• Journal of Korea Multimedia Society
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• v.5 no.3
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• pp.316-322
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• 2002

In this paper we consider continuous block allocation scheme of UNIX file system to support real time retrieval service. The proposed block allocation scheme is designed to place real time data at appropriate disk block location in considering the consume-rate that is given with real time data. To effectively determine the disk block location we analyze the relationship between consume-rate and the two variable factors that are the number of continuous blocks and the cylinder distance of logically consecutive data. In traditional UNIX block allocation scheme it is in fact impossible to find continuous free disk blocks in a specific cylinder location. Thus we propose new bitmap-based free block allocation scheme that enables to determine whether a block in specific cylinder location is free state, or not.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.11
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• pp.599-609
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• 2007

Due to the restrictions of Flash memory such as overwrite limitation and write/erase operational unit differences, block cleaning is required in Flash memory based file systems and known as a key factor on the performance of file systems. In this paper, we identify three parameters, namely utilization, invalidity and uniformity, and analyze how the parameters affect the cost of block cleaning. The analysis show that as uniformity degrades, the cost of block cleaning increases drastically. To overcome this problem, we design a new modification-aware(MODA) page allocation scheme that strives to keep uniformity high by separating frequently-updating data from infrequently-updating data. Real implementation experiments conducted on an embedded system show that the MODA scheme can actually enhance uniformity of Flash memory, which consequently leads to reduce the cost of block cleaning with an average of 123%, compared to the traditional sequential allocation scheme that is used in YAFFS.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.52-60
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• 1999

By implementing the Systems Engineering process for the aircraft preliminary design, functional analysis study is performed, hence Functional Interface Data Flow(FIDF) and Functional Flow Block Diagram(FFBD) are generated. Based on FIDF and FFBD, allocable and non-allocable design/performance/RM＆S requirements are allocated to the appropriate levels. Weight and cost tracking and design margin management methodologies are studied and implemented for the balanced aircraft design.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.1-7
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• 2016

In this paper, we propose in this paper present a novel locality data allocation policy as COLD(Correlated Locality Data) allocation policy. COLD is defined as a set of data that will be updated together later. By distributing a COLD into a NAND block separately, it can preserve th locality. In addition, by handling multiple COLD simultaneously, it can obtain the parallelism among NAND chips. We perform two experiment to demonstrate the effectiveness of the COLD data allocation policy. First, we implement COLD detector, and then, analyze a well-known workload. And we confirm the amount of COLD found depending on the size of data constituting the COLD. Secondly, we compared the traditional page-level mapping policy and COLD for garbage collection overhead in actual development board Cosmos OpenSSD. Experimental results have shown that COLD data allocation policy is significantly reduces the garbage collection overhead. Also, we confirmed that garbage collection overhead vary depending on the COLD size.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.387-398
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• 2006

In this paper, we propose a new page allocation scheme for flash memory file system. The proposed scheme allocates pages by exploiting the concept of Purity, which is defined as the fraction of blocks where valid Pages and invalid Pages are coexisted. The Pity determines the cost of block cleaning, that is, the portion of pages to be copied and blocks to be erased for block cleaning. To enhance the purity, the scheme classifies hot-modified data and cold-modified data and allocates them into different blocks. The hot/cold classification is based on both static properties such as attribute of data and dynamic properties such as the frequency of modifications. We have implemented the proposed scheme in YAFFS and evaluated its performance on the embedded board equipped with 400MHz XScale CPU, 64MB SDRAM, and 64MB NAND flash memory. Performance measurements have shown that the proposed scheme can reduce block cleaning time by up to 15.4 seconds with an average of 7.8 seconds compared to the typical YAFFS. Also, the enhancement becomes bigger as the utilization of flash memory increases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.99-105
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• 2022

This paper deals with the problem of appropriately allocating multiple processors arriving at the ready queue to the block in the user space of the main memory is divided into blocks of variable size at compilation time. The existing allocation methods, first fit(FF), best fit(BF), worst fit(WF), and next fit(NF) methods, had the disadvantage of waiting for a specific processor because they failed to allocate all processors arriving at the ready queue. The proposed algorithm in this paper is a simple block packing algorithm that allocates as many processors as possible to the largest block by sorting the size of the partitioned blocks(holes) and the size of the processor in the ready queue in descending order. The application of the proposed algorithm to nine benchmarking experimental data showed the performance of allocating all processors while having minimal internal fragment(IF) for all eight data except one data in which the weiting processor occurs due to partition errors.

• Journal of the Korean Society for Railway
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• v.10 no.3 s.40
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• pp.319-326
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• 2007

During the design phase of a system, which requires high reliability and safety such as aircraft, high speed train and nuclear power plant, reliability engineer must set up the target system reliability. To meet a reliability goal for the system, reliability allocation should be done gradually from the system to its element. For this end, first of all, we need to construct functional block diagram based on the design output and PWBS(Project Work Breakdown System). Another important input data for reliability allocation is the relationship between the cost and the reliability. In this study we investigate various reliability allocation models, which can be applicable to aircraft, vehicle, and power plant, and etc. And we suggest a proper reliability allocation model which can be effectively applicable to KTX-II high speed train to achieve the target system reliability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.1006-1013
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• 2009

This paper proposes a data stream allocation technique for fair capacity performance in multiuser multiple-input multiple-output (MIMO) systems using block diagonalization (BD) algorithm. Conventional studies have been focused on maximum sum capacity. Thus, there is a very large difference of capacity among users, since user capacity unfairly distributed according to each user channel environment. In additional, poor channel user has very small capacity, since base station allocates the power by using water-filling technique. Also, almost studies limited itself to obtain the additional gain by using the same number of data streams for all users. In this paper, we propose the technique for maximizing sum capacity under the fair performance constraint by allocating data stream according to user channel environment. Also, proposed algorithm has more gain of sum capacity and transmit power than conventional equal allocation via computer simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.20-39
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• 2020

This paper considers a downlink multi-carrier cooperative non-orthogonal multiple access (NOMA) transmission, where no direct link exists between the far user and the base station (BS), and the communication between them only relies on the assist of the near user. Firstly, the BS sends a superimposed signal of the far and the near user to the near user, and then the near user adopts simultaneous wireless information and power transfer (SWIPT) to split the received superimposed signal into two portions for energy harvesting and information decoding respectively. Afterwards, the near user forwards the signal of the far user by utilizing the harvested energy. A minimum data is required to ensure the quality of service (QoS) of the far user. We jointly optimize power allocation, subcarrier allocation, time allocation, the power allocation (PA) coefficient and the power splitting (PS) ratio to maximize the number of data bits received at the near user under the energy causality constraint, the minimum data constraint and the transmission power constraint. The block-coordinate descent method and the Lagrange duality method are used to obtain a suboptimal solution of this optimization problem. In the final simulation results, the superiority of the proposed NOMA scheme is confirmed compared with the benchmark NOMA schemes and the orthogonal multiple access (OMA) scheme.