• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.435-447
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• 2006

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.191-200
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• 2007

We propose the QoS (Quality of Service) assurance model for AMR (Adaptive MultiRate) voice users considering the capacity and service quality jointly in downlink WCDMA system. For this purpose, we introduce a new system performance measure and the number-based AMR mode allocation scheme. The proposed number-based AMR mode allocation can be operated only with the information of total number of ongoing users. Therefore, it can be more simply implemented than the existing power-based allocation. The proposed system performance measure considers the stochastic variations of AMR modes of ongoing users and can be analytically obtained using CTMC (Continuous Time Markov Chain) modeling. In order to validate the proposed analytical model, a discrete event-based simulation model is also developed. The performance measure obtained from the analytical model is in agreement with the simulation results and is expected to be useful for parameter optimization.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.159-161
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• 2000

This paper presents a GA for service restoration in electric power distribution systems. The aim of the service restoration is to restore service with maximizing the amount of total load restored while minimizing the number of required switch operation when a fault or overload occurs in distribution system. This paper develops GA for service restoration problem with constrained multi-objective optimization problem. The results show the effectiveness of the proposed method for solving the problem.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.580-590
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• 2018

Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cut carbon emission and improve system benefits. ADS is an evolving, complex and uncertain system, thus comprehensive model and effective optimization algorithms are needed. Battery swapping station (BSS) for EV service is an essential type of flexible load (FL). This paper establishes ADS planning model considering BSS firstly for the minimization of total cost including feeder investment, operation and maintenance, net loss and carbon tax. Meanwhile, immune binary firefly algorithm (IBFA) is proposed to optimize ADS planning. Firefly algorithm (FA) is a novel intelligent algorithm with simple structure and good convergence. By involving biological immune system into FA, IBFA adjusts antibody population scale to increase diversity and global search capability. To validate proposed algorithm, IBFA is compared with particle swarm optimization (PSO) algorithm on IEEE 39-bus system. The results prove that IBFA performs better than PSO in global search and convergence in ADS planning.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.445-459
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• 2008

This paper addresses a call admission control(CAC) scheme giving handoff calls a priority over new calls for OFDMA wireless communication systems. The characteristics of OFDMA system and a variety of user QoS (Quality of Service) requirements are incorporated into the proposed CAC scheme which consists of several optimization modules for the system resource(subcarriers and power) allocations. The mathematical models and its solution methods for the embedded resource allocation problems are proposed. Some extensive computational experiments are conducted to illustrate the superiority of our CAC.

• 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 the Korean Society for Precision Engineering
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• v.26 no.1
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• pp.17-23
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• 2009

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5A
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• pp.325-338
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• 2012

In this paper, a radio resource allocation scheme for a multi-hop relay transmission in cognitive radio (CR) system is proposed to support the employment of relay nodes in IEEE 802.22 standard for wireless regional area network (WRAN). An optimization problem is formulated to maximize the number of serving secondary users (SUs) under system constraints such as time-divided frame structure for multiplexing and a single resource-unit to every relay-hop. However, due to mathematical complexity, the optimization problem is solved with a sub-optimal manner instead, which takes three steps in the order of user selection, relay/path selection, and frequency selection. In the numerical analysis, this proposed solution is evaluated in terms of service rate denoting as the ratio of the number of serving SUs to the number of service-requesting SUs. Simulation results show the condition of adopting multi-hop relay and the optimum number of relaying hops by comparing with the performance of 1-hop system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4680-4697
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• 2017

In future, since the user experience plays a more and more important role in the development of today's communication systems, quality of experience (QoE) becomes a widely used metric, which reflects the subjective experience of end users for wireless service. In addition, the energy efficiency is an increasingly important problem with the explosive growth in the amount of wireless terminals and nodes. Hence, a QoE-aware energy efficiency maximization based joint user access selection and power allocation approach is proposed to solve the problem. We transform the joint allocation process to an optimization of energy efficiency by establishing an energy efficiency model, and then the optimization problem is solved by chaotic clone immune algorithm (CCIA). Numerical simulation results indicate that the proposed algorithm can efficiently and reliably improve the QoE and ensure high energy efficiency of networks.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.342-352
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• 2021

Multicast Routings is a big challenge due to limitations such as node power and bandwidth Mobile Ad-hoc Network (MANET). The path to be chosen from the source to the destination node requires protocols. Multicast protocols support group-oriented operations in a bandwidth-efficient way. While several protocols for multi-cast MANETs have been evolved, security remains a challenging problem. Consequently, MANET is required for high quality of service measures (QoS) such infrastructure and application to be identified. The goal of a MANETs QoS-aware protocol is to discover more optimal pathways between the network source/destination nodes and hence the QoS demands. It works by employing the optimization method to pick the route path with the emphasis on several QoS metrics. In this paper safe routing is guaranteed using the Secured Multicast Routing offered in MANET by utilizing the Ant Colony Optimization (ACO) technique to integrate the QOS-conscious route setup into the route selection. This implies that only the data transmission may select the way to meet the QoS limitations from source to destination. Furthermore, the track reliability is considered when selecting the best path between the source and destination nodes. For the optimization of the best path and its performance, the optimized algorithm called the micro artificial bee colony approach is chosen about the probabilistic ant routing technique.