25 research outputs found

    (An) RSVP extensionfor Multi-Path routing Networks

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    Maste

    Neighbor Discovery Schemes for Multichannel Wireless Networks and Opportunistic Networks

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    Doctor์ตœ๊ทผ์—, ๊ธฐํšŒ ๋„คํŠธ์›Œํฌ (opportunistic network)๋‚˜ ์ธ์ง€ ๋„คํŠธ์›Œํฌ (cognitive network)์™€ ๊ฐ™์€ ์ƒˆ๋กœ์šด ์œ ํ˜•์˜ ์ด๋™ ์• ๋“œํ˜น ๋„คํŠธ์›Œํฌ (mobile ad hoc network) ๊ฐ€ ๋งŽ์€ ๊ด€์‹ฌ์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ๊ตฐ์‚ฌ, ์ฐจ๋Ÿ‰, ์˜๋ฃŒ, ๋ฉ€ํ‹ฐ๋ฏธ๋””์–ด ์ „์†ก ๋“ฑ ๋‹ค์–‘ํ•œ ์„œ๋น„์Šค์— ์‘์šฉ๋  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋„คํŠธ์›Œํฌ๋Š” ์ผ๋ฐ˜์ ์œผ๋กœ ๊ธฐ๊ฐ„ ํ†ต์‹ ์—†์ด ์ž๊ฐ€ ๊ตฌ์„ฑ (self-configuration) ์„ ํ•  ์ˆ˜ ์žˆ์–ด์•ผ ํ•œ๋‹ค. ์ด ์ž๊ฐ€ ๊ตฌ์„ฑ์˜ ์ œ์ผ ์ฒซ๋ฒˆ์งธ ๋‹จ๊ณ„๊ฐ€ ์ด์›ƒ ํƒ์ƒ‰์ด๋‹ค. ์ „์†ก๊ฑฐ๋ฆฌ ๋‚ด์— ์žˆ๋Š” ๋‘ ๋…ธ๋“œ๋“ค์€ ๋ฐ์ดํƒ€๋ฅผ ๊ตํ™˜ํ•˜๊ธฐ ์ „์—, ์„œ๋กœ๋ฅผ ์ธ์‹ํ•˜๊ณ  ์—ฐ๊ฒฐ์„ ์„ค์ •ํ•ด์•ผ ํ•œ๋‹ค. ๋งŒ์•ฝ ์„œ๋กœ๋ฅผ ์ธ์‹ํ•˜์ง€ ๋ชปํ•œ๋‹ค๋ฉด, ํ†ต์‹  ๊ธฐํšŒ๋ฅผ ๋†“์น˜๊ฒŒ ๋˜๊ณ , ์ „์†ก ์ง€์—ฐ์ด ๊ธธ์–ด์ ธ ๊ฒฐ๊ตญ ๋ฐ์ดํƒ€ ์ „์†ก์„ ํ•˜์ง€ ๋ชปํ•˜๊ฒŒ ๋œ๋‹ค. ์ด์›ƒ ํƒ์ƒ‰ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ฐพ๋Š” ๊ฒƒ์€ ๋…ธ๋“œ๋“ค์ด ์„œ๋กœ ์–ธ์ œ ์–ผ๋งˆ๋‚˜ ์˜ค๋žซ๋™์•ˆ ๋งŒ๋‚ ์ง€ ๋ชจ๋ฅด๊ธฐ ๋•Œ๋ฌธ์— ์ƒ๋‹นํžˆ ์–ด๋ ค์šด ๋ฌธ์ œ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ถ„์‚ฐ์  (distributed)์ด๊ณ  ๊ฒฐ์ •์ ์ธ (deterministic) ๋ฐฉ์‹์œผ๋กœ ์ด์›ƒ ๋…ธ๋“œ๋ฅผ ํƒ์ƒ‰ํ•˜๋Š” ๋ฌธ์ œ๋ฅผ ๋‹ค๋ฃจ๊ณ ์ž ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ์ฒซ ๋ฒˆ์งธ ์ฃผ์ œ์—์„œ๋Š”, ๋‹ค์ค‘ ์ฑ„๋„ ์•ก์„ธ์Šค ๋„คํŠธ์›Œํฌ์—์„œ ์ฑ„๋„ ๋Ÿ‰๋ฐ๋ทฐ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๋…ธ๋“œ๋“ค์€ ๋ฐ์ดํ„ฐ ์ „์†ก์„ ์‹œ์ž‘ํ•˜๊ธฐ ์ „์— ํ•˜๋‚˜์˜ ๊ณตํ†ต๋œ ์ฑ„๋„์—์„œ ๋งํฌ๋ฅผ ์„ค์ •ํ•ด์•ผ ํ•œ๋‹ค. ๊ทธ๋Ÿฐ ๊ณตํ†ต์˜ ์ฑ„๋„์„ ์ฐพ๋Š” ๋ฐฉ๋ฒ•์€ ์ค‘์•™ ์ฒ˜๋ฆฌ ๋˜๋Š” ๋ถ„์‚ฐ ์ฒ˜๋ฆฌ ๋ฐฉ์‹์œผ๋กœ ์ด๋ฃจ์–ด ์งˆ ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ณ„๋„์˜ ์ œ์–ด ์ฑ„๋„ ์—†์ด ์™„์ „ ๋ถ„์‚ฐ ์ฒ˜๋ฆฌ (fully distributed) ๋ฐฉ์‹์œผ๋กœ ์ด๋ฃจ์–ด์ง€๋Š” ์ฑ„๋„ ๋ž‘๋ฐ๋ทฐ ๋ฌธ์ œ์— ๋Œ€ํ•ด ์ดˆ์ ์„ ๋งž์ถ˜๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ์‹์€ ๋‘๊ฐœ์˜ ๋…ธ๋“œ๋“ค์ด 2N+1 ์Šฌ๋กฏ ๋‚ด์— ๋ž‘๋ฐ๋ทฐํ•  ๊ฐ€์šฉ ์ฑ„๋„์„ ๋ฐฉ๋ฌธํ•˜๋Š” ์ˆœ์„œ๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ์—ฌ๊ธฐ์„œ N์€ ์ฑ„๋„์˜ ์ˆ˜์ด๊ณ  ์Šฌ๋กฏ์€ ๊ณตํ†ต ์ฑ„๋„์—์„œ ๋‘ ๋…ธ๋“œ๊ฐ€ ๋งํฌ๋ฅผ ์„ค์ •ํ•˜๋Š”๋ฐ ํ•„์š”ํ•œ ์ตœ์†Œ์˜ ์‹œ๊ฐ„ ๊ฐ„๊ฒฉ์„ ๋‚˜ํƒ€๋‚ธ๋‹ค. ์ง€๊ธˆ๊นŒ์ง€ ์•Œ๋ ค์ง„ ๊ฐ€์žฅ ์ข‹์€ ๋ฐฉ์‹์œผ๋กœ๋Š” N^2+N-1 ์Šฌ๋กฏ ๋‚ด์— ๋ž‘๋ฐ๋ทฐํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ์Šฌ๋กฏ์˜ ๋™๊ธฐํ™” ์—†์ด๋„ ๊ตฌํ˜„๊ฐ€๋Šฅํ•˜๋‹ค๋Š” ๊ฒƒ์„ ์ฆ๋ช…ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ๋‘ ๋ฒˆ์งธ ์ฃผ์ œ์—์„œ๋Š”, ๊ธฐํšŒ ๋„คํŠธ์›Œํฌ์—์„œ ์ตœ์ ์˜ ์—๋„ˆ์ง€ ํšจ์œจ์ ์ธ ์ด์›ƒ ํƒ์ƒ‰ ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ๊ธฐํšŒ ๋„คํŠธ์›Œํฌ๋Š” ์ด๋™ ์• ๋“œํ˜น ๋„คํŠธ์›Œํฌ๊ฐ€ ๊ฐ€์žฅ ํฅ๋ฏธ๋กญ๊ฒŒ ์ง„ํ™”๋œ ํ˜•ํƒœ์ด๋‹ค. ์‹ค์ œ ์ด๋™ ์• ๋“œํ˜น ๋„คํŠธ์›Œํฌ์—์„œ๋Š” ๋…ธ๋“œ์˜ ์งง์€ ์ „์†ก๊ฑฐ๋ฆฌ์™€ ์‚ฌ์šฉ์ž์˜ ๋น ๋ฅธ ์ด๋™์œผ๋กœ ์ธํ•˜์—ฌ ๋นˆ๋ฒˆํ•˜๊ฒŒ ์—ฐ๊ฒฐ์ด ๋Š๊ธด๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ, ์ „์ฒด ๋„คํŠธ์›Œํฌ๋Š” ์—ฐ๊ฒฐ๋˜์–ด ์žˆ๊ณ  ๋…ธ๋“œ๋“ค ์‚ฌ์ด์—๋Š” ๋‹จ๋Œ€๋‹จ (end-to-end) ๊ฒฝ๋กœ๊ฐ€ ์กด์žฌํ•œ๋‹ค๊ณ  ๊ฐ€์ •ํ•˜ํ•˜๊ณ  ์žˆ๋Š” ๊ธฐ์กด์˜ ์ด๋™ ์• ๋“œํ˜น ๋„คํŠธ์›Œํฌ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋“ค์€ ์ ์šฉํ•  ์ˆ˜ ์—†๋‹ค. ์‹ ์†ํ•œ ์ด์›ƒ ํƒ์ƒ‰์„ ํ•˜๊ธฐ ์œ„ํ•ด์„œ, ๋…ธ๋“œ๋Š” ์ง€์†์ ์œผ๋กœ ์ฃผ๋ณ€์— ์žˆ๋Š” ๋‹ค๋ฅธ ๋…ธ๋“œ๋ฅผ ํƒ์ƒ‰ํ•˜๊ธฐ ์œ„ํ•ด probing ๋ฉ”์‹œ์ง€๋ฅผ broadcastingํ•˜๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฐ ์ข…๋ฅ˜์˜ ์ง€์†์ ์ธ probing์€ ๋„ˆ๋ฌด ์—๋„ˆ์ง€ ์†Œ๋ชจ๊ฐ€ ํฌ๊ธฐ ๋•Œ๋ฌธ์—, ๋ฐฐํ„ฐ๋ฆฌ๋กœ ๋™์ž‘ํ•˜๋Š” ์žฅ์น˜์—๊ฒŒ๋Š” ์ ํ•ฉํ•˜์ง€ ์•Š๋‹ค. ์—๋„ˆ์ง€ ์†Œ๋น„๋ฅผ ์ตœ์†Œํ™”ํ•˜๊ธฐ ์œ„ํ•ด์„œ ๋‹ค๋ฅธ ๋…ธ๋“œ๋ฅผ ๋งŒ๋‚˜์ง€ ์•Š์„ ๋•Œ์—๋Š” radio ์ „์›์„ ๊บผ์„œ sleeping mode๋กœ ์„ค์ •ํ•˜๊ณ , ์˜ค์ง ์ด์›ƒ ํƒ์ƒ‰๊ณผ ๋ฐ์ดํƒ€๋ฅผ ๊ตํ™˜ํ•  ๋•Œ์—๋งŒ radio ์ „์›์„ ์ผœ์•ผ ํ•œ๋‹ค. ์šฐ์„ , ์—๋„ˆ์ง€ ํšจ์œจ์ ์ด๊ณ  ์ตœ์†Œ์˜ missing ํ™•๋ฅ ๊ณผ ๊ณ ์ • ์ง€์—ฐ ์‹œ๊ฐ„์„ ์ œ๊ณตํ•˜๋Š” probing ์Šค์ผ€์ฅด ๋ฐฉ์‹์„ ์„ค๊ณ„ํ•œ๋‹ค. ์ดํ›„ ์ œ์•ˆ๋œ probing ์Šค์ผ€์ฅด๊ณผ ํ•จ๊ป˜ ์ตœ์ ์˜ ์—๋„ˆ์ง€ ํšจ์œจ์ ์ธ listening ์Šค์ผ€์ฅด ๋ฐฉ์‹์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ์ด์›ƒ ํƒ์ƒ‰ ๊ธฐ๋ฒ•์€ ์ตœ์†Œ์˜ ์—๋„ˆ์ง€ ์†Œ๋ชจ์™€ ์ตœ์†Œ์˜ missing ํ™•๋ฅ ์„ ์ œ๊ณตํ•˜๋ฉด์„œ ๊ณ ์ • ์ง€์—ฐ ์‹œ๊ฐ„์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ์ ์—์„œ ์ตœ์ ์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด๋ผ๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, ์ด๋ก ์  ๋ถ„์„๊ณผ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ฒฐ๊ณผ๋ฅผ ํ†ตํ•ด์„œ ๊ธฐ์กด์˜ ๊ธฐ๋ฒ•๋“ค๊ณผ ์„ฑ๋Šฅ์„ ๋น„๊ตํ•˜์˜€๋‹ค. ์ด ๋น„๊ต๋ฅผ ํ†ตํ•ด์„œ ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์ด ์—๋„ˆ์ง€ ์†Œ๋ชจ ๋ฐ contact์˜ missing ํ™•๋ฅ  ์ธก๋ฉด์—์„œ ๊ธฐ๋ณธ์˜ ๊ธฐ๋ฒ•๋“ค๋ณด๋‹ค ์šฐ์ˆ˜ํ•œ ์—๋„ˆ์ง€ ํšจ์œจ์„ฑ๊ณผ ๋†’์€ ์ด์›ƒ ํƒ์ƒ‰ ํ™•๋ฅ ์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ ์ค€๋‹ค.Recently, there has been a growing interest in new networking paradigms such as opportunistic networks and cognitive networks. Various applications of ubiquitous networking and cloud computing are at the heart of such development (e.g. military, vehicular, rescue, medical, and multimedia transfer service). These networks are typically deployed without any communication infrastructure and are required to configure themselves. Neighbor discovery is one of the first steps in the self-configuration. To enable reliable exchange of data or control information, two nodes in physical contact must recognize each other and establish a link in a common channel. If a node fails to accomplish it, it misses the contact and experiences very long delivery latency or a failure of data delivery. Moreover, since it is difficult to predict when a node gets and how long it keeps in contact with another node, it is very challenging to discover neighbor nodes. In this thesis, we focus on the problem of discovering neighbor nodes in a fully distributed and deterministic manner.In the first topic of this thesis, we propose a channel rendezvous scheme in multi-channel access networks. Nodes must establish a link on a common channel before data transmission begins. We focus on the distributed channel rendezvous problem without a separate control channel. Our scheme determines the order, in which two nodes visit available channels to rendezvous within 2N+1 slots, where NN is the number of channels and a slot is the minimum interval required for establishing a link between any pair of nodes that are in a common channel. The best bound known so far is N^2+N-1 slots. By Jain's fairness index, we justify the claim that all channels are fairly accessed. More notably, our scheme can be implemented without slot synchronization which is hard to accomplish in a distributed manner.In the second topic of this thesis, we propose an optimal energy-efficient neighbor discovery scheme for opportunistic networks. Opportunistic networks are one of the most interesting evolutions of MANETs (Mobile Adhoc Networks). For a practical MANET, links may be intermittently established due to short transmission range and high user mobility, which is not the case where most previous works have implicitly assumed that the network is connected and there is a contemporaneous end-to-end path between any two nodes. For prompt neighbor discovery, a node is assumed to broadcast continuously probing messages to discover another in its vicinity. This kind of persistent probing consumes too much energy for battery-operated devices to afford. In order to minimize the energy consumption for persistent probing, a node must be able to turn off its radio, thus setting it to sleeping mode, during non-contact times and be able to turn it on only for neighbor discovery and data exchange. We design a probing schedule which provides a bounded delay with the minimal miss probability of a contact. Then, we derive an energy-efficient probing and associated listening schedule. The proposed neighbor discovery scheme is optimal in the sense that it provides a bounded delay with the minimal energy consumption as well as with the minimal miss probability of a contact. The performance of the proposed neighbor discovery scheme is evaluated by an extensive theoretical analysis and simulation results. Performance metrics, such as energy consumption, and loss probability of a contact are compared with those of existing schemes. The theoretical analysis and simulation results are also used to show the performance of the proposed scheme could be improved. In opportunistic networks where contact between two nodes occurs infrequently, we show that the proposed scheme achieves more significant energy-efficiency and provides much higher successful neighbor discovery probability than existing schemes
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