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    ๋น„๋Œ€์นญ ์ „์†ก์ „๋ ฅ ๊ธฐ๋ฐ˜ ๋ฌด์„  ์„ผ์„œ ์‹œ์Šคํ…œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2016. 2. ๋ฐ•์„ธ์›….๋Œ€๊ทœ๋ชจ ๋งˆ์ผ“์˜ ๊ฐ€๊ฒฉํ‘œ ์—…๋ฐ์ดํŠธ๋Š” ๋‹จ์ˆœํ•˜๊ณ  ๋ฐ˜๋ณต์ ์ธ ์ž‘์—…์ด์ง€๋งŒ, ์—ฌ์ „ํžˆ ๋Œ€๋ถ€๋ถ„์˜ ๋งˆ์ผ“์—์„œ ์ˆ˜๋™์œผ๋กœ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋‹ค. ์ˆ˜๋™ ๊ฐ€๊ฒฉํ‘œ ์—…๋ฐ์ดํŠธ๋Š” ์žฆ์€ ์ง์›๋“ค์˜ ์‹ค์ˆ˜๋กœ ์ธํ•œ ์†Œ๋น„์ž๋“ค์˜ ๋ถˆ๋งŒ๊ณผ ์นด์šดํ„ฐ์˜ ๊ณ„์‚ฐ ์˜ค๋ฅ˜๋ฅผ ์•ผ๊ธฐํ•˜๋ฏ€๋กœ, ์ƒ๊ธฐ ์—…๋ฐ์ดํŠธ ๊ณผ์ •์„ ์ž๋™ํ™”ํ•˜๋ฉด ๋งŽ์€ ์ด์ต์„ ์ฐฝ์ถœํ•  ์ˆ˜ ์žˆ๋‹ค. ํ•œํŽธ, ์ตœ๊ทผ ์ „์ž ์ž‰ํฌ์™€ ๊ฐ™์€ ์ €์ „๋ ฅ ๋””์Šคํ”Œ๋ ˆ์ด ๊ธฐ์ˆ ์ด ๋ฐœ์ „ํ•˜๋ฉด์„œ ์ „์ž ๋ฌด์„  ๊ฐ€๊ฒฉํ‘œ ์—…๋ฐ์ดํŠธ ์„œ๋น„์Šค์˜ ์‹คํ˜„ ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์•„์กŒ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์šฐ๋ฆฌ๋Š” ์ƒ๊ธฐ ์ „์ž ๋ฌด์„  ๊ฐ€๊ฒฉํ‘œ ์—…๋ฐ์ดํŠธ ์„œ๋น„์Šค๋ฅผ ์œ„ํ•œ ๋„คํŠธ์›Œํฌ ์•„ํ‚คํ…์ณ๋ฅผ ์ œ์•ˆํ•˜๊ณ  ํ…Œ์ŠคํŠธํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ๋จผ์ € ์‹ค์ œ ๋งˆ์ผ“์—์„œ์˜ ์˜ˆ๋น„ ์‹คํ—˜๋“ค์„ ํ†ตํ•ด, ํ˜„์กดํ•˜๋Š” ๋„คํŠธ์›Œํฌ ํ”„๋กœํ† ์ฝœ๋“ค์ด ๋ฐ”์œ ๋งˆ์ผ“ ํ™˜๊ฒฝ์—์„œ ๋ฐœ์ƒํ•˜๋Š” ๋…ํŠนํ•œ ๋ฌธ์ œ๋“ค์„ ๊ทน๋ณตํ•˜์ง€ ๋ชปํ•˜๊ณ , ๋‚ฎ์€ ์„ฑ๋Šฅ์„ ๋ณด์ธ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐํžŒ๋‹ค. ์šฐ๋ฆฌ๋Š” ์ƒ๊ธฐ ์‹คํ—˜๋“ค์„ ํ†ตํ•ด ๊ธฐ์ˆ ์ ์ธ ๋„์ „๊ณผ์ œ๋“ค์„ ํ™•์ธํ•˜๊ณ , ์žฅ์• ๋ฌผ๊ณผ ์ธ๊ตฌ๊ฐ€ ๋งŽ์€ ํ™˜๊ฒฝ์—์„œ ํ•˜ํ–ฅ๋งํฌ ์œ„์ฃผ์˜ ํŠธ๋ž˜ํ”ฝ์„ ์ „์†กํ•˜๊ธฐ์— ์ ํ•ฉํ•œ ๋น„๋Œ€์นญ ์ „์†ก ์ „๋ ฅ ๊ธฐ๋ฐ˜ ์‹œ์Šคํ…œ์ธ MarketNet์„ ์ œ์•ˆํ•˜์—ฌ ์ƒ๊ธฐ ๋„์ „๊ณผ์ œ๋“ค์„ ํ•ด๊ฒฐํ•œ๋‹ค. ์šฐ๋ฆฌ๋Š” ํ•˜๋ฃจ์— 5000๋ช… ์ด์ƒ์˜ ์†๋‹˜์ด ๋ฐฉ๋ฌธํ•˜๋Š” ์‹ค๋‚ด ๋งˆ์ผ“ ํ™˜๊ฒฝ์—์„œ MarketNet์˜ ์„ฑ๋Šฅ์„ ํ‰๊ฐ€ํ•œ๋‹ค. ์ƒ๊ธฐ ์„ฑ๋Šฅ ํ‰๊ฐ€์˜ ๊ฒฐ๊ณผ๋“ค์€ MarketNet์ด ํƒ€๊นƒ ํ™˜๊ฒฝ(์žฅ์• ๋ฌผ์ด ๋งŽ๊ณ  ๋ถ๋น„๋Š” ๋งˆ์ผ“)์—์„œ ํƒ€๊นƒ ์‘์šฉ ๋ถ„์•ผ(์ „์ž ๋ฌด์„  ๊ฐ€๊ฒฉํ‘œ ์—…๋ฐ์ดํŠธ)๋ฅผ ์ ์ ˆํžˆ ์ง€์›ํ•  ์ˆ˜ ์žˆ์„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, RPL๊ณผ LPL๊ณผ ๊ฐ™์€ ๊ธฐ์กด ํ”„๋กœํ† ์ฝœ๋“ค๋ณด๋‹ค ํ˜„์ €ํžˆ ๋†’์€ ํŒจํ‚ท ์ „์†ก๋ฅ ๊ณผ ๋‚ฎ์€ ๋“€ํ‹ฐ์‚ฌ์ดํด์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค€๋‹ค.Updating price tags in a large-scale market is a recurrent task, still performed manually in most markets. Given that human-errors can easily lead to customer complaints and accounting inaccuracies, the ability to autonomously reconfigure price tags can be of significant benefit. With the introduction of low-power display techniques such as electronic-ink, applications of enabling electronic, wirelessly reconfigurable price tags show potential for future deployment. In this dissertation, we examine networking architectures that can be applied in such scenarios. Through a series of preliminary pilot studies in an actual supermarket, we show that the performance of existing protocols are not ready to overcome the unique challenges of busy market environments. We identify underlying technical challenges and propose MarketNet, an asymmetric transmission power-based system designed for densely populated, obstacle-rich, downwards traffic-oriented environments. We evaluate MarketNet in a large indoor market visited by 5000+ customers per day. Our results show that MarketNet addresses the challenges of the target application and environment, while achieving higher packet delivery performance with noticeably lower radio duty-cycles than existing protocols such as RPL and LPL.1 Introduction 1 1.1 Motivation 1 1.2 Related Work 4 1.2.1 Wireless Price Tag Update System 4 1.2.2 Wireless Systems Community 5 1.2.3 Wireless Network Community 10 1.3 Contributions and Outline 12 2 Target Application: Wireless and Remote Update of e-Price Tags 17 2.1 Price Representation 17 2.2 Application Scenario 19 2.3 System Requirements 22 3 Preliminary Study in Urban Crowded Markets 25 3.1 Introduction 25 3.2 Wireless Channel Characteristics 27 3.3 Performance of Pre-existing Protocols 38 3.3.1 RPL Operation 38 3.3.2 LPL Operation 42 3.3.3 Performance of RPL over LPL 44 3.4 Summary 48 4 MarketNet 1.0: Asymmetric Transmission Power-based Network 50 4.1 Introduction 50 4.2 Applicability of Asymmetric Transmission Power Networks 54 4.3 MarketNet1.0 System Design 58 4.3.1 Design Overview 58 4.3.2 Neighbor Forwarding over LPL 61 4.4 Mathematical Performance Analysis 66 4.4.1 Packet Reception Ratio 67 4.4.2 Latency 69 4.4.3 Power Consumption 70 4.5 Simulation Results 78 4.5.1 Latency 80 4.5.2 Packet Delivery Ratio 81 4.5.3 Power Consumption 82 4.6 Testbed Experiments 84 4.6.1 Implementation and Environment Setting 84 4.6.2 Downward Traffic Scenario 88 4.6.3 Mixed Traffic Scenario 93 4.7 Market Deployment 98 4.8 Summary 102 5 MarketNet 2.0: Network-wide Superframe Architecture 103 5.1 Introduction 103 5.2 MarketNet2.0 System Design 105 5.2.1 Network-wide Superframe Architecture 107 5.2.2 IPv6 and Routing Layers in MarketNet2.0 112 5.3 System Evaluation 115 5.3.1 Testbed Evaluations 115 5.3.2 Market Deployments 120 5.4 Non-technical but Practical Lessons 126 5.5 Summary 127 6 Conclusion 129 6.1 Research Contributions 129 6.2 Further Research Direction 131 Bibliography 135 ์ดˆ ๋ก 150Docto
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