• Title/Summary/Keyword: Inbound Network

Search Result 34, Processing Time 0.022 seconds

Design and Implementation of an InfiniBand System Interconnect for High-Performance Cluster Systems (고성능 클러스터 시스템을 위한 인피니밴드 시스템 연결망의 설계 및 구현)

  • Mo, Sang-Man;Park, Kyung;Kim, Sung-Nam;Kim, Myung-Jun;Im, Ki-Wook
    • The KIPS Transactions:PartA
    • /
    • v.10A no.4
    • /
    • pp.389-396
    • /
    • 2003
  • InfiniBand technology is being accepted as the future system interconnect to serve as the high-end enterprise fabric for cluster computing. This paper presents the design and implementation of the InfiniBand system interconnect, focusing on an InfiniBand host channel adapter (HCA) based on dual ARM9 processor cores The HCA is an SoC tailed KinCA which connects a host node onto the InfiniBand network both in hardware and in software. Since the ARM9 processor core does not provide necessary features for multiprocessor configuration, novel inter-processor communication and interrupt mechanisms between the two processors were designed and embedded within the KinCA chip. Kinch was fabricated as a 564-pin enhanced BGA (Bail Grid Array) device using 0.18${\mu}{\textrm}{m}$ CMOS technology Mounted on host nodes, it provides 10 Gbps outbound and inbound channels for transmit and receive, respectively, resulting in a high-performance cluster system.

Design of Quantum Key Distribution System without Fixed Role of Cryptographic Applications (암호장치의 송·수신자 역할 설정이 없는 양자키분배 시스템 설계)

  • Ko, Haeng-Seok;Ji, Se-Wan;Jang, Jingak
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.30 no.5
    • /
    • pp.771-780
    • /
    • 2020
  • QKD(Quantum Key Distribution) is one of the protocols that can make two distant parties safely share secure keys against the threat of quantum computer. Generally, cryptographic applications which are connected to the QKD device have fixed roles as a transmitter and a receiver due to the race condition and complexity of implementation. Because the conventional QKD system is mainly applied to the link encryptor, there are no problems even if the roles of the cryptographic devices are fixed. We propose a new scheme of QKD system and protocol that is easy to extend to the QKD network by eliminating quantum key dependency between cryptographic device and QKD node. The secure keys which are generated by the TRNG(True Random Number Generator) are provided to the cryptographic applications instead of quantum keys. We design an architecture to transmit safely the secure keys using the inbound and outbound quantum keys which are shared between two nodes. In this scheme, since the dependency of shared quantum keys between two QKD nodes is eliminated, all cryptographic applicatons can be a master or a slave depending on who initiates the cryptographic communications.

Building battery deterioration prediction model using real field data (머신러닝 기법을 이용한 납축전지 열화 예측 모델 개발)

  • Choi, Keunho;Kim, Gunwoo
    • Journal of Intelligence and Information Systems
    • /
    • v.24 no.2
    • /
    • pp.243-264
    • /
    • 2018
  • Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

Evaluating Global Container Ports' Performance Considering the Port Calls' Attractiveness (기항 매력도를 고려한 세계 컨테이너 항만의 성과 평가)

  • Park, Byungin
    • Journal of Korea Port Economic Association
    • /
    • v.38 no.3
    • /
    • pp.105-131
    • /
    • 2022
  • Even after the improvement in 2019, UNCTAD's Liner Shipping Connectivity Index (LSCI), which evaluates the performance of the global container port market, has limited use. In particular, since the liner shipping connectivity index evaluates the performance based only on the distance of the relationship, the performance index combining the port attractiveness of calling would be more efficient. This study used the modified Huff model, the hub-authority algorithm and the eigenvector centrality of social network analysis, and correlation analysis for 2007, 2017, and 2019 data of Ocean-Commerce, Japan. The findings are as follows: Firstly, the port attractiveness of calling and the overall performance of the port did not always match. However, according to the analysis of the attractiveness of a port calling, Busan remained within the top 10. Still, the attractiveness among other Korean ports improved slowly from the low level during the study period. Secondly, Global container ports are generally specialized for long-term specialized inbound and outbound ports by the route and grow while maintaining professionalism throughout the entire period. The Korean ports continue to change roles from analysis period to period. Lastly, the volume of cargo by period and the extended port connectivity index (EPCI) presented in this study showed a correlation from 0.77 to 0.85. Even though the Atlantic data is excluded from the analysis and the ship's operable capacity is used instead of the port throughput volume, it shows a high correlation. The study result would help evaluate and analyze global ports. According to the study, Korean ports need a long-term strategy to improve performance while maintaining professionalism. In order to maintain and develop the port's desirable role, it is necessary to utilize cooperation and partnerships with the complimentary port and attract shipping companies' services calling to the complementary port. Although this study carried out a complex analysis using a lot of data and methodologies for an extended period, it is necessary to conduct a study covering ports around the world, a long-term panel analysis, and a scientific parameter estimation study of the attractiveness analysis.