• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2169-2175
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• 2014

In this paper we have proposed a new distributed architecture of session-based instant message system, in which multiple servers can distribute loads effectively to improve system extendability. The server of session-based instant message system should manage SIP sessions to transfer instant message with multimedia data to each users, and it should process large amount of presence informations from each users. Therefore load of the server should be distributed as the number of users increases. In our system, when server load increases according to large user numbers, the load are distributed by selecting a server with the lowest load value, or new server is created to allocate the message processing. Therefore the overall load of instant message system can be dynamically distributed. A new presence information data format with added elements for controlling server load has been designed for this purpose, and SIP messages exchanging procedure between servers and users has been also suggested. The performance of our proposed system has been analysed by simulation, and showed improvement of performance.

• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.363-372
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• 2009

For large scale VOD service, cluster servers are spotlighted to their high performance and low cost. A cluster server usually consists of a front-end node and multiple back-end nodes. Though increasing the number of back-end nodes can result in the more QoS streams for clients, the possibility of failures in back-end nodes is proportionally increased. The failure causes not only the stop of all streaming service but also the loss of the current playing positions. In this paper, when a back-end node becomes a failed state, the recovery mechanisms are studied to support the unceasing streaming service. For the actual VOD service environment, we implement a cluster-based VOD servers composed of general PCs and adopt the parallel processing for MPEG movies. From the implemented VOD server, a video block recovery mechanism is designed on parity algorithms. However, without considering the architecture of cluster-based VOD server, the application of the basic technique causes the performance bottleneck of the internal network for recovery and also results in the inefficiency CPU usage of back-end nodes. To address these problems, we propose a new failure recovery mechanism based on the pipeline computing concept.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.79-88
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• 2002

Transcoding proxy strategy has been widely used as a means to reduce the delay in retrieving Web pages over wireless mobile data service networks. However, this strategy has the serious drawbacks of being a potential point of failure or a bottleneck of the service. We developed a distributed proxy server system in which multiple proxy servers are installed at geographically dispersed locations and share the workloads among them by serving mobile hosts only within assigned regions. A new handoff message protocol to enable handoffs between proxies as the mobile hosts move between regions is proposed. According to the proxy server handoff protocol, a client agent at the mobile horst requests a proxy server to start handoff processing by which two proxy servers synchronize distilled data belonging to a HTTP session that must be maintained across the handoff. Also, we introduce the architecture of the proxy server and the client agent that handles the proxy server handoff. Finally, we evaluate the proposed system through performance test.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.283-288
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• 2016

In recent years, there have been many research efforts on Big Data, and many companies developed a variety of relevant products. Accordingly, we are able to store and analyze a large volume of log data, which have been difficult to be handled in the traditional computing environment. To handle a large volume of log data, which rapidly occur in multiple servers, in this paper we design a new data storage architecture to efficiently analyze those big log data through Apache Hive. We then design and implement anomaly detection methods, which identify abnormal status of servers from log data, based on moving average and 3-sigma techniques. We also show effectiveness of the proposed detection methods by demonstrating that our methods identifies anomalies correctly. These results show that our anomaly detection is an excellent approach for properly detecting anomalies from Hadoop log data.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.587-593
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• 2021

In this thesis, we will break away from the classic DDoS response system for large-scale denial-of-service attacks that develop day by day, and effectively endure intelligent denial-of-service attacks by utilizing artificial intelligence-based technology, one of the core technologies of the 4th revolution. A possible service model development plan was proposed. That is, a method to detect denial of service attacks and minimize damage through machine learning artificial intelligence learning targeting a large amount of data collected from multiple security devices and web servers was proposed. In particular, the development of a model for using artificial intelligence technology is to detect a Western service attack by focusing on the fact that when a service denial attack occurs while repeating a certain traffic change and transmitting data in a stable flow, a different pattern of data flow is shown. Artificial intelligence technology was used. When a denial of service attack occurs, a deviation between the probability-based actual traffic and the predicted value occurs, so it is possible to respond by judging as aggressiveness data. In this paper, a service denial attack detection model was explained by analyzing data based on logs generated from security equipment or servers.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.60-70
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• 2018

A software defined storage (SDS) is being deployed in cloud environment to allow multiple users to virtualize physical servers, but a solution for optimizing space efficiency with limited physical resources is needed. In the conventional data deduplication system, it is difficult to deduplicate redundant data uploaded to distributed storages. In this paper, we propose a distributed deduplication method using similarity-based clustering and multi-layer bloom filter. Rabin hash is applied to determine the degree of similarity between virtual machine servers and cluster similar virtual machines. Therefore, it improves the performance compared to deduplication efficiency for individual storage nodes. In addition, a multi-layer bloom filter incorporated into the deduplication process to shorten processing time by reducing the number of the false positives. Experimental results show that the proposed method improves the deduplication ratio by 9% compared to deduplication method using IP address based clusters without any difference in processing time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.162-169
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• 2022

In a dynamically changing time-varying network environment, the optimal moving pattern of edge devices can be applied to distributing computing resources to edge cloud servers or deploying new edge servers in the FEC(Fog/Edge Computing) environment. In addition, this can be used to build an environment capable of efficient computation offloading to alleviate latency problems, which are disadvantages of cloud computing. This paper proposes an algorithm to extract the optimal moving pattern by analyzing the moving path of multiple edge devices requiring application services in an arbitrary spatio-temporal environment based on frequency. A comparative experiment with A^* and Dijkstra algorithms shows that the proposed algorithm uses a relatively fast execution time and less memory, and extracts a more accurate optimal path. Furthermore, it was deduced from the comparison result with the A^* algorithm that applying weights (preference, congestion, etc.) simultaneously with frequency can increase path extraction accuracy.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.291-296
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• 2021

The development of the Internet of Things(IoT) requires large computational resources for tasks from numerous devices. Mobile Edge Computing(MEC) has attracted a lot of attention in the IoT environment because it provides computational resources geographically close to the devices. Task offloading to MEC servers is efficient for devices with limited battery life and computational capability. In this paper, we assumed an industrial IoT environment requiring high reliability. The complexity of optimization problem in industrial IoT environment with many devices and multiple MEC servers is very high. To solve this problem, the problem is divided into two. After selecting the MEC server considering the queue status of the MEC server, we propose an offloading decision algorithm that optimizes reliability and energy consumption using genetic algorithm. Through experiments, we analyze the performance of the proposed algorithm in terms of energy consumption and reliability.

• Journal of Platform Technology
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• v.11 no.3
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• pp.3-11
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• 2023

Real-time control systems are growing rapidly as infrastructure technologies such as IoT and mobile communication develop and services that value real-time such as factory management and vehicle operation checks increase. Various solutions have been proposed to increase the time sensitivity of this system, but most real-time control systems are currently composed of local servers and multiple clients located in control stations, which are transmitted to local servers where control systems are located. In this paper, we proposed an edge computing-based real-time control model that can reduce the time it takes for the bus information system, one of the real-time control systems, to provide the information to the user at the time it collects the information. Simulating the existing model and the edge computing model, the edge computing model confirmed that the cost for users to receive data is reduced from at least 10% to up to 80% compared to the existing model.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2002.11a
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• pp.215-218
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• 2002

패스워드 기반 키분배 프로토콜의 가장 중요한 요구사항 중 하나는 사전공격과 같은 패스워드 추측 공격에 대하여 안전하여야 한다. 그러나 지금까지 제안된 패스워드 추측 공격에 대한 안전성은 비밀 서버를 가정하고 있다. 즉, 검증자 기반 방식이더라도 서버에 저장되어 있는 패스워드 검증자가 비밀리에 보관되어야 한다는 단점이 있다. 본 논문에서는 새로운 방식의 다중 서버를 이용한 패스워드 기반 키분배 방식을 제안한다. 딜리는 사용자에 대한 인증 및 검증자를 각 서버에 전송하는 일을 담당한다. 사용자는 특정 서버와 단독으로 세션키를 교환하지만, 서버는 세션키를 생성하기 위해서는 그룹 내에 있는 모든 서버와 비밀 복원 과정을 거처야만 하는 새로운 방식이다. 사용자와 키분배를 수행하는 특정한 서버는 그룹 내에 있는 다른 서버와 비밀 복원 과정을 거처야만 키분배 과정을 수행할 수 있으므로, 특정 서버의 패스워드 파일이 노출되어 패스워드 검증자가 공격자에게 노출되더라도 비밀 분산 과정을 수행하지 못하는 공격자는 패스워드 추측에 필요한 정보를 획득할 수 없다.