• Convergence Security Journal
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• v.12 no.3
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• pp.35-43
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• 2012

The explosive growth of Internet traffic cause by smart equipment such as smart phone has led to a dramatic increase in demand for data transmission capacity and network control architecture, which requires high transmission rates beyond the conventional transmission capability. Next generation networks are expected to be controlled by Generalized Multi-Protocol Label Switching(GMPLS) protocol suite and operating at multiple switching layers. In order to ensure the most efficient utilization of multilayer network resources, effective global provisioning that providing the network with the possibility of reacting in advance to traffic changes should be provided. In this paper, we proposes a new path selection scheme in multilayer optical networks based on the vertical PCE architecture and a different approach to efficiently exploit multiple PCE cooperation.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.17-26
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• 2022

Sensor Nodes play a major role to monitor and sense the variations in physical space in various real-time application scenarios. These nodes are powered by limited battery resources and replacing those resource is highly tedious task along with this it increases implementation cost. Thus, maintaining a good network lifespan is amongst the utmost important challenge in this field of WSN. Currently, energy efficient routing techniques are considered as promising solution to prolong the network lifespan where multi-hop communications are performed by identifying the most energy efficient path. However, the existing scheme suffer from performance related issues. To solve the issues of existing techniques, a novel hybrid technique by merging particle swarm optimization and game theory model is presented. The PSO helps to obtain the efficient number of cluster and Cluster Head selection whereas game theory aids in finding the best optimized path from source to destination by utilizing a path selection probability approach. This probability is obtained by using conditional probability to compute payoff for agents. When compared to current strategies, the experimental study demonstrates that the proposed GTPSO strategy outperforms them.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.40-47
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• 1994

In this paper, Micro-Genetic algorithms($\mu$-GAs) is proposed on a minimum-time path planning for robot manipulator. which is a kind of optimization algorithm. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computation burden and can`t often find the optimaul values. One way to overcome such difficulties is to apply the Micro-Genetic Algorithms, which can allow to find the optimul values, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Micro-Genetic Algorithms. The effectiveness of the proposed method is demonstrated using the 2 d.o.f plannar Robot manipulator.

• Journal of Communications and Networks
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• v.5 no.3
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• pp.230-239
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• 2003

In this paper, we propose a framework to study how to route packets efficiently in multipath communication networks. Two traffic congestion control techniques, namely, flow assignment and packet scheduling, have been investigated. The flow assignment mechanism defines an optimal splitting of data traffic on multiple disjoint paths. The resequencing delay and the usage of the resequencing buffer can be reduced significantly by properly scheduling the sending order of all packets, say, according to their expected arrival times at the destination. To illustrate our model, and without loss of generality, Gaussian distributed end-to-end path delays are used. Our analytical results show that the techniques are very effective in reducing the average end-to-end path delay, the average packet resequencing delay, and the average resequencing buffer occupancy for various path configurations. These promising results can form a basis for designing future adaptive multipath protocols.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.356-367
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• 2007

In large networks, maintaining precise global network state information is impossible. The imprecise network state information has significant impacts on Quality-of-Service(QoS) routing and path establishment. In this paper, we develop analytical models for investigating the QoS routing schemes that are designed to tolerate imprecise network state information, and study the performance of various QoS routing schemes, including randomized routing, multi-path routing, and probability based routing, using both the models and simulations. We further propose a new mechanism, called local rerouting, that improves the effectiveness of QoS path establishment in the presence of imprecise global network state information. Local rerouting is orthogonal to existing schemes for dealing with imprecise state information and can be used in conjunction with them to alleviate the impacts of the imprecise information. The results of our performance study indicate that local rerouting is robust and effective.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.498-509
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• 2010

In this paper, a waypoint guidance law Line Tracking algorithm is designed for testing an Unmanned Airship. In order to verify, we develop an autonomous flight control and test system of unmanned airship. The flight test system is composed FCC (Flight Control Computer), GCS (Ground Control System), Autopilot & Guidance program, GUI (Graphic User Interface) based analysis program, and Test Log Sheet for the management of flight test data. It contains flight test results of single-path & multi-path following, one point continuation turn, LOS guidance, and safe mode for emergency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.855-857
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• 2011

In this paper, we proposed EEAR(Efficient Energy Alternative Routing). This is a method of selecting a backup node for path routing management. When some node disconnection on the path routing, using pre-selected backup node provides immediately recover the path recovery. When selecting a Step-Parents node on the path management, the node' s energy level and distance information are cared in context-awareness. This not only increased the system' s capacity cost effectively, but also reduce transmission power entire nodes consume energy. As a result, each node could efficiently management and improves the life time for mobile host and extends system coverage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.20-23
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• 2004

In non-selective frequency environment, it is difficult to take the advantage of path diversity. In the literature, some methods have been proposed to solve the issue. This paper presents a new method to obtain the resolvable path in Indoor Multi-carrier Code Division Multiple Access (MC-CDMA) system by using downlink beam forming. With the aid of downlink beamforming, the most reliable path is found and chosen for the communication link. The new approach is evaluated in term of bit error rate (BER) and power consumption. The simulation results show that the new approach can get better BER performance. However, the cost of BER improvement is a small degradation in power reservation.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.149-158
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• 2005

The object of this paper is to develop the shortest path algorithm. The existing shortest path algorithm models are developed while considering travel time and travel distance. A few problems occur in these shortest path algorithm models, which have paid no regard to cognition of users, such as when user who doesn't have complete information about the trip meets a strange road or when the route searched from the shortest path algorithm model is not commonly used by users in real network. This paper develops a shortest path algorithm model to provide ideal route that many people actually prefer. In order to provide the ideal shortest path with the consideration of travel time, travel distance and road cognition, travel time is predicted by using Kalman filtering and travel distance is predicted by using GIS attributions. The road cognition is considered by using space data of GIS. Optimal routes provided from this paper are shortest distance path, shortest time path, shortest path considering distance and cognition and shortest path considering time and cognition.

• Steel and Composite Structures
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• v.15 no.4
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• pp.451-466
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• 2013

This paper deals with the multi-objective optimization of tire reinforcement structures such as the tread belt and the carcass path. The multi-objective functions are defined in terms of the discrete-type design variables and approximated by artificial neutral network, and the sensitivity analyses of these functions are replaced with the iterative genetic evolution. The multi-objective optimization algorithm introduced in this paper is not only highly CPU-time-efficient but it can also be applicable to other multi-objective optimization problems in which the objective function, the design variables and the constraints are not continuous but discrete. Through the illustrative numerical experiments, the fiber-reinforced tire belt structure is optimally tailored. The proposed multi-objective optimization algorithm is not limited to the tire reinforcement structure, but it can be applicable to the generalized multi-objective structural optimization problems in various engineering applications.