• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.393-397
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• 2006

Significant increase of container flows in marine terminals requires more efficient automatic port systems. This paper presents a novel routing and collision avoidance algorithm of linear motor based shuttle cars using dynamic programming (DP). The proposed DP is accomplished online for determining optimal paths for each shuttle car. We apply our algorithm to Agile port terminal in USA.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.293-300
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• 2014

As energy harvesting communication systems emerge, there is a need for transmission schemes that dynamically adapt to the energy harvesting process. In this paper, after exhibiting a finite-horizon online throughput-maximizing scheduling problem formulation and the structure of its optimal solution within a dynamic programming formulation, a low complexity online scheduling policy is proposed. The policy exploits the existence of thresholds for choosing rate and power levels as a function of stored energy, harvest state and time until the end of the horizon. The policy, which is based on computing an expected threshold, performs close to optimal on a wide range of example energy harvest patterns. Moreover, it achieves higher throughput values for a given delay, than throughput-optimal online policies developed based on infinite-horizon formulations in recent literature. The solution is extended to include ergodic time-varying (fading) channels, and a corresponding low complexity policy is proposed and evaluated for this case as well.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1736-1737
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• 2007

Significant increase of container flows in marine terminals requires more efficient automatic port systems. This paper presents a novel routing and collision avoidance algorithm of linear motor based shuttle cars using random access sequence dynamic programming (RAS DP). The proposed RAS DP is accomplished online for determining optimal paths for each shuttle car.

• Journal of Navigation and Port Research
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• v.30 no.9
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• pp.773-777
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• 2006

Significant increase of container flows in the marine terminals requires more efficient port equipments such as logistic and transfer systems. This paper presents collision avoidance and routing approach based on dynamic programming (DP) algorithm for a linear motor based shuttle car which is considered as a new transfer system in the port terminals. Most of routing problems are focused on automatic guided vehicle (AGV) systems, but its solutions are hardly utilized for LM based shuttle cars since both are mechanically different. Our proposed DP is implemented for real-time searching of an optimal path for each shuttle car in the Agile port terminal located at California in USA.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.226-227
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• 2007

Significant increase of container flows in marine terminals requires more efficient automatic port systems. This paper presents a novel routing and collision avoidance algorithm of linear motor based shuttle cars using random access sequence dynamic programming (RAS DP). The proposed RAS DP is accomplished online for determining optimal paths for each shuttle car.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.107-112
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• 2016

Fastener is a very important component that is used in various areas in industry. Recently, various color fasteners are introduced. According to this, online inspection is required in this area. In this paper, an algorithm for the automatic extraction of the surface of color fastener using color information and dynamic programming is presented. The outer boundary of fastener is found using the difference of color that enables robust processing. The inner boundary of fastener is found by dynamic programming that uses the difference of brightness value within fixed area after converting image to polar coordinate. Experiments are done using the same parameters.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2074-2079
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• 2018

Global state space's optimal policy is used for offline controller in the form of table by using Dynamic Programming. If an optimal policy table has a large amount of control data, it is difficult to use the system in a low capacity system. To resolve these problem, controller using the compressed optimal policy table is proposed in this paper. A DCT is used for compression method and the cosine function is used as a basis. The size of cosine function decreased as the frequency increased. In other words, an essential information which is used for restoration is concentrated in the low frequency band and a value of small size that belong to a high frequency band could be discarded by quantization because high frequency's information doesn't have a big effect on restoration. Therefore, memory could be largely reduced by removing the information. The compressed output is stored in memory of embedded system in offline and optimal control input which correspond to state of plant is computed by interpolation with Inverse DCT in online. To verify the performance of the proposed controller, computer simulation was accomplished with a one link inverted pendulum.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.890-903
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• 2017

The problem of determining a smooth and collision-free path with maximum possible speed for a Mobile Robot (MR) which is chasing a moving target in a dynamic environment is addressed in this paper. Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. This paper presents GNP-RL based on predicting collision positions as a first attempt to apply it for MR navigation in dynamic environment. The combination between features of the proposed collision prediction and that of GNP-RL provides safe navigation (effective obstacle avoidance) in dynamic environment, smooth movement, and reducing the obstacle avoidance latency time. Simulation in dynamic environment is used to evaluate the performance of collision prediction based GNP-RL compared with that of two state-of-the art navigation approaches, namely, Q-Learning (QL) and Artificial Potential Field (APF). The simulation results show that the proposed GNP-RL outperforms both QL and APF in terms of smooth movement and safer navigation. In addition, it outperforms APF in terms of preserving maximum possible speed during obstacle avoidance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2095-2110
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• 2015

This paper presents a design for a throughput-efficient online relay selection scheme for dual-hop multi-relay cooperative networks. Problems arise with these networks due to unpredictability of the relaying link quality and high time-consumption to probe the dual-hop link. In this paper, we firstly propose a novel probing and relaying protocol, which greatly reduces the overhead of the dual-hop link estimation by leveraging the wireless broadcasting nature of the network. We then formulate an opportunistic relay selection process for the online decision-making, which uses a tradeoff between obtaining more link information to establish better cooperative relaying and minimizing the time cost for dual-hop link estimation to achieve higher throughput. Dynamic programming is used to construct the throughput-optimal control policy for a typically heterogeneous Rayleigh fading environment, and determines which relay to probe and when to transmit the data. Additionally, we extend the main results to mixed Rayleigh/Rician link scenarios, i.e., where one side of the relaying link experiences Rayleigh fading while the other has Rician distribution. Numerical results validate the effectiveness and superiority of our proposed relaying scheme, e.g., it achieves at least 107% throughput gain compared with the state of the art solution.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4364-4384
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• 2021

The dynamic network state and the mobility of the terminals make the service function chain (SFC) orchestration mechanisms based on static and deterministic assumptions hard to be applied in SDN/NFV mobile edge computing networks. Designing dynamic and online SFC orchestration mechanism can greatly improve the execution efficiency of compute-intensive and resource-hungry applications in mobile edge computing networks. In order to increase the overall profit of service provider and reduce the resource cost, the system running time is divided into a sequence of time slots and a dynamic orchestration scheme based on an improved column generation algorithm is proposed in each slot. Firstly, the SFC dynamic orchestration problem is formulated as an integer linear programming (ILP) model based on layered graph. Then, in order to reduce the computation costs, a column generation model is used to simplify the ILP model. Finally, a two-stage heuristic algorithm based on greedy strategy is proposed. Four metrics are defined and the performance of the proposed algorithm is evaluated based on simulation. The results show that our proposal significantly provides more than 30% reduction of run time and about 12% improvement in service deployment success ratio compared to the Viterbi algorithm based mechanism.