๋ฆฌ๋ฐ ์„œ๋น„์Šค๋ฅผ ์œ„ํ•œ ์ ์ ˆํ•œ ํ’ˆ์งˆ์„ ์ œ๊ณตํ•˜๋ฉด์„œ, ๋™์‹œ์— ์ž์› ํšจ์œจ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ด์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ํ•œํŽธ, ์ˆœ๋ฐฉํ–ฅ ์˜ค๋ฅ˜ ์ •์ • ๊ธฐ๋ฒ•(FEC)์€ ๋ฌด์„ ๋žœ ํ™˜๊ฒฝ์—์„œ ๊ณ ํ’ˆ์งˆ์˜ ์‹ ๋ขฐ์„ฑ์žˆ๋Š” ๋น„๋””์˜ค ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ๋ฅผ ์ง€์›ํ•œ๋‹ค. ๋ฌด์„ ๋žœ ํ™˜๊ฒฝ์—์„œ ๋ณต์ˆ˜๊ฐœ์˜ ์•ก์„ธ์Šคํฌ์ธํŠธ(AP)๊ฐ„์˜ ์กฐ์ •์„ ํ†ตํ•œ ์‹ ๋ขฐ์„ฑ์žˆ๋Š” ๋น„๋””์˜ค ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๋ณต์ˆ˜๊ฐœ์˜ AP๊ฐ„์˜ ์กฐ์ •์„ ํ†ตํ•ด ๊ฐ๊ฐ์˜ AP๋“ค์ด (1) ์™„์ „ํžˆ ์„œ๋กœ ๋‹ค๋ฅธ, ํ˜น์€ (2) ๋ถ€๋ถ„์ ์œผ๋กœ ์„œ๋กœ ๋‹ค๋ฅธ, ์ธ์ฝ”๋”ฉ๋œ ํŒจํ‚ท๋“ค์„ ์ „์†กํ•˜๊ฒŒ ํ•˜์—ฌ, ๊ณต๊ฐ„ ๋ฐ ์‹œ๊ฐ„์  ๋‹ค์–‘์„ฑ์„ ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ์œ ์ €์—๊ฒŒ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋‹ค. ์ถ”๊ฐ€๋กœ, ์ œํ•œ๋œ ๋ฌด์„  ์ž์›์„ ๋ณด๋‹ค ํšจ์œจ์ ์œผ๋กœ ์‚ฌ์šฉํ•˜๊ธฐ ์œ„ํ•ด, ์ˆœ๋ฐฉํ–ฅ ์˜ค๋ฅ˜ ์ •์ • ๊ธฐ๋ฒ•์˜ ์ฝ”๋”ฉ ๋น„์œจ ์ ์‘ ๊ธฐ๋ฒ•์„ ์œ„ํ•œ ์ž์› ํ• ๋‹น ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. ๋˜ํ•œ, FEC ๋””์ฝ”๋”ฉ ํ›„์˜ ๋น„๋””์˜ค ํŒจํ‚ท์˜ ์ „์†ก์œจ๋ฅผ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋‹ค์–‘ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜๊ณผ ์‹คํ—˜์„ ํ†ตํ•ด ์ œ์•ˆํ•œ ๊ธฐ๋ฒ•๋“ค์˜ ์šฐ์ˆ˜์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ์ „์†ก์€ ๊ธฐ๋ณธ์ ์œผ๋กœ ๋ฌด์„  ์ฑ„๋„ ์˜ค๋ฅ˜๋กœ ์ธํ•ด ์ „์†ก ์‹คํŒจ๊ฐ€ ๋ฐœ์ƒํ•  ๊ฐ€๋Šฅ์„ฑ์„ ๋‚ดํฌํ•œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ธฐ์กด์˜ ๋ฌด์„ ๋žœ ํ‘œ์ค€์—์„œ๋Š” ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ํ™˜๊ฒฝ์—์„œ ์ž๋™ ๋ฐ˜๋ณต ์š”์ฒญ ๊ธฐ๋ฒ•(ARQ)์„ ํ†ตํ•œ ์†์‹ค ์กฐ์ • ๋ฐฉ๋ฒ•์„ ์ œ๊ณตํ•˜์ง€ ์•Š์•˜๋‹ค. ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ์ „์†ก์˜ ๋น„์‹ ๋ขฐ์„ฑ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด, ์ž๋™ ๋ฐ˜๋ณต ์š”์ฒญ ๊ธฐ๋ฒ•(ARQ)๊ณผ ์ˆœ๋ฐฉํ–ฅ ์˜ค๋ฅ˜ ์ •์ • ๊ธฐ๋ฒ•(FEC)๋ฅผ ํ•จ๊ป˜ ๊ณ ๋ คํ•œ ์‹ ๋ขฐ์„ฑ ์žˆ๋Š” ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ์ „์†ก ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์‹ ๋ขฐ์„ฑ ์žˆ๋Š” ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ์ „์†ก์„ ์œ„ํ•œ ํ”ผ๋“œ๋ฐฑ ๊ตํ™˜์˜ ์˜ค๋ฒ„ํ—ค๋“œ๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•œ ๋ณต์ˆ˜๊ฐœ์˜ ํšจ์œจ์ ์ธ ํ”ผ๋“œ๋ฐฑ ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ œ์•ˆํ•œ ํ”ผ๋“œ๋ฐฑ ๊ธฐ๋ฒ•์€ ์•ก์„ธ์Šคํฌ์ธํŠธ(AP)๊ฐ€ ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ์œ ์ €๋“ค์˜ ์†์‹ค๋œ ํŒจํ‚ท๋“ค์˜ ๋ณต์›์„ ์œ„ํ•ด ํ•„์š”ํ•œ ํŒจ๋ฆฌํ‹ฐ(parity) ํŒจํ‚ท์˜ ๊ฐœ์ˆ˜๋ฅผ ์‰ฝ๊ฒŒ ์•Œ ์ˆ˜ ์žˆ๋„๋ก ํ•œ๋‹ค. ํ”ผ๋“œ๋ฐฑ ๊ฐ„์˜ ์ถฉ๋Œ์„ ๊ฐ์•ˆํ•œ ์˜๋„์ ์ธ ๋™์‹œ ์ „์†ก์„ ํ†ตํ•ด ํ”ผ๋“œ๋ฐฑ ์˜ค๋ฒ„ํ—ค๋“œ๋ฅผ ๊ฐ์†Œ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ์ถ”๊ฐ€๋กœ, ํšจ์œจ์ ์ธ ํ”ผ๋“œ๋ฐฑ ํ”„๋กœํ† ์ฝœ์„ ํ™œ์šฉํ•˜์—ฌ, ๋ณ€์กฐ ๋ฐ ์ฝ”๋”ฉ ๊ธฐ๋ฒ•(MCS)์˜ ํ์‡„์  ํ”ผ๋“œ๋ฐฑ ๊ธฐ๋ฐ˜์˜ ๋ฌผ๋ฆฌ ์ „์†ก ์†๋„ ์ ์‘ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์„ฑ๋Šฅ ๊ฒ€์ฆ์„ ํ†ตํ•ด ์ œ์•ˆํ•œ ๊ธฐ๋ฒ•๋“ค์ด ํšจ์œจ์ ์œผ๋กœ ํ”ผ๋“œ๋ฐฑ ์˜ค๋ฒ„ํ—ค๋“œ๋ฅผ ๊ฐ์†Œ์‹œํ‚ค๋ฉฐ, ๋™์‹œ์— ์‹ ๋ขฐ์„ฑ์žˆ๋Š” ๋ฉ€ํ‹ฐ์บ์ŠคํŠธ ์ „์†ก์„ ๋ณด์žฅํ•จ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค.Today, along with the rapid growth of the network performance, the demand for high-quality video streaming services has greatly increased. The emerging 60 GHz multi-Gbps wireless technology enables the streaming of high-quality uncompressed video, which was not possible with other existing wireless technologies. To support such high quality video with limited wireless resources, an efficient link adaptation policy, which selects the proper Modulation and Coding Scheme (MCS) for a given channel environment, is essential. We introduce a new metric, called expected Peak Signal-to-Noise Ratio (ePSNR), to numerically estimate the video streaming quality, and additionally adopt Unequal Error Protection (UEP) schemes that enable flexible link adaptation. Using the ePSNR as a criterion, we propose two link adaptation policies with different objectives. The proposed link adaptation policies attempt to (1) maximize the video quality for given wireless resources, or (2) minimize the required wireless resources while meeting the video quality. Our extensive simulation results demonstrate that the introduced variable, i.e., ePSNR, well represents the level of video quality. It is also shown that the proposed link adaptation policies can enhance the resource efficiency while achieving acceptable quality of the video streaming. Meanwhile, Forward Error Correction (FEC) can be exploited to realize reliable video multicast over Wi-Fi with high video quality. We propose reliable video multicast over Wi-Fi networks with coordinated multiple Access Points (APs) to enhance video quality. By coordinating multiple APs, each AP can transmit (1) entirely different or (2) partially different FEC-encoded packets so that a multicast receiver can benefit from both spatial and time diversities. The proposed scheme can enlarge the satisfactory video multicast region by exploiting the multi-AP diversity, thus serving more multicast receivers located at cell edge with satisfactory video quality. We propose a resource-allocation algorithm for FEC code rate adaptation, utilizing the limited wireless resource more efficiently while enhancing video quality. We also introduce the method for estimating the video packet delivery ratio after FEC decoding. The effectiveness of the proposed schemes is evaluated via extensive simulation and experimentation. The proposed schemes are observed to enhance the ratio of satisfied users by up to 37.1% compared with the conventional single AP multicast scheme. The multicast transmission is inherently unreliable due to the transmission failures caused by wireless channel errors, however, the error control with Automatic Repeat reQuest (ARQ) is not provided for the multicast transmission in legacy IEEE 802.11 standard. To overcome the unreliability of multicast transmission, finally, we propose the reliable multicast protocols considering both ARQ and packet-level FEC together. For the proposed reliable multicast protocol, to reduce the overheads of feedback messages while providing the reliable multicast service, the multiple efficient feedback protocols, i.e., Idle-time-based feedback, Slot-based feedback, Flash-based feedback, and Busy-time-based feedback, are proposed. The proposed feedback protocols let the AP know easily the number of requiring parity frames of the worst user(s) for the recovery of the lost packets. The feedback overheads can be reduced by intending the concurrent transmissions, which makes the collisions, between feedback messages. In addition, utilizing the efficient feedback protocols, we propose the PHY rate adaptation based on the close-loop MCS feedback in multicast transmissions. From the performance evaluations, the proposed protocols can efficiently reduce the feedback overheads, while the reliable multicast transmissions are guaranteed.1 Introduction 1 1.1 Video Streaming over Wireless Networks 1 1.1.1 Uncompressed Video Streaming over 60 GHz band 2 1.1.2 Video Multicast over IEEE 802.11 WLAN 3 1.2 Overview of Existing Approaches 5 1.2.1 Link Adaptation over Wireless Networks 5 1.2.2 Video Streaming over IEEE 802.11 WLAN 6 1.2.3 Reliable Multicast over IEEE 802.11 WLAN 8 1.3 Main Contributions 9 1.4 Organization of the Dissertation 11 2 Link Adaptation for High-Quality Uncompressed Video Streaming in 60 GHz Wireless Networks 12 2.1 Introduction 12 2.2 ECMA-387 and Wireless HDMI 17 2.2.1 ECMA-387 18 2.2.2 Wireless HDMI (HDMI PAL) 21 2.2.3 UEP Operations 22 2.2.4 ACK Transmissions for Video Streaming 23 2.2.5 Latency of Compressed and Uncompressed Video Streaming 24 2.3 ePSNR-Based Link Adaptation Policies 25 2.3.1 ePSNR 28 2.3.2 PSNR-based Link Adaptation 30 2.4 Performance Evaluation 33 2.4.1 Evaluation of ePSNR 34 2.4.2 Performance of Link Adaptation 40 2.5 Summary 45 3 Reliable Video Multicast over Wi-Fi Networks with Coordinated Multiple APs 47 3.1 Introduction 47 3.2 System Environments 50 3.2.1 Time-Slotted Multicast 50 3.2.2 FEC Coding Schemes 52 3.3 Reliable Video Multicast with Coordinated Multiple APs 52 3.3.1 Proposed Video Multicast 52 3.3.2 Video Multicast Procedure 55 3.4 FEC Code Rate Adaptation 58 3.4.1 Estimation of Delivery Ratio 59 3.4.2 Greedy FEC Code Rate Adaptation 61 3.5 Performance Evaluation 63 3.5.1 Raptor Code Performance 64 3.5.2 Simulation Results: No Fading 66 3.5.3 Simulation Results: Fading Channel 69 3.5.4 Simulation Results: Code Rate Adaptation 70 3.5.5 Experimental Results 74 3.5.6 Prototype Implementation 76 3.6 Summary 79 4 Reliable Video Multicast with Efficient Feedback over Wi-Fi 81 4.1 Introduction 81 4.2 Motivation 85 4.3 Proposed Feedback Protocols for Reliable Multicast 87 4.3.1 Idle-time-based Feedback 88 4.3.2 Slot-based Feedback 89 4.3.3 Flash-based Feedback 91 4.3.4 Busy-time-based Feedback 92 4.4 PHY Rate Adaptation in Multicast Transmission 93 4.5 Performance Evaluation 96 4.5.1 Performance evaluation considering feedback error 104 4.6 Summary 109 5 Conclusion and Future Work 110 5.1 Research Contributions 110 5.2 Future Research Directions 111 Abstract (In Korean) 121Docto

    Instantly Decodable Network Coding: From Centralized to Device-to-Device Communications

    Get PDF
    From its introduction to its quindecennial, network coding has built a strong reputation for enhancing packet recovery and achieving maximum information flow in both wired and wireless networks. Traditional studies focused on optimizing the throughput of the system by proposing elaborate schemes able to reach the network capacity. With the shift toward distributed computing on mobile devices, performance and complexity become both critical factors that affect the efficiency of a coding strategy. Instantly decodable network coding presents itself as a new paradigm in network coding that trades off these two aspects. This paper review instantly decodable network coding schemes by identifying, categorizing, and evaluating various algorithms proposed in the literature. The first part of the manuscript investigates the conventional centralized systems, in which all decisions are carried out by a central unit, e.g., a base-station. In particular, two successful approaches known as the strict and generalized instantly decodable network are compared in terms of reliability, performance, complexity, and packet selection methodology. The second part considers the use of instantly decodable codes in a device-to-device communication network, in which devices speed up the recovery of the missing packets by exchanging network coded packets. Although the performance improvements are directly proportional to the computational complexity increases, numerous successful schemes from both the performance and complexity viewpoints are identified

    2013 Doctoral Workshop on Distributed Systems

    Get PDF
    The Doctoral Workshop on Distributed Systems was held at Les Plans-sur-Bex, Switzerland, from June 26-28, 2013. Ph.D. students from the Universities of Neuchรขtel and Bern as well as the University of Applied Sciences of Fribourg presented their current research work and discussed recent research results. This technical report includes the extended abstracts of the talks given during the workshop
    corecore