• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2595-2618
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• 2018

In this paper, we investigate secure communication with the presence of multiple eavesdroppers (Eves) in a two-tier downlink dense heterogeneous network, wherein there is a macrocell base station (MBS) and multiple femtocell base stations (FBSs). Each base station (BS) has multiple users. And Eves attempt to wiretap a macrocell user (MU). To keep Eves ignorant of the confidential message, we propose a physical-layer security scheme based on cross-layer cooperation to exploit interference in the considered network. Under the constraints on the quality of service (QoS) of other legitimate users and transmit power, the secrecy rate of system can be maximized through jointly optimizing the beamforming vectors of MBS and cooperative FBSs. We explore the problem of maximizing secrecy rate in both non-colluding and colluding Eves scenarios, respectively. Firstly, in non-colluding Eves scenario, we approximate the original non-convex problem into a few semi-definite programs (SDPs) by employing the semi-definite relaxation (SDR) technique and conservative convex approximation under perfect channel state information (CSI) case. Furthermore, we extend the frame to imperfect CSI case and use the Lagrangian dual theory to cope with uncertain constraints on CSI. Secondly, in colluding Eves scenario, we transform the original problem into a two-tier optimization problem equivalently. Among them, the outer layer problem is a single variable optimization problem and can be solved by one-dimensional linear search. While the inner-layer optimization problem is transformed into a convex SDP problem with SDR technique and Charnes-Cooper transformation. In the perfect CSI case of both non-colluding and colluding Eves scenarios, we prove that the relaxation of SDR is tight and analyze the complexity of proposed algorithms. Finally, simulation results validate the effectiveness and robustness of proposed scheme.

• Journal of KSNVE
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• v.9 no.4
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• pp.849-855
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• 1999

Neural Networks have shown potential to become an attractive alternative to classic methods for identification and control of non-linear dynamic systems. The purpose of this paper is to present an application of neural networks, that is a neural reconstruction of the input signal of a non-linear unknown system. This basic methodology could be used for practical purpose in several engineering fields. Clearly applications of the proposed scheme can be of interest for physical systems where a complete network of sensors measuring system inputs is not available. It should also be emphasized that the application of the reconstruction scheme is of little or no interest when the analyzed system works and operates at nominal conditions. In fact, only when failures and/or system anomailes occur, leasing to performance degradation and/or shutdown, the application of this scheme is of interest. The paper presents the results of the methodology applied to unknown non-linear dynamic systems and the robustness of the scheme to white and colored system noise was evaluated.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.49-58
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• 2000

This paper deals with a systematic approach to neural network controller design for static VAR compensator (SVC) using a learning algorithm of error back propagation that accepts error and change of error as inputs, the momentum learning technique is used for reduction of learning time, to improve system stability. A SVC, one of the Flexible AC Transmission System(FACTS), constructed by a fixed capacitor(FC) and a thyristor controlled reactor(TCR), is designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage.TO verify the robustness of the proposed method, we considered the dynamic response of generator rotor angle deviation, angular velocity deviation and generator terminal voltage by applying a power fluctuation and rotor angle fluctuation in initial point when heavy load and normal load. Thus, we prove the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.352-362
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• 2010

The simultaneous operation of multiple UAV's makes it possible to enhance the mission accomplishment efficiency. In order to achieve this, easily scalable control algorithms are required, and swarm intelligence having such characteristics as flexibility, robustness, decentralized control, and self-organization based on behavioral model comes into the spotlight as a practical substitute. Recently, evolutionary robotics is applied to the control of UAV's to overcome the weakness of difficulties in the logical design of behavioral rules. In this paper, a neural network controller evolved by evolutionary robotics is applied to the control of multiple UAV's which have the mission of searching limited area. Several numerical demonstrations show the proposed algorithm has superior results to those of behavior based neural network controller which is designed by intuition.

• Journal of Digital Contents Society
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• v.19 no.8
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• pp.1545-1554
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• 2018

In order to support the mobility of the wireless devices, at least two APs (Access Points) must be arranged in a single AP area to maintain communication area. In the WLAN (Wireless LAN) environment, seamless handover is one of the most important issues in terms of effective utilization of wireless networks and maximization of services for users. On the other hand, SDN (Software-Defined Networking), which is emerging rapidly in recent years, is revolutionizing network management in terms of flexibility, fine control, and convenience. SDN originally reduces latency time or increases network robustness by real-time flow table control reducing or bypassing paths between switches in LAN-based data centers. In this study, we apply OpenFlow, a SDN platform focused on wired LAN, to a dense WLAN environment using legacy APs to implement and evaluate seamless handover for streaming services of digital contents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2111-2131
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• 2015

Tiered wireless sensor network is a network model of flexibility and robustness, which consists of the traditional resource-limited sensor nodes and the resource-abundant storage nodes. In such architecture, collected data from the sensor nodes are periodically submitted to the nearby storage nodes for archive purpose. When a query is requested, storage nodes also process the query and return qualified data as the result to the base station. The role of the storage nodes leads to an attack prone situation and leaves them more vulnerable in a hostile environment. If any of them is compromised, fake data may be injected into and/or qualified data may be discarded. And the base station would receive incorrect answers incurring malfunction to applications. In this paper, an efficient verifiable top-k query processing scheme called EVTQ is proposed, which is capable of verifying the authentication and completeness of the results. Collected data items with the embedded information of ordering and adjacent relationship through a hashed message authentication coding function, which serves as a validation code, are submitted from the sensor nodes to the storage nodes. Any injected or incomplete data in the returned result from a corresponded storage node is detected by the validation code at the base station. For saving communication cost, two optimized solutions that fuse and compress validation codes are presented. Experiments on communication cost show the proposed method is more efficiency than previous works.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.659-669
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• 2010

The P2P IPTV will create a new paradigm for the Internet services. However, it cannot guarantee the reliability of their server and QoS because of using common Internet users(peers) for SIP server or relay server, though the infrastructural cost is low. This paper proposes the ISP-based P2P IPTV architecture which can solute the limitations of conventional P2P-based IPTV. In this model, ISP can build P2P overlay network with ISP servers and directly manage each server needed for session connection. So, the servers have higher performance and better reliability than previous one. Besides, robustness is improved because each sever is set by P2P overlay network. To evaluate the characteristics of the ISP-based P2P IPTV architecture, we simulate it for some parameters which are end-to-end streaming delay time, connection delay time and traffic amount. We compared the proposed architecture with the conventional P2P architecture about video service and confirmed that the performance of ISP-based P2P IPTV is better than conventional P2P based IPTV.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.77-88
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• 2018

This paper proposes a RBFNN(Radial Basis Function Neural Network) based decentralized adaptive tracking control scheme using PSO(Particle Swarm Optimization) for an uncertain electrically driven robot system with input saturation. Practically, the magnitudes of input voltage and current signals are limited due to the saturation of actuators in robot systems. The proposed controller overcomes this input saturation and does not require any robot link and actuator model parameters. The fitness function used in the presented PSO scheme is expressed as a multi-objective function including the magnitudes of voltages and currents as well as the tracking errors. Using a PSO scheme, the control gains and the number of the RBFs are tuned automatically and thus the performance of the control system is improved. The stability of the total control system is guaranteed by the Lyapunov stability analysis. The validity and robustness of the proposed control scheme are verified through simulation results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.703-713
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• 2015

The linking system between the control system and the field devices in the existing EMS/SCADA, in order to increase the reliability of the data, and access control through the separation of external network. Currently, There is a tendency that the need for connection to an external network that takes into account the economic aspect, systematic management and efficiency of operations is increasing. Such is evolved linkage section, is to have more security vulnerabilities than in the past, Eventually communication EMS/SCADA linkage section requires special management method. In this paper, taking into account the domestic environment, were presented the security Certification and Accreditation technology that was applied to serial DNP3 and TCP/IP based DNP3 that are mainly used in EMS/SCADA linkage section. Presented to security of Certification and Accreditation technology, divided into Resource Robustness Test and Malicious Packet Test for evaluate the safety. Each of the security requirements and evaluation method in proposed technology, is an attempt to present the differentiation of the existing Certification and Accreditation technology.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.3
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• pp.95-106
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• 2000

The load frequency control of power system is one of important subjects in view of system operation and control. That is even though the rapid load disturbances were applied to the given power system, the stable and reliable power should be supplied to the users, converging unconditionally and rapidly the frequency deviations and the tie-line power flow one on each area into allowable boundary limits. Nonetheless of such needs, if the internal parameter perturbation and the sudden load variation were given, the unstable phenomenal of power system can be often brought out because of the large frequency deviation and the unsuppressible power line one. Therefore, it is desirable to design the robust neuro-fuzzy controller which can stabilize effectively the given power system as soon as possible. In this paper the robust neuro-fuzzy controller was proposed and applied to control of load frequency over multi-area power system. The architecture and algorithm of a designed NFC(Neuro-Fuzzy Controller) were consist of fuzzy controller and neural network for auto tuning of fuzzy controller. The adaptively learned antecedent and consequent parameters of membership functions in fuzzy controller were acquired from the steepest gradient method for error-back propagation algorithm. The performances of the resultant NFC, that is, the steady-state deviations of frequency and tie-line power flow and the related dynamics, were investigated and analyzed in detail by being applied to the load frequency control of multi-area power system, when the perturbations of predetermined internal parameters. Through the simulation results tried variously in this paper for disturbances of internal parameters and external stepwise load stepwise load changes, the superiorities of the proposed NFC in robustness and adaptive rapidity to the conventional controllers were proved.