Browsing by Author "Chiu, Cheng-Hsiang"

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A SERVER LOAD BALANCING DESIGN FOR PEER-TO-PEER NETWORK
(2011)
Liaw, Der-Cherng
;
Chiu, Cheng-Hsiang
;
Yeh, Chia-Wei
;
Chang, Chia-Ming
;
Hsieh, Hsiao-Jen
A novel scheme is proposed for server load balancing. It is known that load balancing plays a critical role in network-based information service. Although lots of methods have been recently proposed, however, most of those schemes might not be able to make the loading of all servers evenly. Thus, server system might encounter the risk of being over-loaded and/or out of function. In this paper, we propose a distribution scheme to prevent the server from being over-loaded and save the power consumption of all server system for low loading request. It is shown in the paper that the proposed scheme can make the load distribution more efficiently without being over-loaded. Experimental results demonstrate the success of the proposed design.
A Server Load Balancing Design for Peer-To-Peer Network
(2010)
Liaw, Der-Cherng
;
Chiu, Cheng-Hsiang
;
Yeh, Chia-Wei
;
Chang, Chia-Ming
;
Hsieh, Hsiao-Jen
A novel scheme is proposed for server load balancing. It is known that load balancing plays a critical role in network-based information service. Although lots of methods have been recently proposed, however, most of those schemes might not be able to make the loading of all servers evenly. Thus, server system might encounter the risk of being over-loaded and/or out of function. In this paper, we propose a distribution scheme to prevent the server from being overloaded and save the power consumption of all server system for low loading request. It is shown in the paper that the proposed scheme can make the load distribution more efficiently without being over-loaded. Experimental results demonstrate the success of the proposed design.
Object Tracking Under Sensing Lighting Equipments
(2010)
Chiu, Cheng-Hsiang
;
Hung, Pang-Chan
;
Huang, Hsing-Lu
;
Chuang, Jen-Hui
;
資訊工程學系
In this paper, image processing techniques are applied to the analysis of near-infrared videos. The goal is to detect human activities in the videos. For detecting human activities, we implement the Gaussian mixture modeling (GMM) to construct background model and to perform foreground detection. Additionally, we pay attention to commonly used sensing lighting equipments used in nighttime environment because of its illumination and shadowing phenomena. Accordingly, a two-mode GMM is proposed which separately constructs background GMM for different lighting conditions and switches GMM modes by event detection. In order to cope with excessive shadowing phenomenon, an efficient way of searching footholds by using scan-lines is proposed to remove human shadows. The proposed approach will provide reasonable bounding boxes information of human regions as detection results which will be very helpful for a nighttime surveillance system.