Hsin-Hung Cho

Dr. Hsin-Hung Cho

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Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 August 2019 in IEEE Access
Verified
Journal Article
Open access
Fan-Hsun TsengFan-Hsun Tseng
Fan-Hsun Tseng
HCHsin-Hung Cho
Hsin-Hung Cho
HWHsin-Te Wu
Hsin-Te Wu
With the growth of the human population comes the constantly rising demand for agricultural products. Nevertheless, as the world experiences climate change, many crops are often damaged by weather conditions.This study utilizes Intelligent Agriculture IoT equipment to monitor the environmental factors on a farm. The collected data underwent 3D cluster analysis to yield analysis of the environmental factors of that farm. The proposed scheme bears the following features: (1) data normalization is achieved via the combination of moving average and average variance; (2) we applied 3D cluster analysis to analyze the relation between environmental factors and subsequently examine the rules of thumb held by the farmers; (3) the system determines whether a selected crop has been placed in the appropriate cluster; and (4) the system sets a critical value in the cluster based on future environments and provides advice on whether a crop is suitable for the farm. We placed Intelligent Agriculture IoT equipment in the farm for monitoring purposes and ran an actual-scenario analysis using the algorithm in our study; results confirm that our proposed scheme is indeed feasible.
1 September 2014 in IET Wireless Sensor Systems
Verified
Journal Article
Open access
PDF file
HCHsin-Hung Cho
Hsin-Hung Cho
CCChi‐Yuan Chen
Chi‐Yuan Chen
TSTimothy K. Shih
Timothy K. Shih
HCHan‐Chieh Chao
Han‐Chieh Chao
Underwater wireless sensor networks (UWSNs) have recently received a significant amount of attention. Since they have delay/disruption‐tolerant networks (DTNs) characteristics, the design of any UWSN scheme must take DTN influences into account, especially in routing protocols. Many researchers have proposed various DTN routing techniques for different types of DTN routing schemes in UWSNs. The authors survey state‐of‐the‐art DTN routing protocols, and use the definition of DTN to classify these proposals into scheduled contact, opportunistic contact and predicted contact. Furthermore, the authors analyse the detailed information in order to draw up a comparison table and also expect to inspire more research into this topic in the future.
29 September 2020 in IEEE Internet of Things Journal
Verified
Journal Article
Closed access
HCHsin-Hung Cho
Hsin-Hung Cho
HWHsin-Te Wu
Hsin-Te Wu
Chin-Feng LaiChin-Feng Lai
Chin-Feng Lai
TSTimothy K. Shih
Timothy K. Shih
Fan-Hsun TsengFan-Hsun Tseng
Fan-Hsun Tseng
Wireless rechargeable sensor network was proposed to extend the lifetime of wireless sensor network. In this paper, a charger is combined together with a self-propelled vehicle to provide a more flexible result of charger deployment. The dynamic chargers path selection problem is defined and mapped into the traveling salesman problem. Four metaheuristic algorithms for Internet of Things (IoT) applications are designed, and the higher fitness value between the charging path and the number of dead IoT device is achieved. However, metaheuristic approaches may spend more time on searching solutions so that many IoT devices overuse limited power and fail to be charged for a long time, leading to power exhaustion. In this paper, edge computing technique is applied to accelerate the obtainment of charging paths with the well-defined edge/centralized unit switching. Moreover, to assure the calculated path trustworthy and will not be tampered with, the blockchain technology is adopted. The proposed architecture maintains a high-level information credibility while transmitting the information of charging paths within cloud and edge. The simulation results showed that the proposed method is capable of achieving better charging efficiency and less deployment cost.
4 January 2019 in Peer-to-Peer Networking and Applications
Verified
Journal Article
Closed access
PDF file
CZCong Zhang
Cong Zhang
HCHsin-Hung Cho
Hsin-Hung Cho
Chi-Yuan ChenChi-Yuan Chen
Chi-Yuan Chen
7 April 2021 in Mobile Networks and Applications
Verified
Journal Article
Closed access
PDF file
MTMin-Yan Tsai
Min-Yan Tsai
HCHsin-Hung Cho
Hsin-Hung Cho
1 February 2017 in Enterprise Information Systems
Verified
Journal Article
Closed access
Fan-Hsun TsengFan-Hsun Tseng
Fan-Hsun Tseng
HCHsin-Hung Cho
Hsin-Hung Cho
KCKai-Di Chang
Kai-Di Chang
JLJheng-Cong Li
Jheng-Cong Li
TSTimothy K. Shih
Timothy K. Shih
Nowadays Internet applications have become more complicated that mobile device needs more computing resources for shorter execution time but it is restricted to limited battery capacity. Mobile cloud computing (MCC) is emerged to tackle the finite resource problem of mobile device. MCC offloads the tasks and jobs of mobile devices to cloud and fog environments by using offloading scheme. It is vital to MCC that which task should be offloaded and how to offload efficiently. In the paper, we formulate the offloading problem between mobile device and cloud data center and propose two algorithms based on application-oriented for minimum execution time, i.e. the Minimum Offloading Time for Mobile device (MOTM) algorithm and the Minimum Execution Time for Cloud data center (METC) algorithm. The MOTM algorithm minimizes offloading time by selecting appropriate offloading links based on application categories. The METC algorithm minimizes execution time in cloud data center by selecting virtual and physical machines with corresponding resource requirements of applications. Simulation results show that the proposed mechanism not only minimizes total execution time for mobile devices but also decreases their energy consumption.