• Korean Journal of Computational Design and Engineering
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• v.16 no.3
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• pp.236-245
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• 2011

Many researchers have recently studied multi-level formulation strategies to solve the MDO problems and they basically distributed the coupling compatibilities across all disciplines, while single-level formulations concentrate all the controls at the system-level. In addition, approximation techniques became remedies for computationally expensive analyses and simulations. This paper studies comparisons of the MDO methods with respect to computing performance considering both conventional sequential and modem distributed/parallel processing environments. The comparisons show Individual Disciplinary Feasible (IDF) formulation is the most efficient for sequential processing and IDF with approximation (IDFa) is the most efficient for parallel processing. Results incorporating to popular design examples show this finding. The author suggests design engineers should firstly choose IDF formulation to solve MDO problems because of its simplicity of implementation and not-bad performance. A single drawback of IDF is requiring more memory for local design variables and coupling variables. Adding cheap memories can save engineers valuable time and effort for complicated multi-level formulations and let them free out of no solution headache of Multi-Disciplinary Analysis (MDA) of the Multi-Disciplinary Feasible (MDF) formulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.1
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• pp.37-49
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• 2008

At the present time the task of designing a highly integrated ZigBee radio frequency (RF) receiver with an excellent coexistence performance is still very demanding and challenging. This paper presents a number of system issues and design considerations for a ZigBee RF receiver, namely IEEE 802.15.4, for coexistence with wireless devices in the 2.4-GHz ISM-band. With regard to IEEE 802.15.4, the paper analyzes receiver performance requirements for; system noise figure (NF), system third-order intercept point (system-IIP3), local oscillator phase noise and selectivity. Based on some assumptions, the paper illustrates the relationship between minimum detectable signal (MDS) and various situations that involve the effects of electromagnetic interference generated by other wireless devices. We infer the necessity of much more stringent specification requirements than the published standard for various wireless communication field environments

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• ETRI Journal
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• v.44 no.3
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• pp.450-461
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• 2022

The Gen-Z protocol is a memory semantic protocol between the memory and CPU used in computer architectures with large memory pools. This study presents the implementation of the Gen-Z hardware system configured using Gen-Z specification 1.0 and reports its performance. A hardware prototype of a DDR4 Gen-Z memory pool with an optimized character, a block device driver, and a file system for the Gen-Z hardware was designed. The Gen-Z IP was targeted to the FPGA, and a 512 GB Gen-Z memory pool was configured on an ×86 server. In the experiments, the latency and throughput of the Gen-Z memory were measured and compared with those of the local memory, SATA SSD, and NVMe using character or block device interfaces. The Gen-Z hardware exhibited superior throughput and latency performance compared with SATA SSD and NVMe at block sizes under 4 kB. The MySQL and File IO benchmark of Gen-Z showed good write performance in all block sizes and threads. Besides, it showed low latency in RocksDB's fillseq dbbench using the ext4 direct access filesystem.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.103-126
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• 2015

Compared to other countries, cloud computing in Korea is not popular especially in the government sector. One of the reasons for the current not-fully-blossomed situation is partly by early investment in huge government datacenters under Korea's e-government initiative; let alone, there was no strong control tower as well as no enforcing law and ordinances for driving such cloud computing initiative. However, in 2015 March 'Cloud Computing and Privacy Security Act' (hereinafter, Cloud Act) had been passed in the Parliament and from September 2015 Cloud Act was deployed in Korea. In U.S., FedRAMP (Federal Risk Assessment and Management Program) along with Obama Adminstration's 'Cloud First' strategy for U.S. federal institutions is the key momentum for federal cloud computing adoption. In 2015 January, U.S. Congressional Research Service (CRS) has published an extensive monitoring report for cloud computing in U.S. federal institutions. The CRS report which monitored U.S. government cloud computing implementation is indeed a good guideline for Korean government cloud computing services. For this reason, the purpose of the study is to (1) identify important aspects of the enacted Korean Cloud Act, (2) describe recent U.S. federal government cloud computing status, (3) suggest strategy and key strategy factors for facilitating cloud adoption in public organizations reflecting SDLC strategy, wherein.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.595-601
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• 2010

Desktop virtualization technology running on the local computing system in the process of resource depletion or degradation, such as upgrading the system to solve problems and manage critical information and systems must be protected. In addition, a virtualized environment by constructing a convenient stand-virtualized infrastructure and user space, and security from external attack or internal flaw or a problem, even if the service fails to respond quickly and should help to recover. In this paper, a comprehensive virtualization technology based on the client's desktop virtualization technology elements needed to find a local computing environment more comfortable and stable in the proposed new virtualization technologies.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.471-477
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• 2005

This paper proposes an efficient constraint-based optimization model for the design of 3G mobile networks, such as universal mobile telecommunications system (UMTS). The model concerns about finding a set of sites for locating radio network controllers (RNCs) from a set of pre-defined candidate sites, and at the same time optimally assigning node Bs to the selected RNCs. All these choices must satisfy a set of constraints and optimize an objective function. This problem is NP-hard and consequently cannot be practically solved by exact methods for real size networks. Thus, this paper proposes a hybrid search strategy for tackling this complex and combinatorial optimization problem. The proposed hybrid search strategy is composed of three phases: A constraint satisfaction method with an embedded problem-specific goal which guides the search for a good initial solution, an optimization phase using local search algorithms, such as tabu algorithm, and a post­optimization phase to improve solutions from the second phase by using a constraint optimization procedure. Computational results show that the proposed search strategy and the model are highly efficient. Optimal solutions are always obtained for small or medium sized problems. For large sized problems, the final results are on average within $5.77\%$ to $7.48\%$ of the lower bounds.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.591-593
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• 2022

This paper proposes a partial offloading system for minimizing application service processing latency in an FEC (Fog/Edge Computing) environment, and it analyzes the offloading effect of the proposed system against local-only and edge-server-only processing based on network load. A partial offloading algorithm based on reconstruction linearization of multi-branch structures is included in the proposed system, as is an optimal collaboration algorithm between mobile devices and edge servers [1,2]. The experiment was conducted by applying layer scheduling to a logical CNN model with a DAG topology. When compared to local or edge-only executions, experimental results show that the proposed system always provides efficient task processing strategies and processing latency.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.133-142
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• 2012

This paper presents a salient region detection algorithm for auto-focusing based on the characteristics of a human's visual attention. To describe the saliency at the local, regional, and global levels, this paper proposes a set of novel features including multi-scale local contrast, variance, center-surround entropy, and closeness to the center. Those features are then prioritized to produce a saliency map. The major advantage of the proposed approach is twofold; i) robustness to changes in focus and ii) low computational complexity. The experimental results showed that the proposed method outperforms the existing low-level feature-based methods in the sense of both robustness and accuracy for auto-focusing.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.15 no.1
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• pp.1-17
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• 2011

A new method for option pricing based on the trinomial tree method is introduced. The new method calculates the local average of option prices around a node at each time, instead of computing prices at each node of the trinomial tree. Local averaging has a smoothing effect to reduce oscillations of the tree method and to speed up the convergence. The option price and the hedging parameters are then obtained by the compact scheme and the Richardson extrapolation. Computational results for the valuation of European and American vanilla and barrier options show superiority of the proposed scheme to several existing tree methods.