Vol. 46, No. 4,
Apr. 2019
Digital Library
Software-Defined Networking Enabling Expeditious Forwarding Rule Management for Cyber-Physical Defense Systems
Kilho Lee, Taejune Park, Minsu Kim, Seungwon Shin, Insik Shin
http://doi.org/10.5626/JOK.2019.46.4.291
Recently, there has been an increased interest in Cyber-Physical Systems (CPSs) for national defense. CPSs consist of sensors, actuators, and computing elements which are connected through a network to perform complex tasks while interacting with the physical world. Therefore, CPSs inherently require a high level of real-time guarantee (temporal correctness), and the CPS networking systems require highly dynamic network management capabilities to satisfy the real-time constraints. This requirement can be supported by using Software-defined networking (SDN) through flexible network management. However, applying SDN to CPS networking systems raises several challenges, since SDN lacks consideration for handling real-time traffic, such as a long delay to update packet handling rules. This paper presents a novel SDN switch architecture that reduces the time delay required to change the packet handling rules significantly; it enables flexible network management without compromising the real-time requirements of network flows which are essential for the system safety. We implemented and evaluated the proposed architecture on top of real hardware. The evaluation showed that the proposed architecture resulted in 500 times faster rule management than the standard SDN architecture. We also implemented a fault recovery system by applying the proposed architecture. The fault recovery application proved that the proposed architecture can significantly improve the system safety.
Parallel Algorithms for the Boxed-Mesh Permutation Pattern Matching Problem
Jihyo Choi, Youngho Kim, Joong Chae Na, Jeong Seop Sim
http://doi.org/10.5626/JOK.2019.46.4.299
Given a text T(|T|= n) and a pattern P(|P|= m), the boxed-mesh permutation pattern matching problem asks to find all boxed subsequences of T that are order-isomorphic to P. In this paper we present two parallel algorithms for the problem. We first propose an O(nm) -time parallel algorithm using O(n) threads and then propose an O(n)-time algorithm using O(nm) threads. The experimental results for Daw Jones Industrial Average show that our first and second algorithms run approximately 7.2 times and 20.6 times, respectively, faster compared to the sequential algorithm using order-statistics trees when n = 36,364 and m = 30.
A Survey of Movement Symptom and Quantification Method in Parkinson’s Disease
Daeun Gwon, Yoseop Kim, Sangjun Kim, Myeonghu Song, Minkyu Ahn
http://doi.org/10.5626/JOK.2019.46.4.308
Parkinson’s disease (PD) is a neurodegenerative disease that causes abnormal motor symptoms such as tremor, bradykinesia, stiffness, and postural instability. The number of patients with PD is increasing worldwide. Therefore, it is of great importance to delay the progression of PD through early diagnosis and treatment or to provide appropriate treatment and continuous assistance to PD patients through regular examination to determine changes in their symptoms and the rate of disease progression. In this paper, we investigated motor disease symptoms (tremor, stiffness and bradykinesia) caused by PD and methods that quantified it by engineering. In addition, 67 papers (24 in Korea and 43 abroad) directly related to quantification methods of Parkinsonian motor symptoms were investigated through domestic and international searches of published research papers. As a result of the search, it was confirmed that acceleration / angular velocity (46%) and electromyography (22.7%) were most widely used both in domestic and international research for quantification of movement disorders (tremor, stiffness, bradykinesia) and UPDRS (Unified Parkinson’s Disease Rating Scale) was the most widely used scale (78%, N = 55) to compare and confirm results of such methods.
Input Data Description using Stratified Context-Free Grammar
Taehwan Kim, Damho Lee, Hyunji Seo, Changwoo Pyo
http://doi.org/10.5626/JOK.2019.46.4.321
This paper defines Data Description Language (DDL) based on a context-free grammar that describes syntactic characteristics of input from multiple input files or devices. Each input file or device has its input description, which is connected to its upper-level input description to form a hierarchy. We also developed a method generating input data using DDL. To demonstrate DDL’s utility, we have compared our method with two others using the metrics of basic block coverage and input generation times. For 37 programs of Coreutils, our method generated valid input faster by O(103) times, and the coverage was higher by 25.44% than KLEE. Compared to the method of single context-free grammars, ours took 1.52 times, but basic block coverage was larger by 6.59%. Currently, we use DDL for generating regular input for dynamic control-flow analysis.
Flexible and Efficient Continuous Integration to Improve Development Processes in Various Execution Environments
http://doi.org/10.5626/JOK.2019.46.4.328
Continuous Integration is an automated software development process that periodically builds, tests, validates, and integrates code changes into a version control system. Continuous integration help increase programmer’s productivity. However, since the existing integration testing techniques based on unit tests only evaluate a program at code level, critical problems are often discovered during a later software development phase such as testing. Specifically, when executions environments are diverse and dynamically change, problems arise due to the differences between the test environment and the actual working environment. Also, when a plurality of CI tasks are simultaneously requested, the CI performance is degraded due to resource contention between CI tasks. This study is about CI services for software development in various execution environment and introduce scheduling method for when many CI tasks are requested.
Coreference Resolution using Multi-resolution Pointer Networks
Cheoneum Park, Changki Lee, Hyunki Kim
http://doi.org/10.5626/JOK.2019.46.4.334
Multi-resolution RNN is a method of modeling parallel sequences as RNNs. Coreference resolution is a natural language processing task in which several words representing different entities present in a document are defined as one cluster and can be solved by a pointer network. The encoder input sequence of the coreference resolution becomes all the morphemes of the document using the pointer network, and the decoder input sequence becomes all the nouns present in the document. In this paper, we propose three multi-resolution pointer network models that encode all morphemes and noun lists of a document in parallel and perform decoding by using both encoded hidden states in a decoder. We have solved the coreference resolution based on the proposed models. Experimental results show that Multi-resolution1 of the proposed model has 71.44% CoNLL F1, 70.52% CoNLL F1 of Multi-resolution2 and 70.59% CoNLL F1 of Multi-resolution3.
Categories and Patterns of Java Program Unit Test Code Bugs
http://doi.org/10.5626/JOK.2019.46.4.341
Since unit testing is widely used in many software projects, the threat of unit test bugs(i.e., bugs in the test case code) is becoming a more important issue of software quality assurance. Test code bugs are critical threats because they may invalidate the quality assurance process, which consequently hurts quality of products and performance of the project. This paper presents a set of test bug categories and a set of bug patterns extracted from real-world cases. Unlike the existing work on test code bugs, this paper suggests a classification method to systematically categorize different features of test code bugs (i.e., structures, operations, and requirements). In addition, this paper defines eight new bug patterns in unit test code, based on previous bug reports from well-known open-source projects. Each pattern is formally specified as source code patterns so that it can be used for to construct a static bug pattern checker.
Incremental Clustering and Multi-Document Summarization for Issue Analysis based on Real-time News
Hongyeon Yu, Seungwoo Lee, Youngjoong Ko
http://doi.org/10.5626/JOK.2019.46.4.355
In order to analyze an issue based on real-time news articles, automatic clustering and technique for summarization of multiple news articles are mandatory. Although traditional clustering and summarization technique have been widely used in many natural language processing tasks with considerable success, the focus was on static corpora, instead of real-time data. Consequently, in the present work, we propose an incremental and hierarchical news clustering and multi-document summarization method for analysis of a large set of news articles in real time. We have employed both qualitative and quantitative evaluation methods. For qualitative evaluation, we used real-time data of about two months between October 2016 and November 2016, and the professionally trained researchers conducted a qualitative evaluation based on Precision at k. For quantitative evaluation, manually constructed news evaluation data was used, and document allocation accuracy was used for clustering performance. Furthermore, the ROUGE evaluation method was used for summarization performance. Accordingly, in the qualitative evaluation, the cluster performance was 66% on an average and the summarization performance was 92% on an average. In the quantitative evaluation, the cluster performance was 53.95% on an average. The summary performance was ROUGE-1: 0.2269, ROUGE-2: 0.1018, and ROUGE-L: 0.1689.
Data-driven Path Selection for Improving Industrial-Strength Static Analyzers
http://doi.org/10.5626/JOK.2019.46.4.363
We propose a data-driven method to improve path-sensitive industrial-strength static analyzers. Most industrial static analyzers adopt path-sensitive techniques and path selection holds the key to their performance. We propose a method to automatically learn new cost-effective path-selection heuristics from an existing analyzer with a manually tuned path-selection heuristic. We evaluated our method on an industrial static C code bug-finder from Sparrow as a baseline analyzer with 17 C open-source benchmark programs. The experimental results showed that with the newly-learned path-selection heuristic, the analyzer reported 90.8% of the defects in only 38% of the analysis time, compared to the baseline analysis. This method reported more defects in less time than the baseline path-selection heuristic under similar path search space constraints.
Image Caption Generation using Object Attention Mechanism
http://doi.org/10.5626/JOK.2019.46.4.369
Explosive increases in image data have led studies investigating the role of image caption generation in image expression of natural language. The current technologies for generating Korean image captions contain errors associated with object concurrence attributed to dataset translation from English datasets. In this paper, we propose a model of image caption generation employing attention as a new loss function using the extracted nouns of image references. The proposed method displayed BLEU1 0.686, BLEU2 0.557, BLEU3 0.456, BLEU4 0.372, which proves that the proposed model facilitates the resolution of high-frequency word-pair errors. We also showed that it enhances the performance compared with previous studies and reduces redundancies in the sentences. As a result, the proposed method can be used to generate a caption corpus effectively.
Data Privacy-Price Negotiation for applying Differential Privacy in Data Market Environments
http://doi.org/10.5626/JOK.2019.46.4.376
Digital data is currently an indispensable resource for making effective decisions. As the value of digital data is increasing, digital markets, where data providers and consumers can deal with data, are also attracting attention as a mean of obtaining that data. However, obtaining the digital data can lead to privacy breaches, which affects individuals’ willingness to provide data. In this study, a fair negotiation method that can set the appropriate price and noise parameter εconsidering the data provider and the consumer in the differentially private data market environment was proposed. A data market framework with a market manager that links the data provider and the consumer is suggested. In addition, a technique of determining the price and noise parameter ε of the data in two phases using matching theory and Rubinstein bargaining is proposed. It is established that the proposed negotiation technique provides an appropriate level of ε and unit price, which satisfy the data provider and the consumer. The proposed technique prevents unfair transactions and can determine the appropriate level of ε and unit price.
MQTT-based Gateway System for Auto-configuration of IoT Devices and Services
Geonwoo Kim, Jiwoo Park, Kwangsue Chung
http://doi.org/10.5626/JOK.2019.46.4.385
MQTT (Message Queuing Telemetry Transport) is a messaging protocol for the IoT(Internet of Things) selected by the OASIS (Organization for the Advancement of Structured Information Standards), which enables efficient data transmission to occur over low-power, unreliable networks. However, there is a problem that the service discovery is impossible, because the MQTT does not use multicast features, and there is no resource directory for managing resource information in the local network. In this paper, we propose an auto-configuration system that enables service discovery and device operation using a MQTT Publish/Subscribe message transmission method through a gateway acting as a resource directory. Through the implementation results, we confirmed that devices and services existing in the local network can be discovered and operated by using the proposed auto-configuration system.
Analyzing the Impact of Convolution Coding Effect on the Performance Improvement for the Link-16 Enhanced Throughput
http://doi.org/10.5626/JOK.2019.46.4.391
Modern warfare requires the implementation of a combined/jointed operational environment, in which the multinational and three-dimensional powers are simultaneously deployed. The United States, NATO and its allies, including Korea, are using Link-16, which is noted as a tactical data link that enables combined/jointed operations. Currently, Link-16 is undergoing a performance improvement for utilizing crypto modernization, enhanced throughput and frequency re-mapping. In this paper, we will analyze the operability and efficiency of the Link-16 performance improvement factors, and analyze performance improvement status for double throughput improvement. We also analyze the effect of the newly applied convolutional coding to improve Link-16 throughput. Analysis of the impact of convolutional coding to improve Link-16 throughput has shown that it can gain twice as much efficiency of use in regard to the current Link-16 throughput.
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