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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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KIISE Transactions on Computing Practices
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Journal DOI :
Korean Institute of Information Scientists and Engineers
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Volume & Issues
Volume 21, Issue 12 - Dec 2015
Volume 21, Issue 11 - Nov 2015
Volume 21, Issue 10 - Oct 2015
Volume 21, Issue 9 - Sep 2015
Volume 21, Issue 8 - Aug 2015
Volume 21, Issue 7 - Jul 2015
Volume 21, Issue 6 - Jun 2015
Volume 21, Issue 5 - May 2015
Volume 21, Issue 4 - Apr 2015
Volume 21, Issue 3 - Mar 2015
Volume 21, Issue 2 - Feb 2015
Volume 21, Issue 1 - Jan 2015
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Design and Implementation of an Automated Inter-connection Tool for Multi-Point OpenFlow Sites
Na, TaeHeum ; Kim, JongWon ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 1~12
DOI : 10.5626/KTCP.2015.21.1.1
To realize futuristic services with agility, the role of the experimental facility (i.e., testbed) based on integrated resources has become important, so that developers can flexibly utilize the dynamic provisioning power of software-defined networking and cloud computing. Following this trend, an OpenFlow-based SDN testbed environment, denoted as OF@TEIN, connects multiple sites with unique SmartX Racks (i.e., virtualization-enabled converged resources). In this paper, in order to automate the multi-point L2 (i.e., Ethernet) inter-connection of OpenFlow islands, we introduce an automated tool to configure the required Network Virtualization using Generic Routing Encapsulation (NVGRE) tunneling. With the proposed automation tool, the operators can efficiently and quickly manage network inter-connections among multiple OpenFlow sites, while letting developers to control their own traffic flows for service realization experiments.
A Technique for Provisioning Virtual Clusters in Real-time and Improving I/O Performance on Computational-Science Simulation Environments
Choi, Chanho ; Lee, Jongsuk Ruth ; Kim, Hangi ; Jin, DuSeok ; Yu, Jung-lok ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 13~18
DOI : 10.5626/KTCP.2015.21.1.13
Computational science simulations have been used to enable discovery in a broad spectrum of application areas, these simulations show irregular demanding characteristics of computing resources from time to time. The adoption of virtualized high performance cloud, rather than CPU-centric computing platform (such as supercomputers), is gaining interest of interests mainly due to its ease-of-use, multi-tenancy and flexibility. Basically, provisioning a virtual cluster, which consists of a lot of virtual machines, in a real-time has a critical impact on the successful deployment of the virtualized HPC clouds for computational science simulations. However, the cost of concurrently creating many virtual machines in constructing a virtual cluster can be as much as two orders of magnitude worse than expected. One of the main factors in this bottleneck is the time spent to create the virtual images for the virtual machines. In this paper, we propose a novel technique to minimize the creation time of virtual machine images and improve I/O performance of the provisioned virtual clusters. We also confirm that our proposed technique outperforms the conventional ones using various sets of experiments.
An Algorithm for Identifying the Change of the Current Traffic Congestion Using Historical Traffic Congestion Patterns
Lee, Kyungmin ; Hong, Bonghee ; Jeong, Doseong ; Lee, Jiwan ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 19~28
DOI : 10.5626/KTCP.2015.21.1.19
In this paper, we proposed an algorithm for the identification of relieving or worsening current traffic congestion using historic traffic congestion patterns. Historical congestion patterns were placed in an adjacency list. The patterns were constructed to represent spatial and temporal length for status of a congested road. Then, we found information about historical traffic congestions that were similar to today's traffic congestion and will use that information to show how to change traffic congestion in the future. The most similar pattern to current traffic status among the historical patterns corresponded to starting section of current traffic congestion. One of our experiment results had average error when we compared identified changes of the congestion for one of the sections in the congestion road by using our proposal and real traffic status. The average error was 15 minutes. Another result was for the long congestion road consisting of several sections. The average error for this result was within 10 minutes.
A Fault-tolerant Inertial Navigation System for UAVs Based on Partition Computing
Jung, Byeongyong ; Kim, Jungguk ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 29~39
DOI : 10.5626/KTCP.2015.21.1.29
When new inertial navigation systems for an unmanned aerial vehicles are being developed and tested, construction of a fault-tolerant system is required because of various types of hazards caused by S/W and H/W faults. In this paper, a new fault-tolerant flight system that can be deployed into one or more FCCs (Flight Control Computers) is introduced, based on a partition scheme wherein each OFP (Operational Flight Program) partition uses an independent CPU and memory slot. The new fault-tolerant navigation system utilizes one or two FCCs, and executes a primary navigation OFP under development and a stable shadow OFP partition on each node. The fault-tolerant navigation system based on a single FCC can be used for UAVs with small payloads. For larger UAVs, an additional FCC with two OFP partitions can be used to provide both H/W and S/W fault-tolerance. The developed fault-tolerant navigation system significantly removes various hazards in testing new navigation S/Ws for UAVs.
Influence Maximization against Social Adversaries
Jeong, Sihyun ; Noh, Giseop ; Oh, Hayoung ; Kim, Chong-Kwon ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 40~45
DOI : 10.5626/KTCP.2015.21.1.40
Online social networks(OSN) are very popular nowadays. As OSNs grows, the commercial markets are expanding their social commerce by applying Influence Maximization. However, in reality, there exist more than two players(e.g., commercial companies or service providers) in this same market sector. To address the Influence Maximization problem between adversaries, we first introduced Influence Maximization against the social adversaries' problem. Then, we proposed an algorithm that could efficiently solve the problem efficiently by utilizing social network properties such as Betweenness Centrality, Clustering Coefficient, Local Bridge and Ties and Triadic Closure. Moreover, our algorithm performed orders of magnitudes better than the existing Greedy hill climbing algorithm.
Research Capability Enhancement System Based on Prescriptive Analytics
Gim, Jangwon ; Jung, Hanmin ; Jeong, Do-Heon ; Song, Sa-Kwang ; Hwang, Myunggwon ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 46~51
DOI : 10.5626/KTCP.2015.21.1.46
The explosive growth of data and the rapidly changing technical social evolution new analysis paradigm for predicting and reacting the future the past and present ig data. Prescriptive analysis has a fundamental difference because can support specific behaviors and results according to user's goals with defin researchers establish judgments and activities achiev the goals. However research methods not widely implemented and even the terminology, Prescriptive analysis, is still unfamiliar. This paper thus propose an infrastructure in the prescriptive analysis field with key considerations for enhancing capability of researchers through a case study based on InSciTe Advisory developed with scientific big data. InSciTe Advisory system s developed in 2013, and offers a prescriptive analytics report which contains various As-Is analysis results and To-Be analysis results 5W1H methodology. InSciTe Advisory therefore shows possibility strategy aims to reach a target role model group. Through the availability and reliability of the measurement model the evaluation results obtained relative advantage of 118.8% compared to Elsevier SciVal.
An Analysis on the Performance of TRIM Commands on SSDs and its Application to the Ext4 File System
Son, Hyobong ; Lee, Youngjae ; Kim, Yongserk ; Kim, Jin-Soo ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 52~57
DOI : 10.5626/KTCP.2015.21.1.52
In this paper, we analyze the performance of the TRIM commands on various SSDs and, based on our analysis results, we enhance the performance of these TRIM commands in the Ext4 file system. We observed that the performance of the TRIM commands improves as the size of the LBA-range increases, the sector number is aligned and continuous or more LBA-ranges are notified via a single TRIM command. However, although the performance is better when multiple LBA-ranges are informed by a single TRIM command, the Ext4 file system issues a single TRIM command for every LBA-range. In this paper, we modify the Ext4 file system to convey at most 64 LBA-ranges per TRIM command. Evaluations through Filebench show that the performance of file deletion operations is improved by up to 35%.
Fountain Code-based Hybrid P2P Storage Cloud
Park, Gi Seok ; Song, Hwangjun ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 58~63
DOI : 10.5626/KTCP.2015.21.1.58
In this work, we present a novel fountain code-based hybrid P2P storage system that combines cloud storage with P2P storage. The proposed hybrid storage system minimizes data transmission time while guaranteeing high data retrieval and data privacy. In order to guarantee data privacy and storage efficiency, the user transmits encoded data after performing fountain code-based encoding. Also, the proposed algorithm guarantees the user's data retrieval by storing the data while considering each peer's survival probability. The simulation results show that the proposed algorithm enables fast completion of the upload transmission while satisfying the required data retrieval and supporting the privacy of user data under the system parameters.
Place Recognition Using Ensemble Learning of Mobile Multimodal Sensory Information
Lee, Chung-Yeon ; Lee, Beom-Jin ; On, Kyoung-Woon ; Ha, Jung-Woo ; Kim, Hong-Il ; Zhang, Byoung-Tak ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 64~69
DOI : 10.5626/KTCP.2015.21.1.64
Place awareness is an essential for location-based services that are widely provided to smartphone users. However, traditional GPS-based methods are only valid outdoors where the GPS signal is strong and also require symbolic place information of the physical location. In this paper, environmental sounds and images are used to recognize important aspects of each place. The proposed method extracts feature vectors from visual, auditory and location data recorded by a smartphone with built-in camera, microphone and GPS sensors modules. The heterogeneous feature vectors were then learned by an ensemble learning method that learns each group of feature vectors for each classifier respectively and votes to produce the highest weighted result. The proposed method is evaluated for place recognition using a data group of 3000 samples in six places and the experimental results show a remarkably improved recognition accuracy when using all kinds of sensory data comparing to results using data from a single sensor or audio-visual integrated data only.
SPQI: An Efficient Continuous Range Query Indexing Structure for a Mobile Environment
Lee, JongHyeok ; Jung, HaRim ; Youn, Hee Yong ; Kim, Ung-Mo ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 70~75
DOI : 10.5626/KTCP.2015.21.1.70
In this paper, we explore the efficient processing of continuous range queries over a huge number of moving objects, each of which retrieves the moving objects that are currently located within a geographic query region of interest. The moving objects should continually communicate with the server to report their current locations, so as to keep the results of the continuous range queries up-to-date. However, this increases the server workload and involves a enormous amount of communication as the number of continuous range queries and the moving objects becomes enormous. In this paper, we adopt an approach where we leverage available memory and computational resources of the moving objects in order to resolve these problems. To this end, we propose a query indexing structure, referred to as the Space Partitioning Query Index(SPQI), which enables the server to efficiently cooperate with the moving objects for processing continuous range queries. SPQI improves system performance in terms of server workload and communication cost. Through simulations, we show the superiority of SPQI.
Efficient Top-k Query Processing Algorithm Using Grid Index-based View Selection Method
Hong, Seungtae ; Youn, Deulnyeok ; Chang, Jae Woo ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 76~81
DOI : 10.5626/KTCP.2015.21.1.76
Research on top-k query processing algorithms for analyzing big data have been spotlighted recently. However, because existing top-k query processing algorithms do not provide an efficient index structure, they incur high query processing costs and cannot support various types of queries. To solve these problems, we propose a top-k query processing algorithm using a view selection method based on a grid index. The proposed algorithm reduces the query processing time by retrieving the minimum number of grid cells for the query range, by using a grid index-based view selection method. Finally, we show from our performance analysis that the proposed scheme outperforms an existing scheme, in terms of both query processing time and query result accuracy.
Quality Adaptation Scheme for Improving QoE of DASH-based VBR Video Streaming Service
Yun, Dooyeol ; Chung, Kwangsue ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 82~87
DOI : 10.5626/KTCP.2015.21.1.82
There are many current researches that are looking to improve the quality of HTTP adaptive streaming services. However, the existing schemes have a serious problem of QoE (Quality of Experience) degradation because few consider VBR video transmission. To cope with this problem, in this paper, we proposed a novel media quality adaptation scheme called CB-DASH (Content and Buffer-aware DASH). The proposed scheme controlled the video quality considering the VBR characteristics of video and the client's buffer state. Through the simulation, we proved that our scheme accomplished a more accurate estimated bandwidth than the conventional DASH and improved the QoE of streaming service.
Page Replacement Algorithm for Improving Performance of Hybrid Main Memory
Lee, Minhoe ; Kang, Dong Hyun ; Kim, Junghoon ; Eom, Young Ik ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 88~93
DOI : 10.5626/KTCP.2015.21.1.88
In modern computer systems, DRAM is commonly used as main memory due to its low read/write latency and high endurance. However, DRAM is volatile memory that requires periodic power supply (i.e., memory refresh) to sustain the data stored in it. On the other hand, PCM is a promising candidate for replacement of DRAM because it is non-volatile memory, which could sustain the stored data without memory refresh. PCM is also available for byte-addressable access and in-place update. However, PCM is unsuitable for using main memory of a computer system because it has two limitations: high read/write latency and low endurance. To take the advantage of both DRAM and PCM, a hybrid main memory, which consists of DRAM and PCM, has been suggested and actively studied. In this paper, we propose a novel page replacement algorithm for hybrid main memory. To cope with the weaknesses of PCM, our scheme focuses on reducing the number of PCM writes in the hybrid main memory. Experimental results shows that our proposed page replacement algorithm reduces the number of PCM writes by up to 80.5% compared with the other page replacement algorithms.
MCMC Algorithm for Dirichlet Distribution over Gridded Simplex
Sin, Bong-Kee ;
KIISE Transactions on Computing Practices, volume 21, issue 1, 2015, Pages 94~99
DOI : 10.5626/KTCP.2015.21.1.94
With the recent machine learning paradigm of using nonparametric Bayesian statistics and statistical inference based on random sampling, the Dirichlet distribution finds many uses in a variety of graphical models. It is a multivariate generalization of the gamma distribution and is defined on a continuous (K-1)-simplex. This paper presents a sampling method for a Dirichlet distribution for the problem of dividing an integer X into a sequence of K integers which sum to X. The target samples in our problem are all positive integer vectors when multiplied by a given X. They must be sampled from the correspondingly gridded simplex. In this paper we develop a Markov Chain Monte Carlo (MCMC) proposal distribution for the neighborhood grid points on the simplex and then present the complete algorithm based on the Metropolis-Hastings algorithm. The proposed algorithm can be used for the Markov model, HMM, and Semi-Markov model for accurate state-duration modeling. It can also be used for the Gamma-Dirichlet HMM to model q the global-local duration distributions.