• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1276-1285
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• 2007

Since the TD-SCDMA (Time Division-Synchronous Code Division Multiple Access) system is based on TDD (Time Division Duplexing), the uplink and downlink can be allocated asymmetrically according to the traffic e.g. Web browsing. Although this asymmetric allocation can increase the frequency utilization, it may cause time slot opposing, which implies the time slot is assigned in opposing direction between cells. The time slot opposing can generate significant interference between cells, which results in severe performance degradation. In the paper, a novel dynamic channel allocation (DCA) is proposed in the TD-SCDMA system, to mitigate the impact of time slot opposing considering smart antenna. When the smart antenna is applied in the system, the inter-cell interference is largely affected by beam pattern and beam direction between neighboring cells. Therefore, the time slot opposing and smart antenna should be considered together in the DCA. The intensive simulations show that the proposed scheme can improve the system capacity compared to the conventional DCA schemes.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.36-48
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• 1999

Controlled transfer (CT) service has been recently proposed as a new ATM transfer capability for high-speed data applications, which used a credit-based flow control. This paper investigates buffer allocation schemes for CT service and proposes an improved dynamic bugger allocation scheme. In order to improve the responsiveness to a congestion, the proposed method is considered the load factor of a link when determining the amounts of virtual connection (VC)s buffer allocation. Also, in this paper we compare the performance of the proposed method with those of the existing buffer allocation methods such as flow controlled virtual channels (FCVC) and zero queueing flow control (ZQFC) through simulation. Simulation results show tat the proposed scheme exhibits a better performance than the existing schemes in terms of throughput, fairness, queue length and link utilization.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.9
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• pp.19-28
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• 2010

The GTS(Guaranteed Time Slot) of the IEEE 802.15.4 standard, which is the contention free access mechanism, is used for low-latency applications or applications requiring specific data bandwidth. But it has some problems such as delay of service due to FIFS(First In First Service) scheduling. In this paper, we proposes a weight based GTS allocation scheme for fair queuing in IEEE 802.15.4 LR-WPAN. The proposed scheme uses a weight that formed by how much more weight we give to the recent history than to the older history for a new GTS allocation. This scheme reduces service delay time and also guarantees transmission simultaneously within a limited time. The results of the performance analysis shows that our approach improves the performance as compared to the native explicit allocation mechanism defined in the IEEE 802.15.4 standard.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.567-575
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• 2011

The two most popular virtual machine allocation schemes, both match making and round robin, do consider hardware specifications such as CPU, RAM, and HDD, but not CPU usage, which results in balanced resource distribution, but not in balanced resource usage. Thus, in this paper a new virtual machine allocation scheme considering current CPU usage rate is proposed while retaining even distribution of node resources. In order to evaluate the performance of the proposed scheme, a cloud computing platform composed of three cloud nodes and one front end is implemented. The proposed allocation scheme was compared with both match making and round robin schemes. Experimental results show that the proposed scheme performs better in even distribution of overall CPU usage, which results in efficient load balancing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.7
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• pp.580-591
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• 2013

The Orthogonal Frequency Division Multiple Access (OFDMA) is considered as a novel modulation and multiple access technique for 4th generation wireless systems. In this paper, we formulate a base station's power allocation algorithm for each user to maximize the user's sum rate, subject to constraints on total power, bit error rate, and rate proportionality among the users for a better proportional rate adaptive (RA) resource allocation method for OFDMA based system. We propose a novel power allocation method based on the proportion of subcarrier allocation and the user's normalized proportionality constant. We adapt a greedy algorithm and waterfilling technique for allocating the subcarriers among the users. In an end-to-end simulation, we validate that the proposed technique has higher system capacity and lower CPU execution times, while maintaining the acceptable rate proportionality among users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.156-164
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• 2019

In this paper, we propose an efficient dynamic slot re-assignment scheme for swarming drone networks in which networks members merged and split frequently. The leader drone of each network recognizes the slot allocation information of neighbor networks by periodic information exchange among between the drones. Using the information, the leader drone makes a decision how to reallocate the slots between members in case of network merge. The non-competitive method in the proposed scheme can re-assign the slots without any slot collision and shows always superior performance than competitive scheme. The competitive method in the proposed scheme reduces the number of slots that should be re-assigned in case of network merge. The experimental performance analysis shows that the proposed scheme performs better or at least equal to the performance of the competitive scheme in a swarming drone network.

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.67-79
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• 2019

A warship equipped with Multi Function Radar(MFR) performs operations by evaluating the degree of threats based on threats' symptom and allocating the resource of MFR to the corresponding threats. This study suggests a simulation-based approach and greedy algorithm in order to effectively allocate the resource of an MFR for warships, and compares these two approaches. As a detection probability function depending on the amount of allocations to each threat, we consider linear and exponential functions. Experimental results show that both the simulation-based approach and greedy algorithm allocate resource similarly to the randomly generated threats, and the greedy algorithm outperforms the simulation-based approach in terms of computational perspective. For a various cases of threats, we analyze the results of MFR resource allocation using the greedy algorithm.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.501-508
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• 2020

His paper looks more closely at the Republic of Korea's (ROK) Navy submarine berth-allocation strategies, with the study's results ultimately resulting in the proposition of an integer programming model. Current submarine berth-allocation planning problems include the need for more minimal berth-shifting and general support service failures, as a lack of efficient submarine berth-allocation often leads to submarines unable to receive the support service they need due to the inadequacy of their assigned berths. Currently, the ROK Navy allocates berths by only taking available reserve resources and the full-capacity limits of support services into account. This paper expands upon this strategy, and proposes a model which would allow for submarine berth allocation planning to also take submarine support service scheduling into account, allowing for more efficient and timely submarine servicing. This proposed model in turn minimizes berth shifting, support service failures, and allows for full coordination with the submarine support service request schedule. The construction of this model was carried out through data gathered on the ROK Navy's fleets and forces, allowing for a more nuanced analysis of existing issues with submarine berth-allocation planning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.430-435
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• 2022

In this paper, we consider the non-orthogonal multiple access (NOMA) technique in the heterogeneous network (HetNET) consisting of a single macro base station (BS) and multiple small BSs, where the perfect successive interference cancellation is assumed for the NOMA signals. In this paper, we propose a deep learning-based user association and power allocation scheme to maximize the data rate in the NOMA-based HetNET. In particular, the proposed scheme includes the deep neural network (DNN)-based user association process for load balancing and the DNN-based power allocation process for data-rate maximization. Through the simulation assuming path loss and Rayleigh fading channels between BSs and users, the performance of the proposed scheme is evaluated, and it is compared with the conventional maximum signal-to-interference-plus-noise ratio (Max-SINR) scheme. Through the performance comparison, we show that the proposed scheme provides better sum rate performance than the conventional Max-SINR scheme.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.27-34
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• 2023

The optimal assignment problem between agents and tasks is known as one of the representative problems of combinatorial optimization and an NP-hard problem. This paper covers multi agent-multi task assignment problems with uncertain completion probability. The completion probabilities are generally uncertain due to endogenous (agent or task) or exogenous factors in the system. Assignment decisions without considering uncertainty can be ineffective in a real situation that has volatility. To consider uncertain completion probability mathematically, a mathematical formulation with stochastic programming is illustrated. We also present an algorithm by using the sample average approximation method to solve the problem efficiently. The algorithm can obtain an assignment decision and the upper and lower bounds of the assignment problem. Through numerical experiments, we present the optimality gap and the variance of the gap to confirm the performances of the results. This shows the excellence and robustness of the assignment decisions obtained by the algorithm in the problem with uncertainty.