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Author Lin Min Min Myint,
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Add the result to your basket Make a suggestion Refine your search Apply to external sourcesReprinted Collection. An inter-track interference mitigation technique using partial ITI estimation in patterned media storageh(Reprint) / Myint, Lin Min Min / New York : Institute of Electrical and Electronics Engineers - 2009
Collection Title: Reprinted Collection Title : An inter-track interference mitigation technique using partial ITI estimation in patterned media storageh(Reprint) Material Type: printed text Authors: Myint, Lin Min Min, Author ; Pornchai Supnithi, Associated Name ; Prinya Tantaswadi, Associated Name Publisher: New York : Institute of Electrical and Electronics Engineers Publication Date: 2009 Pagination: 4 p. Layout: ill. Size: 30 cm. Price: 50 Baht General note: Inter-track interference Languages : English (eng) Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=16278 Reprinted Collection. An inter-track interference mitigation technique using partial ITI estimation in patterned media storageh(Reprint) [printed text] / Myint, Lin Min Min, Author ; Pornchai Supnithi, Associated Name ; Prinya Tantaswadi, Associated Name . - New York : Institute of Electrical and Electronics Engineers, 2009 . - 4 p. : ill. ; 30 cm.
50 Baht
Inter-track interference
Languages : English (eng)
Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=16278 Hold
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Barcode Call number Media type Location Section Status 32002000209799 REP545 2009 c.2 Reprinted Graduate Library Reprint Shelf Available 32002000209781 REP545 2009 c.1 Reprinted Main Library Reprint Shelf Available
Collection Title: Reprinted Collection Title : Iterated viterbi detection methods for a 2-D bit patterned media channelh Material Type: printed text Authors: Myint, Lin Min Min, Author ; Pornchai Supnithi, Associated Name ; Prinya Tantaswadi, Associated Name Pagination: 4 p. Layout: ill. Size: 30 cm. Price: 50 Baht General note: Viterbi algorithm Languages : English (eng) Descriptors: [LCSH]Optical communications Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=17990 Reprinted Collection. Iterated viterbi detection methods for a 2-D bit patterned media channelh [printed text] / Myint, Lin Min Min, Author ; Pornchai Supnithi, Associated Name ; Prinya Tantaswadi, Associated Name . - [s.d.] . - 4 p. : ill. ; 30 cm.
50 Baht
Viterbi algorithm
Languages : English (eng)
Descriptors: [LCSH]Optical communications Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=17990 Hold
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Barcode Call number Media type Location Section Status 32002000261055 REP613 2010 c.1 Reprinted Graduate Library Reprint Shelf Available 32002000261063 REP613 2010 c.2 Reprinted Main Library Reprint Shelf Available
Collection Title: SIU RS Title : M-Learning Content Production Platform: A Case Study on Software Testing Course Material Type: printed text Authors: May Thit, Author ; Aekavute Sujarae, Associated Name ; Myint, Lin Min Min, Associated Name Publisher: Bangkok: Shinawatra University Publication Date: 2015 Pagination: ix, 74 p. Layout: ill, tables Size: 30 cm. Price: 500.00 General note: SIU RS: SOIT-MSIT-2015-01
Research Study. [M.S.[Information Technology]]. - Shinawatra University. 2015Languages : English (eng) Descriptors: [LCSH]Learning -- Case studies
[LCSH]Learning -- Evaluation
[LCSH]Mobile learningKeywords: M-Learning Application,
Paper-based theory content,
Content creation tool,
Learning Management System,
Mobile Learning ContentAbstract: Multinational corporations such as TESCOM, BRENNTAG, KAPLAN and SHANGRILA HOTEL, more or less face the same challenges in providing face-to-face training for their employees located across the globe. Many organizations looked for a solution to convert and delivery face-to-face training content in a form of multimedia mobile learning content utilizing content authoring tools and mobile learning application.
In this study, the development of multimedia mobile leaning authoring tool called Book Builder is described. The tool enables conversion of classroom based training materials into online interactive contents. The use of interactive elements and media can help enhance learning and knowledge retention. Together with the suitable Learning Management System, the tool produces engaging and interactive mobile learning content which can be distributed to iOS based mobile learning platform.
Furthermore, the evaluation questionnaires on the Book Builder tool were given to participants at the workshop on Courseware Multimedia Development in Singapore. The evaluation results indicate that the respondents generally preferred ease of use over powerful functions. In addition, the results point out some commonalities among the features, and the features of the Book Builder which are highly helpful.Curricular : BSCS/MSIT Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=26232 SIU RS. M-Learning Content Production Platform: A Case Study on Software Testing Course [printed text] / May Thit, Author ; Aekavute Sujarae, Associated Name ; Myint, Lin Min Min, Associated Name . - [S.l.] : Bangkok: Shinawatra University, 2015 . - ix, 74 p. : ill, tables ; 30 cm.
500.00
SIU RS: SOIT-MSIT-2015-01
Research Study. [M.S.[Information Technology]]. - Shinawatra University. 2015
Languages : English (eng)
Descriptors: [LCSH]Learning -- Case studies
[LCSH]Learning -- Evaluation
[LCSH]Mobile learningKeywords: M-Learning Application,
Paper-based theory content,
Content creation tool,
Learning Management System,
Mobile Learning ContentAbstract: Multinational corporations such as TESCOM, BRENNTAG, KAPLAN and SHANGRILA HOTEL, more or less face the same challenges in providing face-to-face training for their employees located across the globe. Many organizations looked for a solution to convert and delivery face-to-face training content in a form of multimedia mobile learning content utilizing content authoring tools and mobile learning application.
In this study, the development of multimedia mobile leaning authoring tool called Book Builder is described. The tool enables conversion of classroom based training materials into online interactive contents. The use of interactive elements and media can help enhance learning and knowledge retention. Together with the suitable Learning Management System, the tool produces engaging and interactive mobile learning content which can be distributed to iOS based mobile learning platform.
Furthermore, the evaluation questionnaires on the Book Builder tool were given to participants at the workshop on Courseware Multimedia Development in Singapore. The evaluation results indicate that the respondents generally preferred ease of use over powerful functions. In addition, the results point out some commonalities among the features, and the features of the Book Builder which are highly helpful.Curricular : BSCS/MSIT Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=26232 Hold
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Barcode Call number Media type Location Section Status 32002000507051 SIU RS: SOIT-MSIT-2015-01 c.1 SIU Research Study Graduate Library Thesis Corner Available 32002000591048 SIU RS: SOIT-MSIT-2015-01 c.2 SIU Research Study Graduate Library Thesis Corner Available
Collection Title: SIU Thesis Title : The Application Research of Cellular Neural Networks (CNN) in Image Processing Material Type: printed text Authors: Gangyi Hu, Author ; Sumeth Yuenyong, Associated Name ; Myint, Lin Min Min, Associated Name Publisher: Bangkok: Shinawatra University Publication Date: 2017 Pagination: x, 172 p. Layout: ill, Tables Size: 30 cm. Price: 500.00 General note: SIU THE: SOST-PhD-IT-2017-01
Thesis. [PhD [Information Technology]]. -- Shinawatra University, 2017Languages : English (eng) Descriptors: [LCSH]Genetic algorithms
[LCSH]Image processingKeywords: Cellular Neural Networks,
Image Processing,
Edge Detection,
Genetic Algorithm,
Denoising,
Target Protection,
Chaos,
Encryption,
Asymmetric AlgorithmAbstract: The cellular neural networks (CNN) are composed of many cell units which are the local connection. Each cell is consisting of linear and nonlinear circuits. This structure can be realized as very large-scale integrated circuit (VLSI), which can be used in large-scale parallel computing. Therefore, the cellular neural networks can be applied to solve the problem such as image processing, signal processing, robot and biological vision. It is one of the hot spots in the field of neural networks.
This thesis mainly studies the practical problems of image processing application, and it uses the advantages of cellular neural networks, such as nonlinear and high-speed, real-time parallel computing. And then it is combined with the genetic training algorithm, filtering analysis, chaos theory and modern cryptography theory to solve some problems in image processing, which expands the application scope of cellular neural networks.
The main research works of this thesis are as below.
1) It reviews the basic concepts, background, development status, and hardware realization of the cellular neural networks, and then it analyzes the dynamic range and stability characteristics of the cellular neural networks and expounds the principle and significance of cellular neural networks for image processing.
2) In the research on edge detection for the infrared image. It studies the principle, purpose, and significance of infrared image edge detection, and then compared with the traditional target edge detection algorithm such as the Canny algorithm for the infrared image. At last, it discusses using the genetic algorithm with cellular neural networks for infrared image edge detection. It proposes an algorithm to get the cellular neural networks template parameters; this algorithm is based on subpopulation genetic algorithm. Through the optimum design of filial populations as well as the improvement of the parallel genetic offspring, it overcomes the disadvantages such as premature
convergence of simple genetic algorithm to create template parameters, and the fitness function is developed by using the Lyapunov function. The experiments show that this improved genetic algorithm combined with cellular neural networks is used to detect the edge of the infrared image, which can get the edge of infrared image accurately and quickly. This algorithm has fast convergence speed and accurate target edge detection.
3) The image denoising is an important research aspect in image processing, aiming at the contradiction between denoising and edge preserving information in the traditional denoising method. It first studies the noise model, the principle and the evaluation criteria of image denoising, then according to the characteristics of the three templates of cellular neural networks; it proposes an edge constraint adaptive filtering algorithm based on cellular neural networks for image denoising. In the process of designing the three templates separately in cellular neural networks, the control template references the advantage of spatial filtering denoising, it resembles spatial domain denoising filter. The feedback template sets as a matrix which generated by a high pass filter to achieve edge preservation. Thus, it can not only perform denoising but also can protect edges in an image. In the process of designing the threshold template, it uses the different gray levels in an image to achieve the threshold adjustment adaptively. The experiments show that this algorithm has best denoising effect for various image noise types. When comparing the edge protection effect with other denoising algorithms, it can protect the edge information very well. The Peak signal to noise ratio (PSNR) is also higher than other traditional denoising algorithms. This algorithm is mainly developing a new method for image denoising.
4) The image encryption is a vital part of image transmission and an important guarantee to prevent the leakage of image information. It introduces the principle of image encryption and the method of generating hyper chaotic system based on cellular neural networks, then using these hyper chaotic sequences from the chaotic system for image encryption. The image encryption mainly includes two steps, one is changing the image pixel position, and the other is replacing the pixel values. This algorithm is based on cellular neural networks six dimensional hyper chaotic systems. The main idea of
the algorithm is that the image encryption key is first to been input to the cellular neural networks system to generate six-dimensional chaotic sequences, and then encrypt the key by an asymmetric encryption algorithm. In the process of encryption image, firstly change the original image pixel positions according to the chaotic sequences, and then put the pixel shuffled image and the modified chaotic sequences through the XOR operation to replace the pixel value. Thus, it can get the final cipher image. The image decryption process is the reverse of the above two steps. This algorithm has two advantages. First, it realizes the encryption and protection of the image based on the hyper chaotic sequences generated by the high dimensional of cellular neural networks. Secondly, the key is encrypted by asymmetric encryption algorithm such as RSA algorithm. It can protect the key in the transmission process. The experimental results show that this algorithm can achieve low correlation between pixels, and its cipher image can also achieve high change rate of pixel ratio, high information entropy, and strong anti-hacking ability. Compared with other chaotic image encryption schemes, this algorithm has substantial practical value.Curricular : BSCS/MSIT/PhDT Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=27204 SIU Thesis. The Application Research of Cellular Neural Networks (CNN) in Image Processing [printed text] / Gangyi Hu, Author ; Sumeth Yuenyong, Associated Name ; Myint, Lin Min Min, Associated Name . - [S.l.] : Bangkok: Shinawatra University, 2017 . - x, 172 p. : ill, Tables ; 30 cm.
500.00
SIU THE: SOST-PhD-IT-2017-01
Thesis. [PhD [Information Technology]]. -- Shinawatra University, 2017
Languages : English (eng)
Descriptors: [LCSH]Genetic algorithms
[LCSH]Image processingKeywords: Cellular Neural Networks,
Image Processing,
Edge Detection,
Genetic Algorithm,
Denoising,
Target Protection,
Chaos,
Encryption,
Asymmetric AlgorithmAbstract: The cellular neural networks (CNN) are composed of many cell units which are the local connection. Each cell is consisting of linear and nonlinear circuits. This structure can be realized as very large-scale integrated circuit (VLSI), which can be used in large-scale parallel computing. Therefore, the cellular neural networks can be applied to solve the problem such as image processing, signal processing, robot and biological vision. It is one of the hot spots in the field of neural networks.
This thesis mainly studies the practical problems of image processing application, and it uses the advantages of cellular neural networks, such as nonlinear and high-speed, real-time parallel computing. And then it is combined with the genetic training algorithm, filtering analysis, chaos theory and modern cryptography theory to solve some problems in image processing, which expands the application scope of cellular neural networks.
The main research works of this thesis are as below.
1) It reviews the basic concepts, background, development status, and hardware realization of the cellular neural networks, and then it analyzes the dynamic range and stability characteristics of the cellular neural networks and expounds the principle and significance of cellular neural networks for image processing.
2) In the research on edge detection for the infrared image. It studies the principle, purpose, and significance of infrared image edge detection, and then compared with the traditional target edge detection algorithm such as the Canny algorithm for the infrared image. At last, it discusses using the genetic algorithm with cellular neural networks for infrared image edge detection. It proposes an algorithm to get the cellular neural networks template parameters; this algorithm is based on subpopulation genetic algorithm. Through the optimum design of filial populations as well as the improvement of the parallel genetic offspring, it overcomes the disadvantages such as premature
convergence of simple genetic algorithm to create template parameters, and the fitness function is developed by using the Lyapunov function. The experiments show that this improved genetic algorithm combined with cellular neural networks is used to detect the edge of the infrared image, which can get the edge of infrared image accurately and quickly. This algorithm has fast convergence speed and accurate target edge detection.
3) The image denoising is an important research aspect in image processing, aiming at the contradiction between denoising and edge preserving information in the traditional denoising method. It first studies the noise model, the principle and the evaluation criteria of image denoising, then according to the characteristics of the three templates of cellular neural networks; it proposes an edge constraint adaptive filtering algorithm based on cellular neural networks for image denoising. In the process of designing the three templates separately in cellular neural networks, the control template references the advantage of spatial filtering denoising, it resembles spatial domain denoising filter. The feedback template sets as a matrix which generated by a high pass filter to achieve edge preservation. Thus, it can not only perform denoising but also can protect edges in an image. In the process of designing the threshold template, it uses the different gray levels in an image to achieve the threshold adjustment adaptively. The experiments show that this algorithm has best denoising effect for various image noise types. When comparing the edge protection effect with other denoising algorithms, it can protect the edge information very well. The Peak signal to noise ratio (PSNR) is also higher than other traditional denoising algorithms. This algorithm is mainly developing a new method for image denoising.
4) The image encryption is a vital part of image transmission and an important guarantee to prevent the leakage of image information. It introduces the principle of image encryption and the method of generating hyper chaotic system based on cellular neural networks, then using these hyper chaotic sequences from the chaotic system for image encryption. The image encryption mainly includes two steps, one is changing the image pixel position, and the other is replacing the pixel values. This algorithm is based on cellular neural networks six dimensional hyper chaotic systems. The main idea of
the algorithm is that the image encryption key is first to been input to the cellular neural networks system to generate six-dimensional chaotic sequences, and then encrypt the key by an asymmetric encryption algorithm. In the process of encryption image, firstly change the original image pixel positions according to the chaotic sequences, and then put the pixel shuffled image and the modified chaotic sequences through the XOR operation to replace the pixel value. Thus, it can get the final cipher image. The image decryption process is the reverse of the above two steps. This algorithm has two advantages. First, it realizes the encryption and protection of the image based on the hyper chaotic sequences generated by the high dimensional of cellular neural networks. Secondly, the key is encrypted by asymmetric encryption algorithm such as RSA algorithm. It can protect the key in the transmission process. The experimental results show that this algorithm can achieve low correlation between pixels, and its cipher image can also achieve high change rate of pixel ratio, high information entropy, and strong anti-hacking ability. Compared with other chaotic image encryption schemes, this algorithm has substantial practical value.Curricular : BSCS/MSIT/PhDT Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=27204 Hold
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Barcode Call number Media type Location Section Status 32002000594497 SIU THE: SOST-PhD-IT-2017-01 c.1 SIU Thesis and Dissertation Graduate Library Thesis Corner Available 32002000594521 SIU THE: SOST-PhD-IT-2017-01 c.2 SIU Thesis and Dissertation Graduate Library Thesis Corner Available
Collection Title: SIU Thesis Title : Iterative processing for bit patterned media storage Material Type: printed text Authors: Myint, Lin Min Min, Author ; Pornchai Supnithi, Associated Name ; Supachok Wiriyacosol, Associated Name ; Thiti Vatcarasintopchai, Associated Name Publisher: Bangkok : Shinawatra University Publication Date: 2011 Pagination: xi, 112 p. charts, tables Size: 30 cm. Price: 500 Baht General note: photocopy Languages : English (eng) Descriptors: [LCSH]Mass media -- Research -- Methodology
[LCSH]media adaptationCurricular : BSCS/MSIT/PhDT Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=21128 SIU Thesis. Iterative processing for bit patterned media storage [printed text] / Myint, Lin Min Min, Author ; Pornchai Supnithi, Associated Name ; Supachok Wiriyacosol, Associated Name ; Thiti Vatcarasintopchai, Associated Name . - Bangkok : Shinawatra University, 2011 . - xi, 112 p. charts, tables ; 30 cm.
500 Baht
photocopy
Languages : English (eng)
Descriptors: [LCSH]Mass media -- Research -- Methodology
[LCSH]media adaptationCurricular : BSCS/MSIT/PhDT Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=21128 Hold
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Barcode Call number Media type Location Section Status 32002000509370 SIU THE SOIT-PhD-2011-01 c.3 SIU Thesis and Dissertation Graduate Library General Shelf Available 32002000326809 SIU THE SOIT-PhD 2011-01 SIU Thesis and Dissertation Graduate Library Thesis Corner Available 32002000509412 SIU THE SOIT-PhD-2011-01-c.2 SIU Thesis and Dissertation Main Library General Shelf Available
Collection Title: SIU Thesis Title : Optimization Approaches to Cost Effective Resource Management for Cloud-based IoT Applications Material Type: printed text Authors: Nay Myo Sandar, Author ; Myint, Lin Min Min, Associated Name ; Chaisiri Sivadon, Associated Name Publisher: กรุงเทพฯ: มหาวิทยาลัยชินวัตร Publication Date: 2017 Pagination: x, 124 p. Layout: ill, tables Size: 30 cm. Price: 500.00 General note: SIU THE: SOST-PhD-IT-2017-02
Thesis. [PhD [Information Technology]]. -- Shinawatra University, 2017Languages : English (eng) Descriptors: [LCSH]Internet of Things
[LCSH]Wireless Sensor NetworksKeywords: Internet of Things (IoT),
Wireless Sensor Network (WSN),
Cloud Computing,
Aggregator Approach,
Software Defined Network Approach,
Optimization ApproachesAbstract: Over the last decade, the growing popularity of various devices are increasingly connected to the Internet and led to the vision of Internet of Things (IoT). In IoT, wireless sensor networks (WSNs) deploy sensors to gather data around their surroundings. Nowadays, Cloud computing can support scalable storage and processing task for large sensor data. However, sensors can encounter with bandwidth constraint and memory constraint to directly transfer data to the cloud. This thesis proposes a framework using aggregator approach and software defined network (SDN) approach for cloud-based IoT applications. The aggregator approach provides aggregators to buffer data from sensors and forward to the cloud. The SDN approach provides scalable bandwidth and programmable network paths to deliver data between aggregators and cloud. Applying aggregator and SDN approaches in the framework can achieve the expected seamless network connectivity between numerous sensors and cloud.
Since the proposed framework is designed by aggregator approach, SDN approach, and cloud computing, we mainly focus on achieving cost effectiveness for capacity planning of aggregators, provisioning of SDN bandwidth and cloud resources. The capacity planning of aggregators is a critical issue to purchase the optimal number of aggregators from third party providers for handling data from multiple sensors while the investment is minimized. Then, Internet Service Provider (ISP) provides SDN bandwidth and cloud providers provide cloud resources with reservation and on-demand options. The on-demand option allows consumers to dynamically provision resources anytime but it leads to higher cost. The reservation option is cheaper but consumers must prepay specific resources for long term plan before the demand is known. Without knowing demand, provisioning resources with reservation option could experience underprovisioning or overprovisioning. To tackle resource management problems, this thesis proposes several algorithms in three use cases of cloud-based IoT applications, i.e., video monitoring or surveillance system, meteorological monitoring system, and healthcare monitoring system.
First, an optimal on-demand cloud resource provisioning algorithm is proposed for video monitoring or surveillance system. This algorithm applies binary integer programming to allocate video streams from cameras among cloud providers with on-demand option. The numerical results can choose optimal cloud providers where video streams are allocated with the minimum cost.
Second, a joint resource management algorithm is proposed for meteorological monitoring system. This algorithm applies deterministic multi-server queuing theory for capacity planning of aggregators to provide sufficient service to data from meteorological sensors while reducing the investment and deterministic integer programming to provision the precise amount of cloud resources with reservation option based on data demand certainty for stationary sensors. The numerical results can determine optimal number of aggregators and provision optimal amount of cloud resources with the minimum total cost.
Finally, a unified resource management algorithm is proposed for patients’ healthcare monitoring in hospital. This algorithm applies Markov multi-server queuing theory for capacity planning of aggregators to efficiently operate data from body sensors attached to patients within hospital while investment is reduced and two stage stochastic programming to achieve the best advance reservation of SDN bandwidth and cloud resources under data demand uncertainty for mobile sensors. The numerical results can provide the minimum total cost by allocating optimal number of aggregators, amount of SDN bandwidth and cloud resources.
As aforementioned, several algorithms are proposed to minimize the total cost for resource management problems in three usage scenarios of cloud-based IoT applications. In practice, the proposed algorithms can be applicable with the minimum total cost for any cloud-based IoT applications.Curricular : BSCS/MSIT/PhDT Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=27301 SIU Thesis. Optimization Approaches to Cost Effective Resource Management for Cloud-based IoT Applications [printed text] / Nay Myo Sandar, Author ; Myint, Lin Min Min, Associated Name ; Chaisiri Sivadon, Associated Name . - [S.l.] : กรุงเทพฯ: มหาวิทยาลัยชินวัตร, 2017 . - x, 124 p. : ill, tables ; 30 cm.
500.00
SIU THE: SOST-PhD-IT-2017-02
Thesis. [PhD [Information Technology]]. -- Shinawatra University, 2017
Languages : English (eng)
Descriptors: [LCSH]Internet of Things
[LCSH]Wireless Sensor NetworksKeywords: Internet of Things (IoT),
Wireless Sensor Network (WSN),
Cloud Computing,
Aggregator Approach,
Software Defined Network Approach,
Optimization ApproachesAbstract: Over the last decade, the growing popularity of various devices are increasingly connected to the Internet and led to the vision of Internet of Things (IoT). In IoT, wireless sensor networks (WSNs) deploy sensors to gather data around their surroundings. Nowadays, Cloud computing can support scalable storage and processing task for large sensor data. However, sensors can encounter with bandwidth constraint and memory constraint to directly transfer data to the cloud. This thesis proposes a framework using aggregator approach and software defined network (SDN) approach for cloud-based IoT applications. The aggregator approach provides aggregators to buffer data from sensors and forward to the cloud. The SDN approach provides scalable bandwidth and programmable network paths to deliver data between aggregators and cloud. Applying aggregator and SDN approaches in the framework can achieve the expected seamless network connectivity between numerous sensors and cloud.
Since the proposed framework is designed by aggregator approach, SDN approach, and cloud computing, we mainly focus on achieving cost effectiveness for capacity planning of aggregators, provisioning of SDN bandwidth and cloud resources. The capacity planning of aggregators is a critical issue to purchase the optimal number of aggregators from third party providers for handling data from multiple sensors while the investment is minimized. Then, Internet Service Provider (ISP) provides SDN bandwidth and cloud providers provide cloud resources with reservation and on-demand options. The on-demand option allows consumers to dynamically provision resources anytime but it leads to higher cost. The reservation option is cheaper but consumers must prepay specific resources for long term plan before the demand is known. Without knowing demand, provisioning resources with reservation option could experience underprovisioning or overprovisioning. To tackle resource management problems, this thesis proposes several algorithms in three use cases of cloud-based IoT applications, i.e., video monitoring or surveillance system, meteorological monitoring system, and healthcare monitoring system.
First, an optimal on-demand cloud resource provisioning algorithm is proposed for video monitoring or surveillance system. This algorithm applies binary integer programming to allocate video streams from cameras among cloud providers with on-demand option. The numerical results can choose optimal cloud providers where video streams are allocated with the minimum cost.
Second, a joint resource management algorithm is proposed for meteorological monitoring system. This algorithm applies deterministic multi-server queuing theory for capacity planning of aggregators to provide sufficient service to data from meteorological sensors while reducing the investment and deterministic integer programming to provision the precise amount of cloud resources with reservation option based on data demand certainty for stationary sensors. The numerical results can determine optimal number of aggregators and provision optimal amount of cloud resources with the minimum total cost.
Finally, a unified resource management algorithm is proposed for patients’ healthcare monitoring in hospital. This algorithm applies Markov multi-server queuing theory for capacity planning of aggregators to efficiently operate data from body sensors attached to patients within hospital while investment is reduced and two stage stochastic programming to achieve the best advance reservation of SDN bandwidth and cloud resources under data demand uncertainty for mobile sensors. The numerical results can provide the minimum total cost by allocating optimal number of aggregators, amount of SDN bandwidth and cloud resources.
As aforementioned, several algorithms are proposed to minimize the total cost for resource management problems in three usage scenarios of cloud-based IoT applications. In practice, the proposed algorithms can be applicable with the minimum total cost for any cloud-based IoT applications.Curricular : BSCS/MSIT/PhDT Record link: http://libsearch.siu.ac.th/siu/opac_css/index.php?lvl=notice_display&id=27301 Hold
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Barcode Call number Media type Location Section Status 32002000595163 SIU THE: SOST-PhD-IT-2017-02 c.1 SIU Thesis and Dissertation Graduate Library Thesis Corner Available 32002000595155 SIU THE: SOST-PhD-IT-2017-02 c.2 SIU Thesis and Dissertation Graduate Library Thesis Corner Available
