• The KIPS Transactions:PartA
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• v.10A no.4
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• pp.331-338
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• 2003

Cluster is the cost-effective parallel processing environment, and consists of the off-the-shelf computers connected by the computer net works. The characteristics of cluster are the node heterogeneity, the variety of node load, and the variety of network load. Because these characteristics influence the performance of parallel program executions, the load sharing for cluster is important, and by using the proper load sharing strategy, we can reduce the execution time of parallel programs. In this paper, we propose modified GSS algorithm, αGSS. In the proposed load sharing algorithms α GSS, the size of tasks are decided using the BogoMIPS of node. From the result of out experiments, we conclude that the proposed αGSS algorithm is effective in the heterogeneous cluster.

• Journal of Computing Science and Engineering
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• v.12 no.1
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• pp.12-23
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• 2018

The Internet of Things (IoT) ecosystem potentially includes heterogeneous devices with different processing mechanisms as well as very complicated network and communication models. Thus, analysis of data associated with adverse conditions is much more complicated. Moreover, mobile things in the IoT lead to dynamic alteration of environments and developments of a dynamic and ultra-large-scale (ULS) environment. Also, IoT and the services provided by that are mostly based on devices with limited resources or things that may not be capable of hosting conventional controls. Finally, the dynamic and heterogeneous and ULS environment of the IoT will lead to the emergence of new security requirements. The conventional preventive and diagnostic security controls cannot sufficiently protect it against increasing complication of threats. The counteractions provided by these methods are mostly dependent on insufficient static data that cannot sufficiently protect systems against sophisticated and dynamically evolved attacks. Accordingly, this paper investigates the current security approaches employed in the IoT architectures. Moreover, we define the dynamic security based on dynamic event analysis, dynamic engineering of new security requirements, context awareness and adaptability, clarify the need for employment of new security mechanism, and delineate further works that need to be conducted to achieve a secure IoT.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.619-628
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• 2016

This paper describes a theoretical framework for rate allocation to maximize the power efficiency of overall heterogeneous wireless networks whose users are assumed to have multihoming capabilities. Therefore, the paper first presents a power consumption model considering the circuit power and radio transmission power of each wireless network. Using this model, two novel power efficient rate allocation schemes (PERAS) for multihoming services are proposed. In this paper, the convex optimization problem for maximizing the power efficiency over wireless networks is formulated and solved while guaranteeing the required quality of service (QoS). Here, both constant bit rate and variable bit rate services are considered. Furthermore, we extend our theoretical framework by considering the sleep-operation management of wireless networks. The performance results obtained from numerical analysis reveal that the two proposed schemes offer superior performance over the existing rate allocation schemes for multihoming services and guarantee the required QoS.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.1-11
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• 2023

Federated learning (FL) is a ground breaking machine learning paradigm that allow smultiple participants to collaboratively train models in a cloud environment, all while maintaining the privacy of their raw data. This approach is in valuable in applications involving sensitive or geographically distributed data. However, one of the challenges in FL is dealing with heterogeneous and non-independent and identically distributed (non-IID) data across participants, which can result in suboptimal model performance compared to traditionalmachine learning methods. To tackle this, we introduce FedGCD, a novel FL algorithm that employs Graph Neural Network (GNN)-based community detection to enhance model convergence in federated settings. In our experiments, FedGCD consistently outperformed existing FL algorithms in various scenarios: for instance, in a non-IID environment, it achieved an accuracy of 0.9113, a precision of 0.8798,and an F1-Score of 0.8972. In a semi-IID setting, it demonstrated the highest accuracy at 0.9315 and an impressive F1-Score of 0.9312. We also introduce a new metric, nonIIDness, to quantitatively measure the degree of data heterogeneity. Our results indicate that FedGCD not only addresses the challenges of data heterogeneity and non-IIDness but also sets new benchmarks for FL algorithms. The community detection approach adopted in FedGCD has broader implications, suggesting that it could be adapted for other distributed machine learning scenarios, thereby improving model performance and convergence across a range of applications.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.364-374
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• 2016

With vast amounts of spectrum available in the millimeter wave (mmWave) band, small cells at mmWave frequencies densely deployed underlying the conventional homogeneous macrocell network have gained considerable interest from academia, industry, and standards bodies. Due to high propagation loss at higher frequencies, mmWave communications are inherently directional, and concurrent transmissions (spatial reuse) under low inter-link interference can be enabled to significantly improve network capacity. On the other hand, mmWave links are easily blocked by obstacles such as human body and furniture. In this paper, we develop a multi-hop relaying transmission (MHRT) scheme to steer blocked flows around obstacles by establishing multi-hop relay paths. In MHRT, a relay path selection algorithm is proposed to establish relay paths for blocked flows for better use of concurrent transmissions. After relay path selection, we use a multi-hop transmission scheduling algorithm to compute near-optimal schedules by fully exploiting the spatial reuse. Through extensive simulations under various traffic patterns and channel conditions, we demonstrate MHRT achieves superior performance in terms of network throughput and connection robustness compared with other existing protocols, especially under serious blockage conditions. The performance ofMHRT with different hop limitations is also simulated and analyzed for a better choice of the maximum hop number in practice.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.21-33
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• 2007

An overlay network is a virtual network which is constructed on top of a physical computer network. A node in the overlay network is connected through virtual or logical links, where each link corresponds to a path of the links in the underlying physical network. Overlay networks are suitable for sharing heterogeneous resources in distributed environments, However, overlay networks are limited for achieving reliable communication that failure detection in overlay networks is a very important issue. In this paper, we review conditions of conventional failure detection and propose a new approach to failure detection and resilience which can be applied to HRing (Hierarchical Ring) overlay networks. The proposed method consists of the failure detection and the failure resilience phases. Because it utilizes the characteristics of the HRing overlay network for failure detection, it can reduce unnecessary network traffic and provide better scalability and flexibility. We also analyzed and evaluated the performance of the proposed approach through simulations.

• Journal of IKEEE
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• v.12 no.1
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• pp.18-26
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• 2008

With the advent of Ubiquitous environment, wired-wireless combination network is being studied very actively in which mobile nodes having multi-hop communication capability connect wired internet network easily, and shares the information. The study of wired and wireless combination network between MANET(Mobile Ad Hoc Network) and wired network is being focused only on the configuration of heterogeneous network interface. The proposed algorithm establishes independent multi-paths between source node and destination node to prevent data loss when errors happen in route. As the result, it shows that the reliability of the combination network can be improved by making data transmit continuously on the route error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2539-2548
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• 2015

Overcoming inter-cell interference and spectrum scarcity are major issues in heterogeneous cellular networks. Static Frequency reuse schemes have been proposed as an effective way to manage the spectrum and reduce ICI(Inter cell Interference) in cellular networks. In a kind of static frequency reuse scheme, the allocations of transmission power and subcarriers in each cell are fixed prior to system deployment. This limits the potential performance of the static frequency reuse scheme. Also, most of dynamic frequency reuse schemes did not consider small cell and the network environment when the traffic load of each cell is heavy and non-uniform. In this paper, we propose an inter-cell resource allocation algorithm that dynamically optimizes subcarrier allocations for the multi-cell heterogeneous networks. The proposed dynamic frequency reuse scheme first finds the subcarrier usage in each cell-edge by using the exhaustive search and allocates subcarrier for all the cells except small cells. After that it allocates subcarrier for the small cell and then iteratively repeats the process. Proposed dynamic frequency reuse scheme performs better than previous frequency reuse schemes in terms of the throughput by improving the spectral efficiency due to it is able to adapt the network environment immediately when the traffic load of each cell is heavy and non-uniform.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1517-1524
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• 2022

In this paper, we consider a heterogeneous network (HetNet) consisting of one macro base station and multiple small base stations, and assume the coordinated multi-point transmission between the base stations. In addition, we assume that the channel between the base station and the user consists of path loss and Rayleigh fading. Under these assumptions, we present the energy efficiency (EE) achievable by the user for a given base station and we formulate an optimization problem of dynamic cell selection and transmit power allocation to maximize the total EE of the HetNet. In this paper, we propose an unsupervised deep learning method to solve the optimization problem. The proposed deep learning-based scheme can provide high EE while having low complexity compared to the conventional iterative convergence methods. Through the simulation, we show that the proposed dynamic cell selection scheme provides higher EE performance than the maximum signal-to-interference-plus-noise ratio scheme and the Lagrangian dual decomposition scheme, and the proposed transmit power allocation scheme provides the similar performance to the trust region interior point method which can achieve the maximum EE.

• Journal of Korean Society for Geospatial Information Science
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• v.4 no.1 s.6
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• pp.103-114
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• 1996

A vehicle Control System that is a system combined by a Car Navigation System, a Geograhical Information System, and a Communication Network usually permit a central control room to detect vehicle's locations dynamically and manage these informations synthetically. Therefore, a vehicle control system can be used to control the rapid movement of patrol cars, freight transportation, and so on. In this paper, we designed and implemented a data manager for an application system, such as a vehicle control system, that usually manages road data, vehicle data, vehicle's location data, etc. The data manager that is implemented in this paper consists of system management module, road data management module, vehicle data management module, GPS(Global Positioning System) data management module, and additional data management module. Especially, we use the SHORE(Scalable Heterogeneous Object REpository) system as a storage system of the data manager.