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Dive into the research topics where Young-Long Chen is active.

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Featured researches published by Young-Long Chen.


Computer Communications | 2012

Energy efficiency analysis of a chain-based scheme via intra-grid for wireless sensor networks

Young-Long Chen; Jia-Sheng Lin

This study proposes the ideal energy mathematical model for the ideal PEGASIS architecture. Since the distance between nodes is the same, this ideal energy mathematical model can obtain a longer network lifetime than that of the PEGASIS architecture in a WSN. To achieve this objective, the intra-grid PEGASIS architecture, which is architecture that is based on the PEGASIS architecture, is proposed. In the proposed architecture, the sensor area is divided into several network grids, and the nodes of each network grid are deployed at random locations, and the nodes in the network grid are connected. Finally, all of the network grids are connected. The results of a simulation reveal that the energy consumption in each round in the ideal PEGASIS architecture almost equals that in the intra-grid PEGASIS architecture, but the PEGASIS architecture consumes the most energy in each round. Additionally, only a tiny difference is found between the network lifetime of the ideal PEGASIS and that of the intra-grid PEGASIS architecture, and the PEGASIS architecture has the shortest network lifetime.


Wireless Personal Communications | 2014

Improving Low-Energy Adaptive Clustering Hierarchy Architectures with Sleep Mode for Wireless Sensor Networks

Young-Long Chen; Neng-Chung Wang; Yi-Nung Shih; Jia-Sheng Lin

A wireless sensor network (WSN) is composed of sensor nodes whose energy is battery-powered. Therefore, the energy is limited. This paper aims to improve the energy efficiency of sensor nodes in order to extend the lifetime of WSNs. In this paper, we propose four new hierarchical clustering topology architectures: random cluster head and sub-cluster head (RCHSCH), random cluster head and max energy sub-cluster head (RCHMESCH), random cluster head and sub-cluster head with sleep mode (RCHSCHSM) and random cluster head and max energy sub-cluster head with sleep mode (RCHMESCHSM). Our proposed architectures involve three-layers and are based on low-energy adaptive clustering hierarchy (LEACH) architecture. Notably, RCHSCH can improve upon cluster head death within the LEACH architecture. In addition, we develop a sleep mode for sensor nodes based on correlations among sensor data within sub-clusters in RCHSCHSM. Thus, we can reduce the energy consumption of the sensor node and increase energy efficiency. From the simulation results, our proposed RCHSCH, RCHMESCH, RCHSCHSM and RCHMESCHSM architectures perform better than the LEACH architecture in terms of initial node death, the number of nodes alive and total residual energy. Furthermore, we find the performance of RCHMESCHSM architecture to be optimal in the set of all available architectures.


Computer Communications | 2008

Adaptive fuzzy-based rate management and power control in multimedia CDMA cellular systems

Young-Long Chen; Yung-Sheng Lin; Jyu-Wei Wang; Jyh-Horng Wen

In the literature, a number of fuzzy-based power control schemes have been proposed for systems with a single rate. However, emerging CDMA cellular systems are expected to include multimedia services. In such systems, different services have different quality of service (QoS) requirements, such as minimum transmission rates and tolerable delays. This paper introduces an adaptive fuzzy-based controller to integrate power control and transmission rate management for multimedia services in CDMA cellular systems. Simulation results show that the novel scheme is superior to other fuzzy-based or balanced power control schemes proposed for single rate. We also compare our scheme to a multi-rate scheme called the selective power control (SPC) scheme. Results show that our scheme can achieve better performance in several measurements, such as outage probability, average transmission rates, probability of unsuccessful transmissions, and probability of changes in transmission rates.


Entropy | 2013

A Maximum Entropy-Based Chaotic Time-Variant Fragile Watermarking Scheme for Image Tampering Detection

Young-Long Chen; Her-Terng Yau; Guo-Jheng Yang

The fragile watermarking technique is used to protect intellectual property rights while also providing security and rigorous protection. In order to protect the copyright of the creators, it can be implanted in some representative text or totem. Because all of the media on the Internet are digital, protection has become a critical issue, and determining how to use digital watermarks to protect digital media is thus the topic of our research. This paper uses the Logistic map with parameter u = 4 to generate chaotic dynamic behavior with the maximum entropy 1. This approach increases the security and rigor of the protection. The main research target of information hiding is determining how to hide confidential data so that the naked eye cannot see the difference. Next, we introduce one method of information hiding. Generally speaking, if the image only goes through Arnold’s cat map and the Logistic map, it seems to lack sufficient security. Therefore, our emphasis is on controlling Arnold’s cat map and the initial value of the chaos system to undergo small changes and generate different chaos sequences. Thus, the current time is used to not only make encryption more stringent but also to enhance the security of the digital media.


Computers & Electrical Engineering | 2016

Design and evaluation of a cloud-based Mobile Health Information Recommendation system on wireless sensor networks

Shu-Lin Wang; Young-Long Chen; Alex Mu-Hsing Kuo; Hung-Ming Chen; Yi Shiang Shiu

Display Omitted The development of a Mobile Health Information Recommendation system which integrates Cloud Computing, and Context-aware technology, and applies Collaborative Filtering technique for information recommendation.Through the collaborative recommender, users can effectively obtain consistent health information, and reduce energy and time consumption. Recent technological trends such as cloud computing, wireless communication, and wireless sensor networks provide a strong infrastructure and offer a true enabler for health information technology services over the Internet. This system is based on the cloud computing environment, integrating mobile communication technology, context-aware technology, and wireless sensor networks to build a mobile web for a personalized health information service, which includes two health information recommendation service functions: a collaborative recommender and a physiological indicator-based recommender. We further propose a hybrid predictive model, which combines the Grey Theory and Markov chain to predict the moving objects path. This will decrease the cost which arises from tracking errors and prolong the networks lifetime. From the experiment results of usability, it has been discovered that subjects have positive responses towards usability measurement dimensions of the system: satisfaction, expectation-confirmation, perceived trust, perceived usefulness, and perceived value.


Journal of Advances in Computer Networks | 2014

Grid-Based Data Aggregation for Wireless Sensor Networks

Neng-Chung Wang; Yung-Kuei Chiang; Chih-Hung Hsieh; Young-Long Chen

In a wireless sensor network (WSN), a huge number of sensor nodes with limited battery power are generally deployed over a severe field to gather data. It is impractical to recharge or replace the batteries of the sensor nodes in such a severe environment. Therefore, an energy efficient protocol is essential to maximize the lifetimes of nodes. In this paper, we propose a grid-based data aggregation scheme (GBDAS) for WSNs. We partition the whole sensor field into a 2-D logical grid of cells. In each cell, the node with the most residual energy takes turn to be the cell head, responsible for aggregating its own data with the data sensed by the other sensor nodes of the cell, and then transmitting it out. In order to reduce the data transmissions to the base station (BS), we further link each cell head to form a chain. In the chain, the cell head with the most residual energy is designated in turn as the chain leader. Aggregated data moves from head to head along the chain, and finally the chain leader transmits to the BS. In GBDAS, only the cell heads need to transmit data toward the BS. Therefore, the data transmissions to the BS substantially decrease. Besides, the cell heads and chain leader are designated in turn according to the energy level so that the energy depletion of nodes is evenly distributed. Simulation shows that GBDAS outperforms Direct and PEGASIS.


Neural Network World | 2013

DESIGN OF EXPERIMENTS ON NEURAL NETWORK'S PARAMETERS OPTIMIZATION FOR TIME SERIES FORECASTING IN STOCK MARKETS

Mu Yen Chen; Min-Hsuan Fan; Young-Long Chen; Hui-Mei Wei

Artificial neural network (ANN) model has been used for years to conduct research in stock price prediction for three reasons. First, it has a higher prediction accuracy rate in empirical research. Second, it is not subject to the assumption of having samples from a normal distribution. Third, it can deal with non-linear problems. Nevertheless, the accuracy of prediction relies on the parameter settings of neural network as well as the complexities of problems and the neural network architecture; the results of the analysis could be even more significant with the selection of optimal parameters and network architecture. Currently, as a way of setting parameters, most researchers employed the trial and error method. However, this method is very time-consuming and labor-intensive and may not result in the optimal parameters. Therefore, this research took advantage of a back propagation neural network (BPNN) for the purpose of parameter optimization through constructing a model of stock price prediction, applying design of experiment (DOE) to systematize experiment scheduling, and methods of main effects analysis and interaction analysis. The research used two datasets of financial ratios from 50 blue chip companies in Taiwanese stock market and 40 listed American banks in New York stock exchange as experimental samples. Research results showed that the correlation forecasting, root mean squared error (RMSE), and computing time, which can effectively increase the accuracy of stock price prediction, are better than traditional statistical methods and conventional neural network model.


Computers & Mathematics With Applications | 2012

Priority-based transmission rate control with a fuzzy logical controller in wireless multimedia sensor networks

Young-Long Chen; Hung-Pin Lai

Wireless multimedia sensor networks (WMSNs) are usually troubled by network congestion due to large packet transmission amounts, and such congestion will not only lose data packets but also lead to too much energy consumption. Therefore, in order to enhance the transmission performance of WMSNs and reduce the delay time, it is necessary to adjust the transmission rate and control network congestion. WMSNs use different kinds of sensor nodes to collect different kinds of data. In multimedia applications, it is necessary to provide a reliable and fair protocol so as to meet the requirements of quality of service (QoS) of different formats of data. In past research, for WMSNs, priority-based rate control (PBRC) algorithms and exponential weight (EW) algorithms were used to control congestion through the adjusting of the transmission rate among different data formats. However, the weight parameter of the EW algorithm is fixed; when the change in data transmission amount is large, the difference between input transmission rate and estimated output transmission rate for the sink node will be large. In this paper, we have proposed an algorithm where a fuzzy logical controller (FLC) is used to estimate the output transmission rate of the sink node. The FLC is associated with the EW algorithm for selecting the appropriate weight parameter, and then, on the basis of the priority of each child node, an appropriate transmission rate is assigned. Simulation results show that the performance of our proposed algorithm has a better transmission rate as compared to that of PBRC, and hence, the transmission delay and loss probability are reduced; in addition, our proposed algorithm can control effectively the different transmission data types in order to achieve the QoS requirement of the system.


Computers & Mathematics With Applications | 2012

A message negotiation approach to e-services by utility function and multi-criteria decision analysis

Chih-Kun Ke; Young-Long Chen

In modern society, information and internet techniques have changed human lifestyles. Service providers provide innovative e-services to attract and retain their customers. The popularity of e-services has made selecting a good e-service, which will also provide reasonable composite e-service solutions, an important issue. Therefore, this work proposes a message negotiation approach to e-services to assist consumers in acquiring a reasonable composite e-service solution. An e-service composition involves a complete e-service process including a series of steps. E-service formalization, an e-service utility model and a multi-criteria decision analysis are used to determine the optimal selection order of e-services for each specific e-service composition step. Then, the selected e-service for each step is composed through a message negotiation process. The result is presented to the consumer as a reasonable composite e-service solution. This work uses an ingredient procurement use case of property management in Taiwan to demonstrate that the proposed approach is effective.


Applied Soft Computing | 2014

Review article: A fuzzy logical controller for traffic load parameter with priority-based rate in wireless multimedia sensor networks

Young-Long Chen; Hung-Pin Lai

In wireless multimedia sensor networks (WMSNs), sensor nodes use different types of sensors to gather different types of data. In multimedia applications, it is necessary to provide reliable and fair protocols in order to meet specific requirements of quality of service (QoS) demands in regard to these different types of data. To prolong the system lifetime of WMSNs, it is necessary to perform adjustments to the transmission rate and to mitigate network congestion. In previous works investigating WMSNs, exponential weighted priority-based rate control (EWPBRC) schemes with traffic load parameter (TLP) schemes in WMSNs were used to control congestion by adjusting transmission rates relative to various data types. However, when the TLP is fixed, a large change in data transmission causes a significant difference between input transmission rate and the estimated output transmission rate of each sensor node. This study proposes a novel fuzzy logical controller (FLC) pertaining to TLP schemes with an EWPBRC that estimates the output transmission rate of the parent node and then assigns a suitable transmission rate based on the traffic load of each child node, with attention paid to the different amounts of data being transmitted. Simulation results show that the performance of our proposed scheme has a better transmission rate as compared to PBRC: the delay and loss probability are reduced. In addition, our proposed scheme can effectively control different transmission data types insofar as achieving the QoS requirements of a system while decreasing network resource consumption.

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Neng-Chung Wang

National United University

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Chih-Peng Li

National Sun Yat-sen University

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Chin-Ling Chen

Chaoyang University of Technology

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Yung-Chi Chang

National Taichung University of Science and Technology

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Yung-Fa Huang

Chaoyang University of Technology

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Jia-Sheng Lin

National Taichung University of Science and Technology

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Yu-Cheng Lin

National Taichung University of Science and Technology

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Yung-Sheng Lin

National Chung Cheng University

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Chih-Kun Ke

National Taichung University of Science and Technology

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