• Title/Summary/Keyword: distributed memory environment

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Forecasting of Iron Ore Prices using Machine Learning (머신러닝을 이용한 철광석 가격 예측에 대한 연구)

  • Lee, Woo Chang;Kim, Yang Sok;Kim, Jung Min;Lee, Choong Kwon
    • Journal of Korea Society of Industrial Information Systems
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    • v.25 no.2
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    • pp.57-72
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    • 2020
  • The price of iron ore has continued to fluctuate with high demand and supply from many countries and companies. In this business environment, forecasting the price of iron ore has become important. This study developed the machine learning model forecasting the price of iron ore a one month after the trading events. The forecasting model used distributed lag model and deep learning models such as MLP (Multi-layer perceptron), RNN (Recurrent neural network) and LSTM (Long short-term memory). According to the results of comparing individual models through metrics, LSTM showed the lowest predictive error. Also, as a result of comparing the models using the ensemble technique, the distributed lag and LSTM ensemble model showed the lowest prediction.

Towards Choosing Authentication and Encryption: Communication Security in Sensor Networks

  • Youn, Seongwook;Cho, Hyun-chong
    • Journal of Electrical Engineering and Technology
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    • v.12 no.3
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    • pp.1307-1313
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    • 2017
  • Sensor networks are composed of provide low powered, inexpensive distributed devices which can be deployed over enormous physical spaces. Coordination between sensor devices is required to achieve a common communication. In low cost, low power and short-range wireless environment, sensor networks cope with significant resource constraints. Security is one of main issues in wireless sensor networks because of potential adversaries. Several security protocols and models have been implemented for communication on computing devices but deployment these models and protocols into the sensor networks is not easy because of the resource constraints mentioned. Memory intensive encryption algorithms as well as high volume of packet transmission cannot be applied to sensor devices due to its low computational speed and memory. Deployment of sensor networks without security mechanism makes sensor nodes vulnerable to potential attacks. Therefore, attackers compromise the network to accept malicious sensor nodes as legitimate nodes. This paper provides the different security models as a metric, which can then be used to make pertinent security decisions for securing wireless sensor network communication.

Design and Implementation of CORBA Inter-ORB Protocol Based on Shared Memory for Communication Systems (통신 시스템을 위한 공유 메모리 기반 CORBA 연동 프로토콜 설계 및 구현)

  • Jang, Jong-Hyun;Lee, Dong-Gil;Choi, Wan;Han, Chi-Moon;Jang, Ik-Hyun
    • The KIPS Transactions:PartA
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    • v.10A no.3
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    • pp.231-238
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    • 2003
  • Distributed systems present new system architecture for solving interoperability problem in heterogeneous system. This paper presents CORBA Inter-ORB protocol model based on shared memory to support communication software through analysis of existing CORBA IIOP protocol performance and Inter-Process Communication techniques. In the same host environment, proposed model applied standard CORBA mechanism to minimize message transfer overhead can develop software independently to hardware architecture of target communication system. This communication software that has flexibility and extensibility can improve productivity, duality and reusability of software.

A Study on Efficient Executions of MPI Parallel Programs in Memory-Centric Computer Architecture

  • Lee, Je-Man;Lee, Seung-Chul;Shin, Dongha
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.1
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    • pp.1-11
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    • 2020
  • In this paper, we present a technique that executes MPI parallel programs, that are developed on processor-centric computer architecture, more efficiently on memory-centric computer architecture without program modification. The technique we present here improves performance by replacing low-speed data communication over the network of MPI library functions with high-speed data communication using the property called fast large shared memory of memory-centric computer architecture. The technique we present in the paper is implemented in two programs. The first program is a modified MPI library called MC-MPI-LIB that runs MPI parallel programs more efficiently on memory-centric computer architecture preserving the semantics of MPI library functions. The second program is a simulation program called MC-MPI-SIM that simulates the performance of memory-centric computer architecture on processor-centric computer architecture. We developed and tested the programs on distributed systems environment deployed on Docker based virtualization. We analyzed the performance of several MPI parallel programs and showed that we achieved better performance on memory-centric computer architecture. Especially we could see very high performance on the MPI parallel programs with high communication overhead.

The QCE:A Binding Environment for Distributed Memory Multiprocessors (분산메모리 멀티프로세서 시스템을 위한 바인딩 환경(QCE))

  • Lee, Yong-Du;Kim, Hui-Cheol;Chae, Su-Hwan
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.7
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    • pp.1719-1726
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    • 1996
  • In the OR-parallel execution of logic programs, binding environments have a critical impact on the performance. Particularly, this is true for distributed execution on parallel systems with a non-single address space. The reason is that in such systems, the remote accesses across processing elements deteriorate the performance. To solve this problem, some binding methods were previously proposed specifically for a non-single address space. However, compared with the binding methods for a single address space, they are far less efficient due to the overhead of newly introduced operations such as environment closing and back-unification, In this paper, we propose a new binding environment is a hybrid that combines both the binding methods for a single address space and those for anon-single address space. It acomplishes high efficiency by making closing operations unnecessary both at unification and at back-unification, while mainthing the restricted accesses.

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Application of Correlation-Aided DSA(CDSA) Technique to Fast Cell Search in IMT-2000 W-CDMA Systems.

  • Kim, Byoung-Hoon;Jeong, Byeong-Kook;Lee, Byeong-Gi
    • Journal of Communications and Networks
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    • v.2 no.1
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    • pp.58-68
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    • 2000
  • In this paper we introduce the correlation-aided distributed sample acquisition (CDSA) scheme for fast cell search in IMT-2000 W-CDMA cellular system. The proposed scheme incorporates the state symbol correlation process into the comparison-correction based synchronization process of the original DSA scheme to enable fast acquisition even under very poor channel environment. for its realization, each mobile station (MS) has to store in its memory a set of state sample sequences. which are determined by the long-period scrambling sequences used in the system and the sampling interval of the state samples. CDSA based cell search is carried out in two stages : First, the MS first acquires the slot timing by using the primary synch code (PSC) and then identifies the igniter code which conveys the state samples of the current cell . Secondly. the MS identifies the scrambling code and frame timing by taking the comparison-correction based synchronization approach and, if the identification is not done satisfactorily within preset time. it initiates the state symbol correlation process which correlates the received symbol sequence with the pre-stored state sample sequences for a successful identification. As the state symbol SNR is relatively high. the state symbol correlation process enables reliable synchronization even in very low chip-SNR environment. Simulation results show that the proposed CDSA scheme outperforms the 3GPP 3-step approach, requiring the signal power of about 7 dB less for achieving the same acquisition time performance in low-SNR environments. Furthermore, it turns out very robust in the typical synchronization environment where large frequency offset exists.

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Implementing I/O Bandwidth Sharing Scheme between Multiple Linux Containers based on Dm-zoned for Zoned Namespace SSDs

  • Seokjun Lee;Sungyong Ahn
    • International journal of advanced smart convergence
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    • v.12 no.4
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    • pp.237-245
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    • 2023
  • In the cloud service, system resource such as CPU, memory, I/O bandwidth are shared among multiple users. Particularly, in Linux containers environment, I/O bandwidth is distributed in proportion to the weight of each container through the BFQ I/O scheduler. However, since the I/O scheduler can only be applied to conventional block storage devices, it cannot be applied to Zoned Namespace(ZNS) SSD, a new storage interface that has been recently studied. To overcome this limitation, in this paper, we implemented a weighted proportional I/O bandwidth sharing scheme for ZNS SSDs in dm-zoned, which emulates conventional block storage using ZNS SSDs. Each user receives a different amount of budget, which is required to process the user's I/O requests based on the user's weight. If the budget is exhausted I/O requests cannot be processed and requests are queued until the budget replenished. Each budget refill period, the budget is replenished based on the user's weight. In the experiment, as a result, we can confirm that the I/O bandwidth can be distributed on their weight as we expected.

Implementation of Data processing of the High Availability for Software Architecture of the Cloud Computing (클라우드 서비스를 위한 고가용성 대용량 데이터 처리 아키텍쳐)

  • Lee, Byoung-Yup;Park, Junho;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.13 no.2
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    • pp.32-43
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    • 2013
  • These days, there are more and more IT research institutions which foresee cloud services as the predominant IT service in the near future and there, in fact, are actual cloud services provided by some IT leading vendors. Regardless of physical location of the service and environment of the system, cloud service can provide users with storage services, usage of data and software. On the other hand, cloud service has challenges as well. Even though cloud service has its edge in terms of the extent to which the IT resource can be freely utilized regardless of the confinement of hardware, the availability is another problem to be solved. Hence, this paper is dedicated to tackle the aforementioned issues; prerequisites of cloud computing for distributed file system, open source based Hadoop distributed file system, in-memory database technology and high availability database system. Also the author tries to body out the high availability mass distributed data management architecture in cloud service's perspective using currently used distributed file system in cloud computing market.

A New Network Bandwidth Reduction Method of Distributed Rendering System for Scalable Display (확장형 디스플레이를 위한 분산 렌더링 시스템의 네트워크 대역폭 감소 기법)

  • Park, Woo-Chan;Lee, Won-Jong;Kim, Hyung-Rae;Kim, Jung-Woo;Han, Tack-Don;Yang, Sung-Bong
    • Journal of KIISE:Computer Systems and Theory
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    • v.29 no.10
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    • pp.582-588
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    • 2002
  • Scalable displays generate large and high resolution images and provide an immersive environment. Recently, scalable displays are built on the networked clusters of PCs, each of which has a fast graphics accelerator, memory, CPU, and storage. However, the distributed rendering on clusters is a network bound work because of limited network bandwidth. In this paper, we present a new algorithm for reducing the network bandwidth and implement it with a conventional distributed rendering system. This paper describes the algorithm called geometry tracking that avoids the redundant geometry transmission by indexing geometry data. The experimental results show that our algorithm reduces the network bandwidth up to 42%.

Distributed Table Join for Scalable RDFS Reasoning on Cloud Computing Environment (클라우드 컴퓨팅 환경에서의 대용량 RDFS 추론을 위한 분산 테이블 조인 기법)

  • Lee, Wan-Gon;Kim, Je-Min;Park, Young-Tack
    • Journal of KIISE
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    • v.41 no.9
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    • pp.674-685
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    • 2014
  • The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.