• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.3
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• pp.1373-1379
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• 2011

The SLA (Service Level Agreement) is once determined between service provider and users in B3G networks so that the network service must be provided as QoS management. Here, the network situation is changed as the time flow, and the service environment is also altered. Hence, dynamic QoS management scheme should be considered. In this paper, we propose a handover scheme for dyanamic QoS as the network situation in B3G networks. The heterogeneous networks can be used for dynamic QoS management in B3G networks.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1628-1635
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• 2008

In this paper, the motion coordination algorithm of mobile agents in active sensor network is proposed to track the dynamic boundary for environmental monitoring. While most of dynamic boundary tracking algorithms in the literature were studied under the assumption that the boundary and/or its evolving rate is known a priori, the proposed algorithm is assumed that the individual active agent can measure the state of environment locally without any information of the boundary. When the boundary is evolving dynamically, the formation of active agents is designed to achieve two objectives. One is to track boundary layer based on the measured information and a small deviation. The other is to maintain a uniform distance between adjacent agents. The algorithm structure based on a state diagram is proposed to achieve these two objectives. Finally, it will be shown in the simulations that all given agents converge to a desired boundary layer and maintain a formation along the boundary. (e.g., a circle, an ellipse, a triangle and a rectangle)

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.245-248
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• 2000

In this paper we improve the performance of autonomous mobile robot by induction of reinforcement learning concept. Generally, the system used in this paper is divided into two part. Namely, one is neural-fuzzy and the other is dynamic recurrent neural networks. Neural-fuzzy determines the next action of robot. Also, the neural-fuzzy is determined to optimal action internal reinforcement from dynamic recurrent neural network. Dynamic recurrent neural network evaluated to determine action of neural-fuzzy by external reinforcement signal from environment, Besides, dynamic recurrent neural network weight determined to internal reinforcement signal value is evolved by genetic algorithms. The architecture of propose system is applied to the computer simulations on controlling autonomous mobile robot.

• 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 Korea Multimedia Society
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• v.11 no.4
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• pp.544-553
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• 2008

The general sensor network uses bundle method to collect fixed information from sensor node. However, this method is difficult to actively cope with major sensing objects in healthcare environment including status and position change of person and change of surrounding environment. In order to support the healthcare environment, certain information should be provided in accordance with the change of status of person and surrounding circumstance and also must cope with the change of network type by movement of person. This paper analyzes LEACH protocol which guarantees effectiveness of network as it constitutes clusters between Agilla model that is a representative multi agent middle ware and surrounding nodes. Based on the result of this analysis, it suggests LEACH_Mobile protocol which guarantees node mobility that is the weakest point of LEACH protocol. Moreover, it designs mobility agent middleware which supports dynamic function change of node and mobility agent module which supports dynamic function change of mobile node as components of LEACH_Mobile routing module. In addition, it is definitely increase performance which in mobile node of transfer data rate through LEACH_Mobile protocol of simulation result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.907-915
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• 2003

A very efficient packet transmission scheme is needed in the radio environment where radio resource is insufficient as compared with the environment of the wired communication. In general, dual mode packet transmission scheme is used broadly. Packets are transmitted through the dedicated or common chamois according to a switching criterion. The general criteria are the length and generation frequency of packet, that is, large and frequent packets are transmitted using a dedicated channel and small and infrequent packets are transmitted using a common channel. The performance of dual mode packet transmission scheme is closely related to the switching criteria. However, it is very difficult to find the optimal switching point because that is not fixed but variable according to the environment such as traffic load, length of generated packets, and the number of channels. In this paper, a new scheme for the dual mode packet transmission scheme using a dynamic switching threshold is proposed where the switching threshold is not fixed but variable according to the network environment. The performance of the proposed method is analyzed using a simulation. From the simulation results, it is shown that the performance of the proposed scheme is not very influenced by the network environment unlike the conventional dual mode packet transmission scheme.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.1-8
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• 2021

In Mobile Ad-Hoc Network (MANET) Application, routing protocol is essential to ensure successful data transmission to all nodes. Ad-hoc On-demand Distance Vector (AODV) Protocol is a reactive routing protocol that is mostly used in MANET applications. However, the protocol causes Route Request (RREQ) message flooding issue due to the broadcasting method at the route request stage to find a path to a particular destination, where the RREQ will be rebroadcast if no Request Response (RREP) message is received. A scalable neighbor-based routing (SNBR) protocol was then proposed to overcome the issue. In the SNBR protocol, the RREQ message is only rebroadcast if the number of neighbor nodes less than a certain fix number, known as drop factor. However, since a network always have a dynamic characteristic with a dynamic number of neighbor nodes, the fix drop factor in SNBR protocol could not provide an optimal flooding problem solution in a low dense network environment, where the RREQ message is continuously rebroadcast RREQ message until reach the fix drop factor. To overcome this problem, a new broadcasting method as Dynamic SNBR (DSNBR) is proposed, where the drop factor is determined based on current number of neighbor nodes. This method rebroadcast the extra RREQ messages based on the determined dynamic drop factor. The performance of the proposed DSNBR is evaluated using NS2 and compared with the performance of the existing protocol; AODV and SNBR. Simulation results show that the new routing protocol reduces the routing request overhead, energy consumption, MAC Collision and enhances end-to-end delay, network coverage ratio as a result of reducing the extra route request messages.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.253-253
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• 2000

Each robot plays a role of its own behavior in dynamic robot-soccer environment. One of the most necessary conditions to win a game is control of robot movement. In this paper we suggest a win strategy using Cellular Neural Network to set optimal path and cooperative behavior, which divides a soccer ground into grid-cell based ground and has robots move a next grid-cell along the optimal path to approach the moving target.

• The Journal of Korean Association of Computer Education
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• v.12 no.2
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• pp.77-86
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• 2009

Large-scale applications, that needs large-capacity R&D resources and realtime data transmission, have demanded more stable and high-performance network environment than current Internet environments. Recently, global R&D networks have focuses on utilizing Lambda networking technologies and resource reservation systems to be satisfied with various applications' requirements. In this paper, we modify the existing DRS (Dynamic Right-Sizing) model to reflect various advantages in terms of the stability and high-capacity of Lambda network. In addition, we suggest the design methodology of high-performance Lambda network, which can integrate NRPS (Network Resource Provisioning System) into our modified DRS model.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.