8 research outputs found

    Single user TCP downstream throughput probability models in IEEE802.11b WLAN system

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    Single User, Transmission Control Protocol Downstream Throughput (TCPDST) probability models in an IEEE802.11b WLAN have been developed, validated and evaluated for performance. Measurement of single user TCPDST were taken using Tamosoft throughput test while that of signal to noise ratio (SNR) were taken using inSSIDer 2.1. The Tamosoft throughput tests were conducted using different quality of service (QoS) traffic. These QoS traffic (which were sent through an infrastructure based network) correspond to different wireless multimedia tags. Measurements were taken in free space, small offices and open corridor environments. By assuming a normal distribution, single user TCPDST Cumulative distribution function (CDF) probability models were developed for different signal categories namely: (i) all the SNR considered, (ii) strong signals only, (iii) grey signals only and (iv) weak signals only. The models were validated and their performances evaluated using root mean square (RMS) errors. RMS errors were computed by comparing model predicted values with validation data. The RMS errors for single user CDF all signals model was 0.1466%. RMS errors for strong signals models, grey signals model and weak signals model respectively were 0.1466%, 0.6756% and 0.1233% indicating acceptable performances. All signals, strong signals, grey signals and weak signals CDF probability models predicted probabilities of obtaining TCPDST values greater than 5Mbps as 74.79%, 90.55%, 13.00% and 4.77% respectively while probabilities of obtaining TCPDST values less than 2Mbps were predicted as 4.91%, 0.00%, 18.98% and 52.41% respectively. These probability models will provide additional useful information needed to design efficient distributed data networks. Keywords: Throughput, TCP, WLAN, probability model

    Environment specific TCP upstream throughput models in IEEE802.11b WLAN

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    This paper presents our study on environment based dependence of TCP Upstream Throughput (TCPupT) on signal to noise ratio (SNR) for a single user in an IEEE 802.11b Wireless Local Area Network (WLAN). Small offices, open corridors and free space environments were studied using an infrastructure based network for different quality of service (QoS) traffic. Environment based Models that predict TCPupT directly from SNR for different signal categories were statistically generated, validated and compared with similar models that were earlier developed without considering specific environments. The first type of models developed in this work were developed from all data specifically collected from each environment while the second type of models were developed by first categorizing the data in each specific environment into different signal categories and then models were statistically generated for each signal category before combining them into one model equation. At the stated levels of significance and the different degrees of freedom, the developed models were accepted at 1% (for F test) and 0.5% (for T test). From the RMS errors computed, the specific environment based models developed in this work were more accurate (as they showed lower RMS errors compared with earlier similar models) in predicting TCPupT in IEEE 802.11b WLAN for a single user on the network. It was also observed that the second type of models were found to be more accurate having shown lower RMS errors.Keywords: TCP Upstream throughput, Signal to noise ratio, environment based empirical model,IEEE802.11b, WLAN

    Proceedings of the Third Edition of the Annual Conference on Wireless On-demand Network Systems and Services (WONS 2006)

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    Ce fichier regroupe en un seul documents l'ensemble des articles accรฉptรฉs pour la confรฉrences WONS2006/http://citi.insa-lyon.fr/wons2006/index.htmlThis year, 56 papers were submitted. From the Open Call submissions we accepted 16 papers as full papers (up to 12 pages) and 8 papers as short papers (up to 6 pages). All the accepted papers will be presented orally in the Workshop sessions. More precisely, the selected papers have been organized in 7 session: Channel access and scheduling, Energy-aware Protocols, QoS in Mobile Ad-Hoc networks, Multihop Performance Issues, Wireless Internet, Applications and finally Security Issues. The papers (and authors) come from all parts of the world, confirming the international stature of this Workshop. The majority of the contributions are from Europe (France, Germany, Greece, Italy, Netherlands, Norway, Switzerland, UK). However, a significant number is from Australia, Brazil, Canada, Iran, Korea and USA. The proceedings also include two invited papers. We take this opportunity to thank all the authors who submitted their papers to WONS 2006. You helped make this event again a success

    ์™„์ „ ์ด์‹ํ˜• ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ •๋ณด๊ณตํ•™๋ถ€,2020. 2. ๊น€์„ฑ์ค€.A visual prosthetic system typically consists of a neural stimulator, which is a surgically implantable device for electrical stimulation intended to restore the partial vision of blind patients, and peripheral external devices including an image sensor, a controller, and a processor. Although several visual prosthetic systems, such as retinal prostheses or retinal implants, have already been commercialized, there are still many issues on them (e.g., substrate materials for implantable units, electrode configurations, the use of external hardware, power supply and data transmission methods, design and fabrication approaches, etc.) to be dealt with for an improved visual prosthetic system. In this dissertation, a totally implantable visual prosthetic system is suggested with four motivations, which are thought to be important, as in the following: 1) simple fabrication of implantable parts, such as micro-sized electrodes and a case, for a neural stimulator based on polymer without semiconductor techniques, 2) multi-polar stimulation for virtual channel generation to overcome a limited number of physical electrodes in a confined space, 3) a new image acquisition strategy using an implantable camera, and 4) power supply as well as data transmission to a neural stimulator without hindering patients various activities. First, polymer materials have been widely used to develop various implantable devices for visual prosthetic systems because of their outstanding advantages including flexibility and applicability to microfabrication, compared with metal, silicon, or ceramic. Most polymer-based implantable devices have been fabricated by the semiconductor technology based on metal deposition and photolithography. This technology provides high accuracy and precision for metal patterning on a polymer substrate. However, the technology is also complicated and time-consuming as it requires masks for photolithography and vacuum for metal deposition as well as huge fabrication facilities. This is the reason why biocompatible cyclic olefin polymer (COP) with low water absorption (<0.01 %) and high light transmission (92 %) was chosen as a new substrate material of an implantable device in this study. Based on COP, simple fabrication process of an implantable device was developed without masks, vacuum, and huge fabrication facilities. COP is characterized by strong adhesion to gold and high ultraviolet (UV) transparency as well. Because of such adhesion and UV transparency, a gold thin film can be thermally laminated on a COP substrate with no adhesion layer and micromachined by a UV laser without damaging the substrate. Using the developed COP-based process, a depth-type microprobe was fabricated first, and its electrochemical and mechanical properties as well as functionality were evaluated by impedance measurements, buckling tests, and in vivo neural signal recording, respectively. Furthermore, the long-term reliability of COP encapsulation formed by the developed process was estimated through leakage current measurements during accelerated aging in saline solution, to show the feasibility of the encapsulation using COP as well. Second, even if stimulation electrodes become sufficiently small, it is demanding to arrange them for precise stimulation on individual neurons due to electrical crosstalk, which is the spatial superposition of electric fields generated by simultaneous stimuli. Hence, an adequate spacing between adjacent electrodes is required, and this causes a limited number of physical electrodes in a confined space such as in the brain or in the retina. To overcome this limitation, many researchers have proposed stimulation strategies using virtual channels, which are intermediate areas with large magnitudes of electric fields between physical electrodes. Such virtual channels can be created by multi-polar stimulation that can combine stimuli output from two or more electrodes at the same time. To produce more delicate stimulation patterns using virtual channels herein, penta-polar stimulation with a grid-shaped arrangement of electrodes was leveraged specially to generate them in two dimensions. This penta-polar stimulation was realized using a custom-designed integrated circuit with five different current sources and surface-type electrodes fabricated by the developed COP-based process. The effectiveness of the penta-polar stimulation was firstly evaluated by focusing electric fields in comparison to mono-polar stimulation. In addition, the distribution of electric fields changed by the penta-polar stimulation, which indicated virtual channel generation, was estimated in accordance with an amplitude ratio between stimuli of the two adjacent electrodes and a distance from them, through both finite element analysis and in vitro evaluation. Third, an implantable camera is herein proposed as a new image acquisition approach capturing real-time images while implanted in the eye, to construct a totally implantable visual prosthetic system. This implantable camera has distinct advantages in that it can provide blind patients with benefits to perform several ordinary activities, such as sleep, shower, or running, while focusing on objects in accordance with natural eye movements. These advantages are impossible to be achieved using a wearing unit such as a glasses-mounted camera used in a conventional partially implantable visual prosthetic system. Moreover, the implantable camera also has a merit of garnering a variety of image information using the complete structure of a camera, compared with a micro-photodiode array of a retinal implant. To fulfill these advantageous features, after having been coated with a biocompatible epoxy to prevent moisture penetration and sealed using a medical-grade silicone elastomer to gain biocompatibility as well as flexibility, the implantable camera was fabricated enough to be inserted into the eye. Its operation was assessed by wireless image acquisition that displayed a processed black and white image. In addition, to estimate reliable wireless communication ranges of the implantable camera in the body, signal-to-noise ratio measurements were conducted while it was covered by an 8-mm-thick biological medium that mimicked an in vivo environment. Lastly, external hardware attached on the body has been generally used in conventional visual prosthetic systems to stably deliver power and data to implanted units and to acquire image signals outside the body. However, there are common problems caused by this external hardware, including functional failure due to external damages, unavailability during sleep, in the shower, or while running or swimming, and cosmetic issues. Especially, an external coil for power and data transmission in a conventional visual prosthetic system is connected to a controller and processor through a wire, which makes the coil more vulnerable to the problems. To solve this issue, a totally implantable neural stimulation system controlled by a handheld remote controller is presented. This handheld remote controller can control a totally implantable stimulator powered by a rechargeable battery through low-power but relatively long-range ZigBee wireless communication. Moreover, two more functions can be performed by the handheld controller for expanded applications; one is percutaneous stimulation, and the other is inductive charging of the rechargeable battery. Additionally, simple switches on the handheld controller enable users to modulate parameters of stimuli like a gamepad. These handheld and user-friendly interfaces can make it easy to use the controller under various circumstances. The functionality of the controller was evaluated in vivo, through percutaneous stimulation and remote control especially for avian navigation, as well as in vitro. Results of both in vivo experiments were compared in order to verify the feasibility of remote control of neural stimulation using the controller. In conclusion, several discussions on results of this study, including the COP-based simple fabrication process, the penta-polar stimulation, the implantable camera, and the multi-functional handheld remote controller, are addressed. Based on these findings and discussions, how the researches in this thesis can be applied to the realization of a totally implantable visual prosthetic system is elucidated at the end of this dissertation.์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์€ ์ผ๋ฐ˜์ ์œผ๋กœ ์‹ค๋ช… ํ™˜์ž๋“ค์˜ ๋ถ€๋ถ„ ์‹œ๋ ฅ์„ ์ „๊ธฐ ์ž๊ทน์œผ๋กœ ํšŒ๋ณต์‹œํ‚ค๊ธฐ ์œ„ํ•˜์—ฌ ์ˆ˜์ˆ ์ ์œผ๋กœ ์ด์‹๋  ์ˆ˜ ์žˆ๋Š” ์žฅ์น˜์ธ ์‹ ๊ฒฝ ์ž๊ทน๊ธฐ์™€ ์ด๋ฏธ์ง€ ์„ผ์„œ ๋˜๋Š” ์ปจํŠธ๋กค๋Ÿฌ, ํ”„๋กœ์„ธ์„œ๋ฅผ ํฌํ•จํ•˜๋Š” ์™ธ๋ถ€์˜ ์ฃผ๋ณ€ ์žฅ์น˜๋“ค๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ๋ง๋ง‰ ๋ณด์ฒ  ์žฅ์น˜ ๋˜๋Š” ๋ง๋ง‰ ์ž„ํ”Œ๋ž€ํŠธ์™€ ๊ฐ™์ด ๋ช‡๋ช‡ ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์€ ์ด๋ฏธ ์ƒ์šฉํ™” ๋˜์—ˆ์ง€๋งŒ, ์—ฌ์ „ํžˆ ๋” ๋‚˜์€ ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์„ ์œ„ํ•˜์—ฌ ๋‹ค๋ค„์ ธ์•ผ ํ•  ๋งŽ์€ ์ด์Šˆ๋“ค (์˜ˆ๋ฅผ ๋“ค์–ด, ์ด์‹ํ˜• ์žฅ์น˜์˜ ๊ธฐํŒ ๋ฌผ์งˆ, ์ „๊ทน์˜ ๋ฐฐ์—ด, ์™ธ๋ถ€ ํ•˜๋“œ์›จ์–ด์˜ ์‚ฌ์šฉ, ์ „๋ ฅ ๊ณต๊ธ‰ ๋ฐ ๋ฐ์ดํ„ฐ ์ „์†ก ๋ฐฉ๋ฒ•, ์„ค๊ณ„ ๋ฐ ์ œ์ž‘ ๋ฐฉ์‹ ๋“ฑ)์ด ์žˆ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์€ ์™„์ „ ์ด์‹ํ˜• ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์„ ์ œ์•ˆํ•˜๋ฉฐ, ์ด๋ฅผ ์œ„ํ•˜์—ฌ ๋‹ค์Œ๊ณผ ๊ฐ™์ด ์ค‘์š”ํ•˜๋‹ค๊ณ  ์ƒ๊ฐ๋˜๋Š” ์ด ๋„ค ๊ฐ€์ง€์˜ ์ด์Šˆ๋“ค๊ณผ ๊ด€๋ จ๋œ ์—ฐ๊ตฌ ๋‚ด์šฉ์„ ๋‹ค๋ฃฌ๋‹ค. 1) ํด๋ฆฌ๋จธ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์‹ ๊ฒฝ ์ž๊ทน๊ธฐ์˜ ๋ฏธ์„ธ ์ „๊ทน ๋ฐ ํŒจํ‚ค์ง€์™€ ๊ฐ™์€ ์ด์‹ ๊ฐ€๋Šฅํ•œ ๋ถ€๋ถ„์„ ๋ฐ˜๋„์ฒด ๊ธฐ์ˆ  ์—†์ด ๊ฐ„๋‹จํ•˜๊ฒŒ ์ œ์ž‘ํ•˜๋Š” ๋ฐฉ๋ฒ•๊ณผ 2) ์ œํ•œ๋œ ๊ณต๊ฐ„์—์„œ ์ „๊ทน ๊ฐœ์ˆ˜์˜ ๋ฌผ๋ฆฌ์ ์ธ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๊ฐ€์ƒ ์ฑ„๋„์„ ํ˜•์„ฑํ•˜๋Š” ๋‹ค๊ทน์„ฑ ์ž๊ทน ๋ฐฉ์‹, 3) ์ด์‹ํ˜• ์นด๋ฉ”๋ผ๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ์ƒˆ๋กœ์šด ์ด๋ฏธ์ง€ ํš๋“ ์ „๋žต, 4) ํ™˜์ž์˜ ๋‹ค์–‘ํ•œ ํ™œ๋™์„ ๋ฐฉํ•ดํ•˜์ง€ ์•Š์œผ๋ฉด์„œ ์‹ ๊ฒฝ ์ž๊ทน๊ธฐ์— ์ „๋ ฅ์„ ๊ณต๊ธ‰ํ•˜๊ณ  ๋ฐ์ดํ„ฐ๋ฅผ ์ „์†กํ•˜๋Š” ๋ฐฉ๋ฒ•. ์ฒซ์งธ๋กœ, ๊ธˆ์†์ด๋‚˜ ์‹ค๋ฆฌ์ฝ˜, ์„ธ๋ผ๋ฏน์— ๋น„ํ•˜์—ฌ ํด๋ฆฌ๋จธ๋Š” ์œ ์—ฐ์„ฑ ๋ฐ ๋ฏธ์„ธ ์ œ์ž‘์—์˜ ์ ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ํฌํ•จํ•˜๋Š” ๋‘๋“œ๋Ÿฌ์ง„ ์ด์ ๋“ค์ด ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์„ ๊ตฌ์„ฑํ•˜๋Š” ๋‹ค์–‘ํ•œ ์ด์‹ ๊ฐ€๋Šฅํ•œ ๋ถ€๋ถ„๋“ค์— ๋„๋ฆฌ ์ด์šฉ๋˜์—ˆ๋‹ค. ๋Œ€๋ถ€๋ถ„์˜ ํด๋ฆฌ๋จธ ๊ธฐ๋ฐ˜ ์ด์‹ํ˜• ์žฅ์น˜๋“ค์€ ๊ธˆ์† ์ฆ์ฐฉ๊ณผ ์‚ฌ์ง„ ์‹๊ฐ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” ๋ฐ˜๋„์ฒด ๊ณต์ •์œผ๋กœ ์ œ์ž‘๋˜์—ˆ๋‹ค. ์ด ๊ณต์ •์€ ํด๋ฆฌ๋จธ ๊ธฐํŒ ์œ„์— ๊ธˆ์†์„ ํŒจํ„ฐ๋‹ ํ•˜๋Š” ๋ฐ์— ์žˆ์–ด์„œ ๋†’์€ ์ •ํ™•์„ฑ๊ณผ ์ •๋ฐ€๋„๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ ๊ณต์ •์€ ๋˜ํ•œ, ์‚ฌ์ง„ ์‹๊ฐ์— ์“ฐ์ด๋Š” ๋งˆ์Šคํฌ์™€ ๊ธˆ์† ์ฆ์ฐฉ์„ ์œ„ํ•œ ์ง„๊ณต๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์•„์ฃผ ํฐ ๊ณต์ • ์„ค๋น„๋ฅผ ์š”๊ตฌํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์‹œ๊ฐ„ ์†Œ๋ชจ๊ฐ€ ์‹ฌํ•˜๊ณ  ๋ณต์žกํ•˜๋‹ค. ์ด๋Š” ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋‚ฎ์€ ์ˆ˜๋ถ„ ํก์ˆ˜ (<0.01 %)์™€ ๋†’์€ ๋น› ํˆฌ๊ณผ (92 %)๋ฅผ ํŠน์ง•์œผ๋กœ ํ•˜๋Š” ์ƒ์ฒด์ ํ•ฉํ•œ ๊ณ ๋ฆฌํ˜• ์˜ฌ๋ ˆํ•€ ํด๋ฆฌ๋จธ (cyclic olefin polymer, COP)๊ฐ€ ์ด์‹ํ˜• ์žฅ์น˜๋ฅผ ์œ„ํ•œ ์ƒˆ๋กœ์šด ๊ธฐํŒ ๋ฌผ์งˆ๋กœ์จ ์„ ํƒ๋œ ์ด์œ ์ด๋‹ค. COP๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜์—ฌ, ๋งˆ์Šคํฌ์™€ ์ง„๊ณต, ํฐ ๊ณต์ • ์„ค๋น„๊ฐ€ ํ•„์š” ์—†์ด ์ด์‹ ๊ฐ€๋Šฅํ•œ ์žฅ์น˜๋ฅผ ๊ฐ„๋‹จํ•˜๊ฒŒ ์ œ์ž‘ํ•˜๋Š” ๊ณต์ •์ด ๊ฐœ๋ฐœ๋˜์—ˆ๋‹ค. COP๋Š” ๊ธˆ๊ณผ์˜ ๊ฐ•ํ•œ ์ ‘ํ•ฉ๊ณผ ์ž์™ธ์„ ์— ๋Œ€ํ•œ ๋†’์€ ํˆฌ๋ช…์„ฑ์„ ๋˜ ๋‹ค๋ฅธ ํŠน์ง•์œผ๋กœ ํ•œ๋‹ค. ์ด์™€ ๊ฐ™์€ ์ ‘ํ•ฉ ํŠน์„ฑ๊ณผ ์ž์™ธ์„  ํˆฌ๋ช…์„ฑ ๋•๋ถ„์—, ๊ธˆ๋ฐ•์€ COP ๊ธฐํŒ์— ๋ณ„๋„์˜ ์ ‘ํ•ฉ์ธต ์—†์ด ์—ด๋กœ ์ ‘ํ•ฉ๋  ์ˆ˜ ์žˆ์„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๊ทธ ๊ธฐํŒ์— ์†์ƒ์„ ์ฃผ์ง€ ์•Š์œผ๋ฉด์„œ ์ž์™ธ์„  ๋ ˆ์ด์ €๋ฅผ ํ†ตํ•˜์—ฌ ๋ฏธ์„ธํ•˜๊ฒŒ ๊ฐ€๊ณต๋  ์ˆ˜ ์žˆ๋‹ค. ๊ฐœ๋ฐœ๋œ COP ๊ธฐ๋ฐ˜์˜ ๊ณต์ •์„ ์ฒ˜์Œ์œผ๋กœ ์‚ฌ์šฉํ•˜์—ฌ ์นจ์Šตํ˜• ๋ฏธ์„ธ ํ”„๋กœ๋ธŒ๊ฐ€ ์ œ์ž‘๋˜์—ˆ๊ณ , ๊ทธ ์ „๊ธฐํ™”ํ•™์ , ๊ธฐ๊ณ„์  ํŠน์„ฑ๊ณผ ๊ธฐ๋Šฅ์„ฑ์ด ๊ฐ๊ฐ ์ž„ํ”ผ๋˜์Šค ์ธก์ •๊ณผ ๋ฒ„ํด๋ง ํ…Œ์ŠคํŠธ, ์ƒ์ฒด ๋‚ด ์‹ ๊ฒฝ์‹ ํ˜ธ ๊ธฐ๋ก์œผ๋กœ ํ‰๊ฐ€๋˜์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  COP๋ฅผ ์‚ฌ์šฉํ•œ ๋ฐ€๋ด‰์˜ ๊ฐ€๋Šฅ์„ฑ๋„ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•˜์—ฌ, ๊ฐœ๋ฐœ๋œ ๊ณต์ •์„ ์‚ฌ์šฉํ•˜์—ฌ ํ˜•์„ฑ๋œ COP ๋ฐ€๋ด‰์˜ ์žฅ๊ธฐ ์•ˆ์ •์„ฑ์ด ์ƒ๋ฆฌ์‹์—ผ์ˆ˜์—์„œ์˜ ๊ฐ€์† ๋…ธํ™” ์ค‘ ๋ˆ„์„ค ์ „๋ฅ˜ ์ธก์ •์„ ํ†ตํ•˜์—ฌ ์ถ”์ •๋˜์—ˆ๋‹ค. ๋‘˜์งธ๋กœ, ์ž๊ทน ์ „๊ทน์˜ ํฌ๊ธฐ๊ฐ€ ์ถฉ๋ถ„ํžˆ ์ž‘์•„์ง„๋‹ค๊ณ  ํ•˜๋”๋ผ๋„, ๋™์‹œ์— ์ถœ๋ ฅ๋˜๋Š” ์ž๊ทน์— ์˜ํ•ด ํ˜•์„ฑ๋˜๋Š” ์ „๊ธฐ์žฅ์˜ ์ค‘์ฒฉ์ธ ํฌ๋กœ์Šค ํ† ํฌ ๋•Œ๋ฌธ์— ๊ฐœ๊ฐœ์˜ ์‹ ๊ฒฝ์„ธํฌ๋ฅผ ์ •๋ฐ€ํ•˜๊ฒŒ ์ž๊ทนํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ „๊ทน์„ ๋ฐฐ์—ดํ•˜๋Š” ๊ฒƒ์€ ์•„์ฃผ ์–ด๋ ต๋‹ค. ๋”ฐ๋ผ์„œ ์ธ์ ‘ํ•œ ์ „๊ทน ์‚ฌ์ด์— ์ ๋‹นํ•œ ๊ฐ„๊ฒฉ์ด ํ•„์š”ํ•˜๊ฒŒ ๋˜๊ณ , ์ด๋Š” ํŠนํžˆ ๋‡Œ ๋˜๋Š” ๋ง๋ง‰๊ณผ ๊ฐ™์€ ์ œํ•œ๋œ ๊ณต๊ฐ„์—์„œ ์ „๊ทน ๊ฐœ์ˆ˜์˜ ๋ฌผ๋ฆฌ์ ์ธ ํ•œ๊ณ„๋ฅผ ์•ผ๊ธฐํ•œ๋‹ค. ์ด ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, ๋งŽ์€ ์—ฐ๊ตฌ์ž๋“ค์€ ์‹ค์ œ ์ „๊ทน ์‚ฌ์ด์—์„œ ํฐ ์ „๊ธฐ์žฅ ์„ธ๊ธฐ๋ฅผ ๊ฐ–๋Š” ์ค‘๊ฐ„ ์˜์—ญ์„ ๋‚˜ํƒ€๋‚ด๋Š” ๊ฐ€์ƒ ์ฑ„๋„์„ ์ด์šฉํ•œ ์ž๊ทน ์ „๋žต์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ฐ€์ƒ ์ฑ„๋„์€ ๋‘˜ ์ด์ƒ์˜ ์ „๊ทน์—์„œ ๋™์‹œ์— ์ถœ๋ ฅ๋˜๋Š” ์ž๊ทน ํŒŒํ˜•์„ ํ•ฉ์น  ์ˆ˜ ์žˆ๋Š” ๋‹ค๊ทน์„ฑ ์ž๊ทน์— ์˜ํ•˜์—ฌ ํ˜•์„ฑ์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ฐ€์ƒ ์ฑ„๋„์„ ์ด์šฉํ•˜์—ฌ ๋” ์ •๊ตํ•œ ์ž๊ทน ํŒจํ„ด์„ ๋งŒ๋“ค๊ธฐ ์œ„ํ•˜์—ฌ, ํŠนํžˆ 2์ฐจ์›์—์„œ์˜ ๊ฐ€์ƒ ์ฑ„๋„์„ ์ƒ์„ฑํ•˜๊ณ ์ž ๊ฒฉ์žํ˜• ๋ฐฐ์—ด์˜ ์ „๊ทน๊ณผ ํ•จ๊ป˜ 5๊ทน์„ฑ ์ž๊ทน์ด ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ์ด 5๊ทน์„ฑ ์ž๊ทน์€ ๋‹ค์„ฏ ๊ฐœ์˜ ์„œ๋กœ ๋‹ค๋ฅธ ์ „๋ฅ˜์›์„ ๊ฐ–๋„๋ก ๋งž์ถค ์„ค๊ณ„๋œ ์ง‘์ ํšŒ๋กœ์™€ ๊ฐœ๋ฐœ๋œ COP ๊ธฐ๋ฐ˜ ๊ณต์ •์œผ๋กœ ์ œ์ž‘๋œ ํ‰๋ฉดํ˜• ์ „๊ทน์„ ์‚ฌ์šฉํ•˜์—ฌ ๊ตฌํ˜„๋˜์—ˆ๋‹ค. ๋จผ์ €, 5๊ทน์„ฑ ์ž๊ทน์˜ ํšจ๊ณผ๋ฅผ ํ™•์ธํ•˜๊ณ ์ž ์ด ์ž๊ทน์œผ๋กœ ์ „๊ธฐ์žฅ์„ ํ•œ ๊ณณ์— ๋” ์ง‘์ค‘๋œ ํ˜•ํƒœ๋กœ ๋งŒ๋“ค ์ˆ˜ ์žˆ์Œ์ด ๋‹จ๊ทน์„ฑ ์ž๊ทน๊ณผ์˜ ๋น„๊ต๋ฅผ ํ†ตํ•˜์—ฌ ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์œ ํ•œ ์š”์†Œ ๋ถ„์„๊ณผ ์ƒ์ฒด ์™ธ ํ‰๊ฐ€ ๋‘˜ ๋ชจ๋‘๋ฅผ ํ†ตํ•˜์—ฌ, 5๊ทน์„ฑ ์ž๊ทน์œผ๋กœ ์ธํ•œ ๊ฐ€์ƒ ์ฑ„๋„ ํ˜•์„ฑ์„ ๋œปํ•˜๋Š” ์ „๊ธฐ์žฅ ๋ถ„ํฌ๊ฐ€ ์ธ์ ‘ํ•œ ๋‘ ์ „๊ทน์—์„œ ๋‚˜์˜ค๋Š” ์ž๊ทน์˜ ์ง„ํญ๋น„์™€ ๊ทธ ์ „๊ทน์œผ๋กœ๋ถ€ํ„ฐ ๋–จ์–ด์ง„ ๊ฑฐ๋ฆฌ์— ๋”ฐ๋ผ ๋ณ€ํ™”๋จ์ด ์ถ”์ •๋˜์—ˆ๋‹ค. ์…‹์งธ๋กœ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ˆˆ์— ์ด์‹๋œ ์ฑ„๋กœ ์‹ค์‹œ๊ฐ„ ์ด๋ฏธ์ง€๋ฅผ ์–ป์Œ์œผ๋กœ์จ ์™„์ „ ์ด์‹ํ˜• ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์„ ๊ตฌ์„ฑํ•˜๋Š” ์ด์‹ํ˜• ์นด๋ฉ”๋ผ๋ฅผ ์ƒˆ๋กœ์šด ์ด๋ฏธ์ง€ ํš๋“ ๋ฐฉ์‹์œผ๋กœ์จ ์ œ์•ˆํ•œ๋‹ค. ์ด ์ด์‹ํ˜• ์นด๋ฉ”๋ผ๋Š” ์‹ค๋ช… ํ™˜์ž๋“ค์ด ์ž์—ฐ์Šค๋Ÿฌ์šด ๋ˆˆ์˜ ์›€์ง์ž„์„ ๋”ฐ๋ผ์„œ ๋ฌผ์ฒด๋ฅผ ๋ณผ ์ˆ˜ ์žˆ์œผ๋ฉฐ ์ž ์ด๋‚˜ ์ƒค์›Œ, ๋‹ฌ๋ฆฌ๊ธฐ์™€ ๊ฐ™์€ ์ผ์ƒ์ ์ธ ํ™œ๋™๋“ค์„ ๋ฐฉํ•ด ๋ฐ›์ง€ ์•Š๊ณ  ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•๋Š”๋‹ค๋Š” ์ ์—์„œ ๋…ํŠนํ•œ ์žฅ์ ์„ ๊ฐ–๋Š”๋‹ค. ๊ธฐ์กด์˜ ๋ถ€๋ถ„ ์ด์‹ํ˜• ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์—์„œ ์“ฐ์ด๋Š” ์•ˆ๊ฒฝ ๋ถ€์ฐฉํ˜• ์นด๋ฉ”๋ผ์™€ ๊ฐ™์€ ์ฐฉ์šฉ ์žฅ๋น„๋กœ๋Š” ์ด๋Ÿฌํ•œ ์žฅ์ ๋“ค์„ ์–ป์„ ์ˆ˜ ์—†๋‹ค. ๊ฒŒ๋‹ค๊ฐ€, ์ด์‹ํ˜• ์นด๋ฉ”๋ผ๋Š” ๋ง๋ง‰ ์ž„ํ”Œ๋ž€ํŠธ์˜ ๋ฏธ์„ธ ํฌํ† ๋‹ค์ด์˜ค๋“œ ์–ด๋ ˆ์ด์™€ ๋‹ฌ๋ฆฌ ์™„์ „ํ•œ ์นด๋ฉ”๋ผ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ๋‹ค์–‘ํ•œ ์ด๋ฏธ์ง€ ์ •๋ณด๋ฅผ ํš๋“ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์žฅ์ ์„ ๊ฐ–๋Š”๋‹ค. ์ด๋Ÿฌํ•œ ์ด์ ๋“ค์„ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, ๊ทธ ์ด์‹ํ˜• ์นด๋ฉ”๋ผ๋Š” ์ˆ˜๋ถ„ ์นจํˆฌ๋ฅผ ๋ง‰๊ณ ์ž ์ƒ์ฒด์ ํ•ฉํ•œ ์—ํญ์‹œ๋กœ ์ฝ”ํŒ…๋˜์—ˆ๊ณ  ์ƒ์ฒด์ ํ•ฉ์„ฑ๊ณผ ์œ ์—ฐ์„ฑ์„ ์–ป๊ธฐ ์œ„ํ•˜์—ฌ ์˜๋ฃŒ์šฉ ์‹ค๋ฆฌ์ฝ˜ ์—˜๋ผ์Šคํ† ๋จธ๋กœ ๋ฐ€๋ด‰๋œ ํ›„์— ๋ˆˆ์— ์ถฉ๋ถ„ํžˆ ์‚ฝ์ž…๋  ์ˆ˜ ์žˆ๋Š” ํ˜•ํƒœ ๋ฐ ํฌ๊ธฐ๋กœ ์ œ์ž‘๋˜์—ˆ๋‹ค. ์ด ์žฅ์น˜์˜ ๋™์ž‘์€ ํ‘๋ฐฑ์œผ๋กœ ์ฒ˜๋ฆฌ๋œ ์ด๋ฏธ์ง€๋ฅผ ํ‘œ์‹œํ•˜๋Š” ๋ฌด์„  ์ด๋ฏธ์ง€ ํš๋“์œผ๋กœ ์‹œํ—˜๋˜์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋ชธ ์•ˆ์—์„œ ์ด์‹ํ˜• ์นด๋ฉ”๋ผ ๊ฐ–๋Š” ์•ˆ์ •์ ์ธ ํ†ต์‹  ๊ฑฐ๋ฆฌ๋ฅผ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ, ์žฅ์น˜๊ฐ€ ์ƒ์ฒด ๋‚ด ํ™˜๊ฒฝ์„ ๋ชจ์‚ฌํ•˜๊ธฐ ์œ„ํ•œ 8 mm ๋‘๊ป˜์˜ ์ƒ์ฒด ๋ฌผ์งˆ๋กœ ๋ฎ์ธ ์ƒํƒœ์—์„œ ๊ทธ ์žฅ์น˜์˜ ์‹ ํ˜ธ ๋Œ€ ์žก์Œ๋น„๊ฐ€ ์ธก์ •๋˜์—ˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๊ธฐ์กด์˜ ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์—์„œ ๋ชธ์— ๋ถ€์ฐฉ๋œ ํ˜•ํƒœ์˜ ์™ธ๋ถ€ ํ•˜๋“œ์›จ์–ด๋Š” ์ด์‹๋œ ์žฅ์น˜์— ์ „๋ ฅ๊ณผ ๋ฐ์ดํ„ฐ๋ฅผ ์•ˆ์ •์ ์œผ๋กœ ์ „๋‹ฌํ•˜๊ณ  ์ด๋ฏธ์ง€ ์‹ ํ˜ธ๋ฅผ ์ˆ˜์ง‘ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ผ๋ฐ˜์ ์œผ๋กœ ์‚ฌ์šฉ๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์ด๋Ÿฌํ•œ ํ•˜๋“œ์›จ์–ด๋Š” ์™ธ๋ถ€๋กœ๋ถ€ํ„ฐ์˜ ์†์ƒ์œผ๋กœ ์ธํ•œ ๊ธฐ๋Šฅ์ ์ธ ๊ฒฐํ•จ๊ณผ ์ˆ˜๋ฉด ๋ฐ ์ƒค์›Œ, ๋‹ฌ๋ฆฌ๊ธฐ, ์ˆ˜์˜ ํ™œ๋™ ์ค‘ ์ด์šฉ ๋ถˆ๊ฐ€๋Šฅ์„ฑ, ์™ธํ˜•์ ์ธ ์ด์Šˆ ๋“ฑ์„ ํฌํ•จํ•˜๋Š” ๊ณตํ†ต์ ์ธ ๋ฌธ์ œ๋“ค์„ ์•ผ๊ธฐํ•œ๋‹ค. ์ „๋ ฅ ๋ฐ ๋ฐ์ดํ„ฐ ์ „์†ก์„ ์œ„ํ•œ ์™ธ๋ถ€ ์ฝ”์ผ์€ ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์—์„œ ์ปจํŠธ๋กค๋Ÿฌ์™€ ํ”„๋กœ์„ธ์„œ์— ์œ ์„ ์œผ๋กœ ์—ฐ๊ฒฐ๋˜๊ณ , ์ด๋Ÿฌํ•œ ์—ฐ๊ฒฐ์€ ๊ทธ ์ฝ”์ผ์ด ์•ž์„œ ์–ธ๊ธ‰๋œ ๋ฌธ์ œ๋“ค์— ํŠนํžˆ ์ทจ์•ฝํ•˜๊ฒŒ ๋งŒ๋“ ๋‹ค. ์ด๋Ÿฌํ•œ ์ด์Šˆ๋ฅผ ํ•ด๊ฒฐํ•˜๊ณ ์ž, ํœด๋Œ€์šฉ ๋ฌด์„  ์ปจํŠธ๋กค๋Ÿฌ๋กœ ์ œ์–ด๋˜๋Š” ์™„์ „ ์ด์‹ํ˜• ์‹ ๊ฒฝ ์ž๊ทน ์‹œ์Šคํ…œ์ด ์ œ์•ˆ๋œ๋‹ค. ์ด ํœด๋Œ€์šฉ ๋ฌด์„  ์ปจํŠธ๋กค๋Ÿฌ๋Š” ์ €์ „๋ ฅ์ด์ง€๋งŒ ๋น„๊ต์  ์žฅ๊ฑฐ๋ฆฌ ํ†ต์‹ ์ด ๊ฐ€๋Šฅํ•œ ์ง๋น„ (ZigBee) ๋ฌด์„  ํ†ต์‹ ์„ ํ†ตํ•˜์—ฌ ์žฌ์ถฉ์ „ ๊ฐ€๋Šฅํ•œ ๋ฐฐํ„ฐ๋ฆฌ๋กœ ๋™์ž‘ํ•˜๋Š” ์™„์ „ ์ด์‹ํ˜• ์ž๊ทน๊ธฐ๋ฅผ ์ œ์–ดํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด ์™ธ์—๋„, ์ด ํœด๋Œ€์šฉ ์ปจํŠธ๋กค๋Ÿฌ๋ฅผ ์‚ฌ์šฉํ•˜๋ฉด ํญ๋„“์€ ์‘์šฉ์„ ์œ„ํ•œ ๋‘ ๊ฐ€์ง€ ๊ธฐ๋Šฅ์„ ์ถ”๊ฐ€๋กœ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋‹ค. ํ•˜๋‚˜๋Š” ์œ ์„  ๊ฒฝํ”ผ ์ž๊ทน์ด๋ฉฐ, ๋‹ค๋ฅธ ํ•˜๋‚˜๋Š” ์žฌ์ถฉ์ „ ๊ฐ€๋Šฅํ•œ ๋ฐฐํ„ฐ๋ฆฌ์˜ ์œ ๋„ ์ถฉ์ „ ๊ธฐ๋Šฅ์ด๋‹ค. ๋˜ํ•œ, ์ด ํœด๋Œ€์šฉ ์ปจํŠธ๋กค๋Ÿฌ์˜ ๊ฐ„๋‹จํ•œ ์Šค์œ„์น˜๋ฅผ ์‚ฌ์šฉํ•˜๋ฉด ์‚ฌ์šฉ์ž๋Š” ๊ฒŒ์ž„ํŒจ๋“œ์™€ ๊ฐ™์ด ์ž๊ทน ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์‰ฝ๊ฒŒ ์กฐ์ ˆํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํœด๋Œ€ ๊ฐ€๋Šฅํ•˜๊ณ  ์‚ฌ์šฉ์ž ์นœํ™”์ ์ธ ์ธํ„ฐํŽ˜์ด์Šค๋ฅผ ํ†ตํ•ด ๋‹ค์–‘ํ•œ ์ƒํ™ฉ์—์„œ ๊ทธ ์ปจํŠธ๋กค๋Ÿฌ๋ฅผ ์‰ฝ๊ฒŒ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ ์ปจํŠธ๋กค๋Ÿฌ์˜ ๊ธฐ๋Šฅ์€ ์ƒ์ฒด ์™ธ ํ‰๊ฐ€๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์กฐ๋ฅ˜์˜ ์›€์ง์ž„ ์ œ์–ด๋ฅผ ์œ„ํ•œ ์œ ์„  ๊ฒฝํ”ผ ์ž๊ทน ๋ฐ ์›๊ฒฉ ์ œ์–ด๋ฅผ ํ†ตํ•ด ์ƒ์ฒด ๋‚ด์—์„œ๋„ ํ‰๊ฐ€๋˜์—ˆ๋‹ค. ๋˜ํ•œ, ๊ทธ ์ปจํŠธ๋กค๋Ÿฌ๋ฅผ ์‚ฌ์šฉํ•œ ์›๊ฒฉ ์‹ ๊ฒฝ ์ž๊ทน ์ œ์–ด์˜ ์ˆ˜ํ–‰ ๊ฐ€๋Šฅ์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๋‘ ์ƒ์ฒด ๋‚ด ์‹คํ—˜์˜ ๊ฒฐ๊ณผ๊ฐ€ ์„œ๋กœ ๋น„๊ต๋˜์—ˆ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ, COP ๊ธฐ๋ฐ˜์˜ ๊ฐ„๋‹จํ•œ ์ œ์ž‘ ๊ณต์ •๊ณผ 5๊ทน์„ฑ ์ž๊ทน, ์ด์‹ํ˜• ์นด๋ฉ”๋ผ, ํœด๋Œ€์šฉ ๋‹ค๊ธฐ๋Šฅ ๋ฌด์„  ์ปจํŠธ๋กค๋Ÿฌ๋ฅผ ํฌํ•จํ•˜๋Š” ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ์—ฌ๋Ÿฌ ๋…ผ์˜๊ฐ€ ์ด๋ฃจ์–ด์ง„๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ์™€ ๊ณ ์ฐฐ์— ๊ธฐ์ดˆํ•˜์—ฌ, ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์˜ ์—ฐ๊ตฌ๊ฐ€ ์™„์ „ ์ด์‹ํ˜• ์‹œ๊ฐ ๋ณด์ฒ  ์‹œ์Šคํ…œ์˜ ๊ตฌํ˜„์— ์–ด๋–ป๊ฒŒ ์ ์šฉ๋  ์ˆ˜ ์žˆ๋Š” ์ง€๊ฐ€ ์ด ๋…ผ๋ฌธ์˜ ๋์—์„œ ์ƒ์„ธํžˆ ์„ค๋ช…๋œ๋‹ค.Abstract ------------------------------------------------------------------ i Contents ---------------------------------------------------------------- vi List of Figures ---------------------------------------------------------- xi List of Tables ----------------------------------------------------------- xx List of Abbreviations ------------------------------------------------ xxii Chapter 1. Introduction --------------------------------------------- 1 1.1. Visual Prosthetic System --------------------------------------- 2 1.1.1. Current Issues ------------------------------------------------- 2 1.1.1.1. Substrate Materials ---------------------------------------- 3 1.1.1.2. Electrode Configurations --------------------------------- 5 1.1.1.3. External Hardware ----------------------------------------- 6 1.1.1.4. Other Issues ------------------------------------------------- 7 1.2. Suggested Visual Prosthetic System ------------------------ 8 1.3. Four Motivations ---------------------------------------------- 10 1.4. Proposed Approaches ---------------------------------------- 11 1.4.1. Cyclic Olefin Polymer (COP) ------------------------------ 11 1.4.2. Penta-Polar Stimulation ----------------------------------- 13 1.4.3. Implantable Camera --------------------------------------- 16 1.4.4. Handheld Remote Controller ---------------------------- 18 1.5. Objectives of this Dissertation ------------------------------ 20 Chapter 2. Materials and Methods ----------------------------- 23 2.1. COP-Based Fabrication and Encapsulation -------------- 24 2.1.1. Overview ----------------------------------------------------- 24 2.1.2. Simple Fabrication Process ------------------------------- 24 2.1.3. Depth-Type Microprobe ---------------------------------- 26 2.1.3.1. Design ----------------------------------------------------- 26 2.1.3.2. Characterization ----------------------------------------- 27 2.1.3.3. In Vivo Neural Signal Recording ---------------------- 30 2.1.4. COP Encapsulation ---------------------------------------- 31 2.1.4.1. In Vitro Reliability Test ---------------------------------- 33 2.2. Penta-Polar Stimulation ------------------------------------- 34 2.2.1. Overview ---------------------------------------------------- 34 2.2.2. Design and Fabrication ----------------------------------- 35 2.2.2.1. Integrated Circuit (IC) Design ------------------------- 35 2.2.2.2. Surface-Type Electrode Fabrication ------------------ 38 2.2.3. Evaluations -------------------------------------------------- 39 2.2.3.1. Focused Electric Field Measurement ---------------- 42 2.2.3.2. Steered Electric Field Measurement ----------------- 42 2.3. Implantable Camera ----------------------------------------- 43 2.3.1. Overview ---------------------------------------------------- 43 2.3.2. Design and Fabrication ----------------------------------- 43 2.3.2.1. Circuit Design -------------------------------------------- 43 2.3.2.2. Wireless Communication Program ------------------ 46 2.3.2.3. Epoxy Coating and Elastomer Sealing -------------- 47 2.3.3. Evaluations ------------------------------------------------- 50 2.3.3.1. Wireless Image Acquisition --------------------------- 50 2.3.3.2. Signal-to-Noise Ratio (SNR) Measurement -------- 52 2.4. Multi-Functional Handheld Remote Controller --------- 53 2.4.1. Overview ---------------------------------------------------- 53 2.4.2. Design and Fabrication ----------------------------------- 53 2.4.2.1. Hardware Description ---------------------------------- 53 2.4.2.2. Software Description ----------------------------------- 57 2.4.3. Evaluations -------------------------------------------------- 57 2.4.3.1. In Vitro Evaluation -------------------------------------- 57 2.4.3.2. In Vivo Evaluation --------------------------------------- 59 Chapter 3. Results ------------------------------------------------- 61 3.1. COP-Based Fabrication and Encapsulation ------------- 62 3.1.1. Fabricated Depth-Type Microprobe ------------------- 62 3.1.1.1. Electrochemical Impedance -------------------------- 63 3.1.1.2. Mechanical Characteristics --------------------------- 64 3.1.1.3. In Vivo Neural Signal Recording --------------------- 66 3.1.2. COP Encapsulation --------------------------------------- 68 3.1.2.1. In Vitro Reliability Test --------------------------------- 68 3.2. Penta-Polar Stimulation ------------------------------------ 70 3.2.1. Fabricated IC and Surface-Type Electrodes ---------- 70 3.2.2. Evaluations ------------------------------------------------- 73 3.2.2.1. Focused Electric Field Measurement --------------- 73 3.2.2.2. Steered Electric Field Measurement ---------------- 75 3.3. Implantable Camera ---------------------------------------- 76 3.3.1. Fabricated Implantable Camera ----------------------- 76 3.3.2. Evaluations ------------------------------------------------ 77 3.3.2.1. Wireless Image Acquisition -------------------------- 77 3.3.2.2. SNR Measurement ------------------------------------ 78 3.4. Multi-Functional Handheld Remote Controller ------- 80 3.4.1. Fabricated Remote Controller ------------------------- 80 3.4.2. Evaluations ------------------------------------------------ 81 3.4.2.1. In Vitro Evaluation ------------------------------------ 81 3.4.2.2. In Vivo Evaluation ------------------------------------- 83 Chapter 4. Discussions ------------------------------------------ 86 4.1. COP-Based Fabrication and Encapsulation ------------ 87 4.1.1. Fabrication Process and Fabricated Devices -------- 87 4.1.2. Encapsulation and Optical Transparency ------------ 89 4.2. Penta-Polar Stimulation------------------------------------ 99 4.2.1. Designed IC and Electrode Configurations --------- 99 4.2.2. Virtual Channels in Two Dimensions ---------------- 101 4.3. Implantable Camera -------------------------------------- 102 4.3.1. Enhanced Reliability by Epoxy Coating ------------- 106 4.4. Multi-Functional Handheld Remote Controller ------ 107 4.4.1. Brief Discussions of the Two Extra Functions ------ 108 4.5. Totally Implantable Visual Prosthetic System --------- 113 Chapter 5. Conclusion ------------------------------------------ 117 References -------------------------------------------------------- 121 Supplements ------------------------------------------------------ 133 ๊ตญ๋ฌธ ์ดˆ๋ก ----------------------------------------------------------- 143Docto

    A cross-layer middleware architecture for time and safety critical applications in MANETs

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    Mobile Ad hoc Networks (MANETs) can be deployed instantaneously and adaptively, making them highly suitable to military, medical and disaster-response scenarios. Using real-time applications for provision of instantaneous and dependable communications, media streaming, and device control in these scenarios is a growing research field. Realising timing requirements in packet delivery is essential to safety-critical real-time applications that are both delay- and loss-sensitive. Safety of these applications is compromised by packet loss, both on the network and by the applications themselves that will drop packets exceeding delay bounds. However, the provision of this required Quality of Service (QoS) must overcome issues relating to the lack of reliable existing infrastructure, conservation of safety-certified functionality. It must also overcome issues relating to the layer-2 dynamics with causal factors including hidden transmitters and fading channels. This thesis proposes that bounded maximum delay and safety-critical application support can be achieved by using cross-layer middleware. Such an approach benefits from the use of established protocols without requiring modifications to safety-certified ones. This research proposes ROAM: a novel, adaptive and scalable cross-layer Real-time Optimising Ad hoc Middleware framework for the provision and maintenance of performance guarantees in self-configuring MANETs. The ROAM framework is designed to be scalable to new optimisers and MANET protocols and requires no modifications of protocol functionality. Four original contributions are proposed: (1) ROAM, a middleware entity abstracts information from the protocol stack using application programming interfaces (APIs) and that implements optimisers to monitor and autonomously tune conditions at protocol layers in response to dynamic network conditions. The cross-layer approach is MANET protocol generic, using minimal imposition on the protocol stack, without protocol modification requirements. (2) A horizontal handoff optimiser that responds to time-varying link quality to ensure optimal and most robust channel usage. (3) A distributed contention reduction optimiser that reduces channel contention and related delay, in response to detection of the presence of a hidden transmitter. (4) A feasibility evaluation of the ROAM architecture to bound maximum delay and jitter in a comprehensive range of ns2-MIRACLE simulation scenarios that demonstrate independence from the key causes of network dynamics: application setting and MANET configuration; including mobility or topology. Experimental results show that ROAM can constrain end-to-end delay, jitter and packet loss, to support real-time applications with critical timing requirements

    Measurement and modelling of TCP downstream throughput dependence on SNR in an IEEE802.11b WLAN system

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    This paper presents our study on the dependence of TCP downstream throughput (TCPdownT) on signal to noise ratio (SNR) for multiple users in an IEEE 802.11b Wireless Local Area Network (WLAN) system. The study was carried out in small offices, open corridors and free space environments using an infrastructure based IEEE 802.11b WLAN while transmitting different quality of service (QoS) traffic all corresponding to different wireless multimedia tags. Models describing TCPdownT against SNR for different signal categories were statistically generated and validated. Our findings show a large variation in the throughput behaviour of the IEEE 802.11b WLAN system for the different categories of signals. We observed RMS errors of 0.938012ย Mbps, 1.047012ย Mbps, 0.65833ย Mbps and 0.452927ย Mbps for the general (all SNR) model, strong signals model, grey signals model and weak signals model respectively which were much lower than that of similar models with which they were compared. Comparing our results with a previous work on TCP upstream throughput showed that it is more accurate to investigate upstream and downstream throughput separately. Our models enable network designers and installers to predict the TCPdownT without the need to measure additional parameters other than the observed SNR which is already part of the normal network installation process. Keywords: TCP downstream throughput, Signal to noise ratio, Empirical model, IEEE802.11b, WLAN

    Measurement and modelling of TCP downstream throughput dependence on SNR in an IEEE802.11b WLAN system

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    AbstractThis paper presents our study on the dependence of TCP downstream throughput (TCPdownT) on signal to noise ratio (SNR) for multiple users in an IEEE 802.11b Wireless Local Area Network (WLAN) system. The study was carried out in small offices, open corridors and free space environments using an infrastructure based IEEE 802.11b WLAN while transmitting different quality of service (QoS) traffic all corresponding to different wireless multimedia tags. Models describing TCPdownT against SNR for different signal categories were statistically generated and validated. Our findings show a large variation in the throughput behaviour of the IEEE 802.11b WLAN system for the different categories of signals. We observed RMS errors of 0.938012Mbps, 1.047012Mbps, 0.65833Mbps and 0.452927Mbps for the general (all SNR) model, strong signals model, grey signals model and weak signals model respectively which were much lower than that of similar models with which they were compared. Comparing our results with a previous work on TCP upstream throughput showed that it is more accurate to investigate upstream and downstream throughput separately. Our models enable network designers and installers to predict the TCPdownT without the need to measure additional parameters other than the observed SNR which is already part of the normal network installation process
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