• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1273-1281
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• 2000

In this paper we studied for multi-user detection system, which hold the merit of CDMA system and can enhance the system capacity. We designed actually realizable quasi-optimal multiuser detection system by use of linear equalizer on the concept that multiuser detection algorithm can be reduced by combining TDMA with CDMA. we call this the hybrid TDMA/CDMA system. And we proposed multiuser detection system, which can use PSAD and MSDD channel estimation method. As a result of performance analysis we acquired equal or much better performance by use of linear multichannel equalizer in the case of not so many user. And on the occasion of many user within cell we can also acquired much better performance in comparison with conventional single user detection system by use of hybrid TDMA/CDMA system.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.29-37
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• 2015

Nowadays, the user-centric application based web 2.0 has replaced the web 1.0. The users gain and provide information by interactive network applications. As a result, traditional approaches that only extract and analyze users' local document operating behavior and network browsing behavior to build the users' preference profile cannot fully reflect their interests. Therefore this paper proposed a preference analysis and indicating approach based on the users' communication information from MicroBlog, such as reading, forwarding and @ behavior, and using the improved PersonalRank method to analyze the importance of a user to other users in the network and based on the users' communication behavior to update the weight of the items in the user preference. Simulation result shows that our proposed method outperforms the ontology model, TREC model, and the category model in terms of 11SPR value.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.45-47
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• 2022

Mobile edge computing (MEC), which enables mobile terminals to offload computational tasks to a server located at the user's edge, is considered an effective way to reduce the heavy computational burden and achieve efficient computational offloading. In this paper, we study a multi-user MEC system in which multiple user devices (UEs) can offload computation to the MEC server via a wireless channel. To solve the resource allocation and task offloading problem, we take the total cost of latency and energy consumption of all UEs as our optimization objective. To minimize the total cost of the considered MEC system, we propose an DRL-based method to solve the resource allocation problem in wireless MEC. Specifically, we propose a Asynchronous Advantage Actor-Critic (A3C)-based scheme. Asynchronous Advantage Actor-Critic (A3C) is applied to this framework and compared with DQN, and Double Q-Learning simulation results show that this scheme significantly reduces the total cost compared to other resource allocation schemes

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.1-8
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• 2009

Learning user's preference is a key issue in intelligent system such as personalized service. The study on user preference model has adapted simple user preference model, which determines a set of preferred keywords or topic, and weights to each target. In this paper, we recommend multi-perspective user preference model that factors sentiment information in the model. Based on the topicality and sentimental information processed using natural language processing techniques, it learns a user's preference. To handle timc-variant nature of user preference, user preference is calculated by session, short-term and long term. User evaluation is used to validate the effect of user preference teaming and it shows 86.52%, 86.28%, 87.22% of accuracy for topic interest, keyword interest, and keyword favorableness.

• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.79-89
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• 2002

Several multi-user online applications which are operated by the existing fixed terminals(PC) are being changed into online application based on multi-platform operated by the several PC, PDA and mobile phones to perform concurrent works recently. The contents of current online application based multi-platform are, however, very unsophisticated because the applications don't consider the simultaneous accesses of shared data by multi-user and also the asymmetry of computing power and network bandwidth among each client. This paper proposed the methods of consistency control based on multi-platform, update propagation protocols among diverse clients, object management techniques which take the characteristics of mobile clients into account. We also implemented a chatting application based on multi-platform and it showed the proposed methods perform well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1100-1122
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• 2023

Scheduling user-submitted cloud tasks to the appropriate virtual machine (VM) in cloud computing is critical for cloud providers. However, as the demand for cloud resources from user tasks continues to grow, current evolutionary algorithms (EAs) cannot satisfy the optimal solution of large-scale cloud task scheduling problems. In this paper, we first construct a large- scale multi-objective cloud task problem considering the time and cost functions. Second, a multi-objective optimization algorithm based on multi-factor optimization (MFO) is proposed to solve the established problem. This algorithm solves by decomposing the large-scale optimization problem into multiple optimization subproblems. This reduces the computational burden of the algorithm. Later, the introduction of the MFO strategy provides the algorithm with a parallel evolutionary paradigm for multiple subpopulations of implicit knowledge transfer. Finally, simulation experiments and comparisons are performed on a large-scale task scheduling test set on the CloudSim platform. Experimental results show that our algorithm can obtain the best scheduling solution while maintaining good results of the objective function compared with other optimization algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4372-4394
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• 2020

The distribution of popular videos incurs a large amount of traffic at the base stations (BS) of networks. Device-to-multi-device (D2MD) communication has emerged an efficient radio access technology for offloading BS traffic in recent years. However, traditional studies have focused on synchronous user requests whereas asynchronous user requests are more common. Hence, offloading BS traffic in case of asynchronous user requests while considering their time-varying characteristics and the quality of experience (QoE) of video request users (VRUs) is a pressing problem. This paper uses social stability (SS) and video loading duration (VLD)-tolerant property to group VRUs and seed users (SUs) to offload BS traffic. We define the average amount of data transmission (AADT) to measure the network's capacity for offloading BS traffic. Based on this, we formulate a time-varying bipartite graph matching optimization problem. We decouple the problem into two subproblems which can be solved separately in terms of time and space. Then, we propose the socially aware D2MD user selection (SA-D2MD-S) algorithm based on finite horizon optimal stopping theory, and propose the SA-D2MD user matching (SA-D2MD-M) algorithm to solve the two subproblems. The results of simulations show that our algorithms outperform prevalent algorithms.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.23-30
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• 2011

Recently, Tsai proposed a remote user authentication scheme suited for multi-server environments, in which users can be authenticated using a single password shared with the registration center. Our analysis shows that Tsai et al's scheme does not achieve its fundamental goal of password security. We demonstrate this by mounting an undetectable on-line password guessing attack on Tsai et al.'s scheme.

• ETRI Journal
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• v.27 no.6
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• pp.768-776
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• 2005

We compare the achievable throughput of time division multiple access (TDMA) multiple-input multiple-output (MIMO) schemes illustrated in the 3rd Generation Partnership Project (3GPP) MIMO technical report, versus the sum-rate capacity of space-time multiple access (STMA). These schemes have been proposed to improve the 3GPP high speed downlink packet access (HSDPA) channel by employing multiple antennas at both the base station and mobile stations. Our comparisons are performed in multi-user environments and are conducted using TDMA such as Qualcomm's High Data Rate and HSDPA, which is a simpler technique than STMA. Furthermore, we present the unified optimal power allocation strategy for HSDPA MIMO schemes by exploiting the similarity of multiple antenna systems and multi-user channel problems.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.215-223
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• 2013

As cloud computing is activated, a variety of cloud services are being distributed. However, to use each different cloud service, you must perform a individual user authentication process to service. Therefore, not only the procedure is cumbersome but also due to repeated authentication process performance, it can cause password exposure or database overload that needs to have user's authentication information each cloud server. Moreover, there is high probability of security problem that being occurred by phishing attacks that result from different authentication schemes and input scheme for each service. Thus, when you want to use a variety of cloud service, we proposed OpenID based user authentication scheme that can be applied to a multi-cloud environment by the trusted user's verify ID provider.