• Journal of Information Processing Systems
• /
• v.17 no.2
• /
• pp.297-305
• /
• 2021

Large amount of data is being generated in gaming servers due to the increase in the number of users and the variety of game services being provided. In particular, load balancing schemes for gaming servers are crucial consideration. The existing literature proposes algorithms that distribute loads in servers by mostly concentrating on load balancing and cooperative offloading. However, many proposed schemes impose heavy restrictions and assumptions, and such a limited service classification method is not enough to satisfy the wide range of service requirements. We propose a load balancing agent that combines the dynamic allocation programming method, a type of greedy algorithm, and proximal policy optimization, a reinforcement learning. Also, we compare performances of our proposed scheme and those of a scheme from previous literature, ProGreGA, by running a simulation.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.10
• /
• pp.116-126
• /
• 2001

This paper suggests a numerical method to find optimal geometric path and minimum-time motion for a spatial 6-link manipulator arm (PUMA 560 type). To find a minimum-time motion, the optimal geometric paths minimizing 2 different dynamic performance indices are searched first, and the minimum-time motions are searched on these optimal paths. In the algorithm to find optimal geometric paths, the objective functions (performance indices) are selected to minimize joint velocities, actuator forces or the combinations of them as well as to avoid one static obstacle. In the minimum-time algorithm the traveling time is expressed by the power series including 21 terms. The coefficients of the series are obtained using nonlinear programming to minimize the total traveling time subject to the constraints of velocity-dependent actuator forces.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2003.05c
• /
• pp.194-199
• /
• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The proposed neural network technique is the real time computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objects during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of objects. All of them request much memory space and time. Therefore the most reliable neural-network algorithm is derived for real-time matching of objects, which is composed of a dynamic programming algorithm based on sequence matching techniques.

• ETRI Journal
• /
• v.41 no.3
• /
• pp.326-336
• /
• 2019

A wireless power transfer technique can solve the power capacity problem in wireless rechargeable sensor networks (WRSNs). The charging strategy is a wide-spread research problem. In this paper, we propose a demand-based charging strategy (DBCS) for WRSNs. We improved the charging programming in four ways: clustering method, selecting to-be-charged nodes, charging path, and charging schedule. First, we proposed a multipoint improved K-means (MIKmeans) clustering algorithm to balance the energy consumption, which can group nodes based on location, residual energy, and historical contribution. Second, the dynamic selection algorithm for charging nodes (DSACN) was proposed to select on-demand charging nodes. Third, we designed simulated annealing based on performance and efficiency (SABPE) to optimize the charging path for a mobile charging vehicle (MCV) and reduce the charging time. Last, we proposed the DBCS to enhance the efficiency of the MCV. Simulations reveal that the strategy can achieve better performance in terms of reducing the charging path, thus increasing communication effectiveness and residual energy utility.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.6 s.177
• /
• pp.1633-1642
• /
• 2000

Like many other mechanical dynamic systems, flexible manipulator systems experience stiction or sticking friction, which may cause input-dependent instabilities. Manipulator performance can be enha nced by identifying friction but it is hard and expensive to measure friction by direct and precise sensing of contact displacements and forces. This study addresses the problem of identifying flexible manipulator joint friction. A dynamic model of a two-link flexible manipulator based upon finite element and Lagrange's method is constructed. The dynamic model includes the effects of joint compliances and actuator dynamics. Friction is also incorporated in the dynamic model to account for stick-slip at the joints. Next, the friction parameters are to be determined. The identification problem is posed as an optimization problem to be solved using nonlinear programming methods. A genetic algorithm is used to increase the convergence rate and the chances of finding the global optimum. The identified friction parameters are experimentally verified and it is expected that the identification technique is applicable to a system parameter identification problem associated with a wide class of nonlinear systems.

• Journal of Korean Institute of Industrial Engineers
• /
• v.27 no.3
• /
• pp.250-259
• /
• 2001

Given a tree structured network in which each node has its own demand and also stands for a candidate location of a potential facility, such as plant or warehouse, a capacitated facility location problem on the network (CFLPOT) is to decide capacitated facility locations so that the total demand occurred on the network can be satisfied from those facilities with the minimum cost. In this paper, we first introduce a mixed integer programming formulation for CFLPOT with two additional assumptions, the indivisible demand assumption and the contiguity assumption and then show that it can be reformulated as a tree partitioning problem with an exponential number of variables. We then show that it can be solved in O($n^2b$) time by utilizing the limited column generation method developed by Shaw (1993), where n is the total number of nodes in the network and b is the maximum facility capacity. We also develop a depth-first dynamic programming algorithm with a running time of O(nb) for finding the locally maximal reduced cost which plays an important role in the limited column generation method. Finally, we implement our algorithms on a set of randomly generated problems and report the computational results.

• Korean Management Science Review
• /
• v.13 no.3
• /
• pp.163-172
• /
• 1996

According to flying hours, aircraft engines require regular overhaul for preventive maintenance. Because of hostile defense environment of Republic of Korea, the aircraft of republic of Korea Air Force(ROKAF) have been operated at the maximum level of availability and have similar overhaul schedule in several months. The concentration of overhaul schedule in a short period demands additional spare engines far exceeding the spare engines for corrective maintenance. If ROKAF decides to purchase extra engines for the preventive maintenance, the extra engines will be used only for the preventive maintenance and will be excess inventory for the most of aircraft life ccle. Also, the procurement of extra engines is significant investment for ROKAF. To help ROKAF schedule the preventive maintenance without significant spending, this study develops a dynamic programming model that is solvable using an integer programming algorithm. The model provides the number of engines that should be overhauled for a month for multiple periods under given constraints. ROKAF actually used this model to solve a T-59 engine overhaul problem and saved about three billion won at one time. ROKAF plans to use this model continuously for T-59 and other weapon systems. Thus, saving for long term will be significant to ROKAF. Finally, with minor modification, this model can be applied to deciding the minimum number of spare engines for preventive maintenance.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.10
• /
• pp.3810-3830
• /
• 2015

In this paper, we investigate the differential game theoretic approach for distributed dynamic cooperative power control in cognitive radio ad hoc networks (CRANETs). First, a payoff function is defined by taking into consideration the tradeoff between the stock of accumulated power interference to the primary networks and the dynamic regulation of the transmit power of secondary users (SUs). Specifically, the payoff function not only reflects the tradeoff between the requirement for quickly finding the stable available spectrum opportunities and the need for better channel conditions, but also reveals the impact of the differentiated types of data traffic on the demand of transmission quality. Then the dynamic power control problem is modeled as a differential game model. Moreover, we convert the differential game model into a dynamic programming problem to obtain a set of optimal strategies of SUs under the condition of the grand coalition. A distributed dynamic cooperative power control algorithm is developed to dynamically adjust the transmit power of SUs under grand coalition. Finally, numerical results are presented to demonstrate the effectiveness of the proposed algorithm for efficient power control in CRANETs.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.8
• /
• pp.917-923
• /
• 1999

This paper proposes an efficient method of hydro-thermal scheduling in coordination with head variation and hydraulically coupled plants using Evolutionary Programing(EP). Based on the EP technique, the proposed algorithm is capable of determining the global optimal solutions. The constraints such a power balance condition, water available condition and transmission losses are embedded and satisfied throughout the proposed EP approach. The effectiveness of the proposed approach is demonstrated on the test systems and compared to those of other method. The results show that the new approach obtains a more highly optimal solutions than the conventional other methods such as newton-raphson method, Dynamic Programming(DP), LU factorization.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.4640-4661
• /
• 2018

To cope with the explosive growth of Internet services, Service Function Chaining (SFC) based on Software-defined Networking (SDN) is an emerging and promising technology that has been suggested to meet this challenge. Determining the placement of Virtual Network Functions (VNFs) and routing paths that optimize the network utilization and resource consumption is a challenging problem, particularly without violating service level agreements (SLAs). This problem is called the optimal SFC placement problem and an Integer Linear Programming (ILP) formulation is provided. A greedy heuristic solution is also provided based on an improved two-step mapping algorithm. The obtained experimental results show that the proposed algorithm can automatically place VNFs at the optimal locations and find the optimal routing paths for each online request. This algorithm can increase the average request acceptance rate by about 17.6% and provide more than 20-fold reduction of the computational complexity compared to the Greedy algorithm. The feasibility of this approach is demonstrated via NetFPGA-10G prototype implementation.