• Journal of Industrial Technology
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• v.27 no.B
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• pp.215-219
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• 2007

For Web server implementations, there are 4 main schemes: process-per-request (PPR), thread-per-request (TPR), worker thread pool (WTP), and worker thread pool with buffers (WTPB). This paper compares performance of the schemes in response time point of view. WTPB shows the best performance. The appropriate number of worker threads for WTPB depends on the request service time. For short requests, the number can be very small. But for longer requests, it is about 1/6 of the number of simultaneous connections.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.876-881
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• 2009

Online game servers usually has been using the static thread pool system. But this system is not fit for huge online game server because the overhead is always up-and-down. Therefore, in this paper, we suggest the new algorithm for huge online game server. This algorithm is based on the prediction-based dynamic thread pool system. But it was developed for web servers and every 0.1 seconds the system prediction the needed numbers of threads and determine the thread pool size. Some experimental results show that the check time of 0.4 seconds is the best one for online game server and if the number of worker threads do not excess or lack to the given threshold then we do not predict and keep the current state. Otherwise we apply the prediction algorithm and change the number of threads. Some experimental results shows that this proposed algorithm reduce the overhead massively and make the performance of huge online game server improved in comparison to the static thread pool system.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.23-34
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• 2010

As the number of user increases according to the improvement of the network, the multi-thread schemes are used to process the service requests of several users who are connected simultaneously. The static thread pool scheme has the problem of occupying a static amount of system resources. On the other hand, the dynamic thread pool scheme can control the number of threads according to the users' requests. However, it has disadvantage that this scheme cannot react to the requests which are larger than the maximum value assigned. In this paper, a web server using a learning-based dynamic thread pool scheme is suggested, which will be running on a server programming of a multi-thread environment. The suggested scheme adds the creation of the threads through the prediction of the next number of periodic requests using Auto Regressive scheme with the web server apache worker MPM (Multi-processing Module). Unlike previous schemes, in order to set the exact number of the necessary threads during the unchanged number of work requests in a certain period, K-Nearest Neighbor algorithm is used to learn the number of threads in advance according to the number of requests. The required number of threads is set by comparing with the previously learned objects. Then, the similar objects are selected to decide the number of the threads according to the request, and they create the threads. In this paper, the response time has decreased by modifying the number of threads dynamically, and the system resources can be used more efficiently by managing the number of threads according to the requests.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.31-41
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• 2007

In order to keep global competitiveness, most of small and medium size manufacturing companies require to equip a product information management system which collects and analyzes the data generated at the manufacturing lines and then provides information for manager or worker to make a decision. However, these companies have a cost problem for adopting the enterprise resource planning system mostly used in large companies. To overcome this problem, we suggest an IOCP-based server for the product information management system suitable for small and medium size manufacturing companies. The basic concept of suggested server is that it is possible to process concurrently the connection requests coming from data collector and client by using the facility of asynchronous notification of OS and protect a server against overload by using the thread pool.