Browsing by Author "Fan, Chih-Tien"

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A Cloud Based Dynamic Content Delivery Network
(2015-01-01)
Fan, Chih-Tien
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Piboonudompornkul, Pawat
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Wu, Zong-You
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交大名義發表
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National Chiao Tung University
In this paper, proposed Cloud based Content delivery network system to serve a dynamic web content delivery service. We used MongoDB as a NoSQL database, deploy inside each HDFS nodes server and connect database together as a replication set of database. This system ensures web content provider will receive a high performance, high availability and fault tolerance from power of NoSQL database technology. From the problem when web content provider want to move their web content in MySQL database environment to work in NoSQL database environment. User require a lot of time change their web content to work with new database environment and think about different schema of each database. So, we also study about Relational database management system (RDBMS) compare with NoSQL database, MongoDB. This work find out differentiation of this two type of database in different aspect: characteristic of each database, feature, database scheme and how to mapping this database query language together. The result of this work we done to develop simple and useful helper tools: PHP MySQL connector and MySQL database migrate tool. This tool is make web content provide easy and fast for migrate their web content from MySQL database web server environment to use our Cloud Based Dynamic Content Delivery Network without any special knowledge with NoSQL database.
A Cross Language Plagiarism Detection Based on Cloud Computing
(2015-01-01)
Fan, Chih-Tien
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Nguyen Dang Minh
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Muhammad, Husaini
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交大名義發表
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National Chiao Tung University
Nowadays, language barrier is getting lower, especially for the students. Most of them know at least one foreign language. Even that, translation through the cloud is getting popular. There are many machine translation services can be access easily via Internet. These services work accurately and support many languages. They are even embedded by default in web browser of users and in mobile devices. This is easiest way for a student to translate a sentence from any language, and of course easy for cross-language plagiarism too. It makes plagiarism is getting difficult to detect. In this paper, we exploited cloud services and cloud computing model for detecting cross-language plagiarism. We downloaded a translation of the article from a website of Vietnam and Vietnamese local news provider then used as a test dataset. These articles were first translated into the English using translation services on the Web. Again, each translated sentences were sent to the web search engine to find related articles. Then, we compared this sentence with each sentence in the related articles to find out its score of plagiarism. Finally, we computed the score of plagiarism of this article. Experiment results show that the accuracy of detection is slightly higher than 0.5.
A Mental Disorder Early Warning Approach by Observing Depression Symptom in Social Diary
(2014)
Fang, Ying-En
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Tai, Chih-Hua
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Chang, Yue-Shan
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Fan, Chih-Tien
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資訊工程學系
With the advances of information technology, there are increasing researches aiming at assisting depression diagnosis and treatment. In most of them the user is necessarily actively joining the diagnosis and treatment program while he has perceived mental disorder himself. In order to early prevent the mental disorder, in this paper we propose an early warning mechanism that observes and mines user diary published on social network platform, and generates a score of getting mental disordered or depressed. If the score is large than a threshold, the system can notify the user and his friends on the social network to take care about the friend. We have conducted experiments to evaluate the proposed approach, and the results show that the proposed approach is effective.
Adaptive Block Partition of Geographic Map Based on Road Coverage in Urban Environment
(2015-01-01)
Wu, Guang-Ting
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Sheu, Ruey-Kai
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Fan, Chih-Tien
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Chang, Yue-Shan
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Tai, Chih-Hua
Smart cities try to deploy new sensors or controller to existing hardware infrastructure to improve the efficiency of city life. How to effectively utilize geographic information to deploy ubiquitous facilities (such as street light control unit) in the urban environment increasingly becomes an important issue. Calculating the minimum block number for facility deployment in a city is similar to the maximum clique problem which belongs to the NP-hard problems. In this paper, we propose an algorithm to find the near minimum block number of geographic map based on road coverage in the urban environment. In the algorithm, we first exploit the Google map as the geographic information to calculate the road coverage of a city and then partitioning the map into numerous partitions according to a given lights (road coverage). We also conduct some experiments to evaluate the performance and accuracy to demonstrate the feasibility of the system. The result shows that the proposed algorithm is effective and efficient.
An Advertisement Video Analysis System based on Eye-Tracking
(2015)
Zhang, Xue-bai
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Fan, Chih-Tien
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Yuan, Shyan-Ming
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Peng, Zih-You
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資訊工程學系
Eye tracking technology provides a faster and more intuitive interface to evaluate video contents. Fewer researches presented complete application of the eye tracking technology in advertisement design, with difficulty in mapping eye tracking data for moving targets on computer displays. This paper proposes an advertisement video analysis system based on eye-tracking for advertiser to evaluate the advertisement content objectively. A cheap eye tracking device is used in our system in order to reduce the burdens of medium-sized and small enterprises and research organizations to contact with eye tracking technology. Simple mouse operations are needed to define the dynamic Area of Interests (AOIs) in the video. Finally, the video which integrates the eye movement data and the dynamic AOIs is provided with some outputs, a simple statistical chart and a detail fixation information analysis. To evaluate the effectiveness of proposed system, we use an advertisement video with multiple moving targets to test eye movement of 20 participants. Experimental results show our system support the analysis of eye movement data for tracking multiple moving targets.
An agent-based workflow scheduling mechanism with deadline constraint on hybrid cloud environment
(2018-01-10)
Chang, Yue-Shan
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Fan, Chih-Tien
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Sheu, Ruey-Kai
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Jhu, Syuan-Ru
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Yuan, Shyan-Ming
With the advances of cloud computing, business and scientific-oriented jobs with certain workflows are increasingly migrated to and run on a variety of cloud environments. These jobs are often with the property of deadline constraint and have to be completed within limited time. Therefore, to schedule a job with workflow (short for workflow) with deadline constraint is increasingly becoming a crucial research issue. In this paper, we, based on previous work, propose an agent-based workflow scheduling mechanism to schedule workflows that are with deadline constraint into federated cloud environment. Design and MethodsWe add a workflow agent into the original framework to schedule the deadline-constraint workflow. The workflow agent can smoothly schedule workflows to the cloud system according to their required resource and automatically monitor their execution. In order to accurately predict the execution time of each task to meet deadline constraint on certain VM with given resource, we inherit the use of rough set theory to estimate execution time of task in our previous work. Result and DiscussionA heuristic algorithm that is embedded into the workflow agent is also proposed because the problem had been shown to be NP-complete. The mechanism also adopts dynamic job dispatching method to reduce the usage of VM and to improve the resource utilization. We also conducted experiments to evaluate the efficiency and effectiveness. ConclusionThe experimental results show that the prediction time is very close to the real execution time and can efficiently schedule multiple scientific workflows to meet the deadline constraints simultaneously.
Execution Time Prediction Using Rough Set Theory in Hybrid Cloud
(2012)
Fan, Chih-Tien
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Chang, Yue-Shan
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Wang, Wei-Jen
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Yuan, Shyan-Ming
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資訊工程學系
Execution time prediction is an important issue in cloud computing. Predicting the execution time fast and accurately not only can help users to schedule jobs smarter, but also maximize the throughput and minimize the resource consumption of cloud platform. While hybrid cloud provides methods to federate multiple cloud platforms, different cloud platforms have different resource attributes, which will increase the difficulties to predict a job's execution time. In this paper, we exploit Rough Set Theory (RST), which is a well-known prediction technique that uses the historical data, to predict the execution time of jobs. The evaluation presents that RST can utilize the accuracy of the execution time, while the decision can be made in a short period of time.
Eye-Tracking Assisted Self-Directed Learning System
(2015)
Daraghmi, Eman Yasser
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Fan, Chih-Tien
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Lin, Wei-Jun
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Peng, Zih-You
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Yuan, Shyan Ming
Guiding young learners\' attention improves their self-directed learning skills, and that attention can be analyzed via the learners\' eye movements. Thus, we propose a self-directed learning system integrating eye trackers with a web based interface to provide an attention guiding function that aims at notifying the learners about the ignored or the skipped parts from the learning material as well as providing hints about the confusing sections. We aim at implementing a cost-effective system that can be used by learners not only at school, but also at home. In conclusion, we believe that the proposed system can be considered as effective tool to enhance the learners\' self-directed learning skills.
File Transfer and Synchronization over Multiple Clients/Server Environment
(2015-01-01)
Andriychenko, Volodymyr
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Fan, Chih-Tien
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Li, Yi-Hung
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交大名義發表
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National Chiao Tung University
With the expanding quantity of personal electronic devices, grows the importance of reliable data storage and distribution. These days, network and wireless solutions are preferred, e.g. cloud storage-based architectures. But does average user really need uploading to a reliable server for all the data? And how the server would deal with hundreds of gigabytes of files from millions of users? To address these issues, a new system called syx is introduced. It has the possibility of local file distribution within the same network, offloading most of the computational, storage and networking load to clients and flexibility in terms of file distribution, when it is decided for each client or device whether to get the specific file or folder onto it.
Implementing a Workflow Agent on Federated Cloud
(2015)
Jhu, Syuan-Ru
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Fan, Chih-Tien
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Yuan, Shyan-Ming
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Chang, Yue-Shan
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資訊工程學系
Workflow scheduling is the way to schedule the complex scientific workflow. In a cloud platform, the resources can be utilized more effectively and efficiently by scheduling the workflow properly. In this paper, an agent-based workflow scheduling mechanism on cloud environment is proposed. We implement a set of agents that can federate multiple clouds and automatically monitor the entire system, and manage the job if it\'s a workflow job. We also implement a dynamic job dispatching algorithm to reduce the VM usage amount and improve the resource utilization.
Mobile cloud-based depression diagnosis using an ontology and a Bayesian network
(2015-02-01)
Chang, Yue-Shan
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Fan, Chih-Tien
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Lo, Win-Tsung
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Hung, Wan-Chun
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Yuan, Shyan-Ming
Recently, depression has becomes a widespread disease throughout the world. However, most people are not aware of the possibility of becoming depressed during their daily lives. Therefore, obtaining an accurate diagnosis of depression is an important issue in healthcare. In this study, we built an inference model based on an ontology and a Bayesian network to infer the possibility of becoming depressed, and we implemented a prototype using a mobile agent platform as a proof-of-concept in the mobile cloud. We developed an ontology model based on the terminology used to describe depression and we utilized a Bayesian network to infer the probability of becoming depressed. We also implemented the system using multi-agents to run on the Android platform, thereby demonstrating the feasibility of this method, and we addressed various implementation issues. The results showed that our method may be useful for inferring a diagnosis of depression. (C) 2014 Elsevier B.V. All rights reserved.
Peer-to-Peer Based Parallel Genetic Algorithm
(2017-01-01)
Helal, Mohammed H. S.
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Fan, Chih-Tien
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Liu, De-You
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Yuan, Shyan-Ming
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資訊科學與工程研究所
In an attempt to reduce communication overhead while maintaining high quality Genetic Algorithm results, this paper presents a Peer-to-Peer based Genetic Algorithm that suites both Parallel and Distributed environments. In order to improve our approach's applicability on both distributed and parallel environments, we experimented a set of different individual exchange intervals when running some well-known hard optimization problems. The proposed approach has been applied in different exchange rates and benchmarked with a regular Master-Slave based PGA on result quality and executions time. Experimental results show that our approach managed to find high quality results in shorter execution time compared to Master-Slave based PGA.
VM instance selection for deadline constraint job on agent-based interconnected cloud
(2018-10-01)
Fan, Chih-Tien
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Chang, Yue-Shan
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Yuan, Shyan-Ming
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資訊工程學系
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Department of Computer Science
In recent years, users have been buying computing resources, such as VM instances, from the cloud resource providers. However, every cloud has its pricing models, solutions, and interfaces. Without a united interface, it is hard to manage across different clouds. To make things worse, it is even hard to select proper VM instances among multiple cloud resource providers when the resources are not sufficient. This paper proposes an interconnected cloud of selecting VM instances based on the job's deadline constraint. To make the system function, five agents are created for different purposes: a System Monitoring Agent, a Job Dispatching Agent, an Instance Group Managing Agent, an Instance Group Administrating Agent, and a Job Executing Agent. This paper also presents two decision algorithms, the Job Dispatching Algorithm and the Instance Group Invocation Algorithm, based on the Rough Set Theory, the jobs' deadline constraint, and the computing resource of the VM instances. The proposed system was deployed and evaluated on the real machines. The result shows not only the VM instances on different machines are interconnected, but also the algorithms successfully help manage the interconnected cloud's computing resources according to the submitted jobs with deadline constraints. (C) 2018 Elsevier B.V. All rights reserved.
Web Resource Cacheable Edge Device in Fog Computing
(2016-01-01)
Fan, Chih-Tien
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Wu, Zong-You
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Chang, Che-Pin
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Yuan, Shyan Ming
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資訊科學與工程研究所
The bandwidth of the network is precious. As cloud computing provides powerful computation power and more and more devices are connected to the Internet there is a need to seek for methods to reduce the traffic. Fog computing was proposed to adding the computation and storage ability to the edge devices. The requests from the end device can be preprocessed or even responded at the edge device. In this work, the ability of Web Resource Caching is added to the edge device to serve as a caching proxy server. In order to obtain more caching storage, the end devices are also exploits to provide some caching space. As the whole caching storage is enlarged, large resource like media files are able to be cached near to the end devices once any of the end devices in the same network just recently requested it. The result shows that the proposed architecture has better downloading latency compares to the single caching proxy approach.