Browsing by Author "Lin, Yi-Shan"

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A Comprehensive Study on the Internet of Underwater Things: Applications, Challenges, and Channel Models
(2017-07-01)
Kao, Chien-Chi
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Lin, Yi-Shan
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Wu, Geng-De
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Huang, Chun-Ju
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資訊工程學系
The Internet of Underwater Things (IoUT) is a novel class of Internet of Things (IoT), and is defined as the network of smart interconnected underwater objects. IoUT is expected to enable various practical applications, such as environmental monitoring, underwater exploration, and disaster prevention. With these applications, IoUT is regarded as one of the potential technologies toward developing smart cities. To support the concept of IoUT, Underwater Wireless Sensor Networks (UWSNs) have emerged as a promising network system. UWSNs are different from the traditional Territorial Wireless Sensor Networks (TWSNs), and have several unique properties, such as long propagation delay, narrow bandwidth, and low reliability. These unique properties would be great challenges for IoUT. In this paper, we provide a comprehensive study of IoUT, and the main contributions of this paper are threefold: (1) we introduce and classify the practical underwater applications that can highlight the importance of IoUT; (2) we point out the differences between UWSNs and traditional TWSNs, and these differences are the main challenges for IoUT; and (3) we investigate and evaluate the channel models, which are the technical core for designing reliable communication protocols on IoUT.
A Hybrid CPU/GPU Pattern-Matching Algorithm for Deep Packet Inspection
(2015-10-05)
Lee, Chun-Liang
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Lin, Yi-Shan
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Chen, Yaw-Chung
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資訊工程學系
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Department of Computer Science
The large quantities of data now being transferred via high-speed networks have made deep packet inspection indispensable for security purposes. Scalable and low-cost signature-based network intrusion detection systems have been developed for deep packet inspection for various software platforms. Traditional approaches that only involve central processing units (CPUs) are now considered inadequate in terms of inspection speed. Graphic processing units (GPUs) have superior parallel processing power, but transmission bottlenecks can reduce optimal GPU efficiency. In this paper we describe our proposal for a hybrid CPU/GPU pattern-matching algorithm (HPMA) that divides and distributes the packet-inspecting workload between a CPU and GPU. All packets are initially inspected by the CPU and filtered using a simple pre-filtering algorithm, and packets that might contain malicious content are sent to the GPU for further inspection. Test results indicate that in terms of random payload traffic, the matching speed of our proposed algorithm was 3.4 times and 2.7 times faster than those of the AC-CPU and AC-GPU algorithms, respectively. Further, HPMA achieved higher energy efficiency than the other tested algorithms.
Internet of Underwater Things: Challenges and Routing Protocols
(2018-01-01)
Liou, En-Cheng
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Kao, Chien-Chi
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Chang, Ching-Hao
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Lin, Yi-Shan
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Huang, Chun-Ju
The Internet of Underwater Things (IoUT) is a novel class of Internet of Things (IoT) that enables practical applications toward developing smart cities. Underwater Wireless Sensor Network (UWSN) shows great potential for the future but also poses new challenges for IoUT. In addition, routing protocol will play a major role in handling how to forward data among the substantial number of"things". In this paper, we call attention to the challenges for IoUT, provide an exhaustive investigation of cutting-edge routing protocol and find the connection between the challenges and routing protocols for IoUT.
TAAI 2011 COMPUTER-GAME TOURNAMENTS
(2011-12-01)
Lin, Yi-Shan
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Wu, I-Chen
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Yen, Shi-Jim
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資訊工程學系
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Department of Computer Science
THE MAN-MACHINE CONNECT6 CHAMPIONSHIP 2011
(2011-06-01)
Wu, I-Chen
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Lin, Yi-Shan
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Tsai, Hsin-Ti
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Lin, Ping-Hung
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資訊工程學系