Vol. 44, No. 9,
Sep. 2017
Digital Library
Snapshot-Based Offloading for Web Applications with HTML5 Canvas
InChang Jeong, Hyuk-Jin Jeong, Soo-Mook Moon
http://doi.org/10.5626/JOK.2017.44.9.871
A vast amount of research has been carried out for executing compute-intensive applications on resource-constrained mobile devices. Computation offloading is a method in which heavy computations are dynamically migrated from a mobile device to a server, exploiting the powerful hardware of the server to perform complex computations. An important issue for offloading is the complexity of reconciling the execution state of applications between the server and the client. To address this issue, snapshot-based offloading has recently been proposed, which utilizes the snapshot of a web app as the portable description of the execution state. However, for web applications using the HTML5 canvas, snapshot-based offloading does not function correctly, because the snapshot cannot capture the state of the canvas. In this paper, we propose a code generation technique to save the canvas state as part of a snapshot, so that the snapshot-based offloading can be applied to web applications using the canvas.
Enhancing the Performance of Multiple Parallel Applications using Heterogeneous Memory on the Intel"s Next-Generation Many-core Processor
Seungwoo Rho, Seoyoung Kim, Dukyun Nam, Geunchul Park, Jik-Soo Kim
http://doi.org/10.5626/JOK.2017.44.9.878
This paper discusses performance bottlenecks that may occur when executing high-performance computing MPI applications in the Intel’s next generation many-core processor called Knights Landing(KNL), as well as effective resource allocation techniques to solve this problem. KNL is composed of a host processor to enable self-booting in addition to an existing accelerator consisting of a many-core processor, and it was released with a new type of on-package memory with improved bandwidth on top of existing DDR4 based memory. We empirically verified an improvement of the execution performance of multiple MPI applications and the overall system utilization ratio by studying a resource allocation method optimized for such new many-core processor architectures.
A Dual Filter-based Channel Selection for Classification of Motor Imagery EEG
David Lee, Hee Jae Lee, Snag-Hoon Park, Sang-Goog Lee
http://doi.org/10.5626/JOK.2017.44.9.887
Brain-computer interface (BCI) is a technology that controls computer and transmits intention by measuring and analyzing electroencephalogram (EEG) signals generated in multi-channel during mental work. At this time, optimal EEG channel selection is necessary not only for convenience and speed of BCI but also for improvement in accuracy. The optimal channel is obtained by removing duplicate(redundant) channels or noisy channels. This paper propose a dual filter-based channel selection method to select the optimal EEG channel. The proposed method first removes duplicate channels using Spearman"s rank correlation to eliminate redundancy between channels. Then, using F score, the relevance between channels and class labels is obtained, and only the top m channels are then selected. The proposed method can provide good classification accuracy by using features obtained from channels that are associated with class labels and have no duplicates. The proposed channel selection method greatly reduces the number of channels required while improving the average classification accuracy.
A Method to Specify and Verify Requirements for Safety Critical System
http://doi.org/10.5626/JOK.2017.44.9.893
In safety-critical systems, software defects may have serious consequences. Therefore, defects should be considered during the requirements specification process, which is the first step of a software development lifecycle. Stakeholder requirements that are usually written in natural language are difficult to derived, and there may also be defects due to ambiguity and inaccuracy. To address these issues, we propose a requirement specification method using a standardized Boilerplate and a GSN Model. The Boilerplate is a semi-standard language that follows a predefined format. Due to its ability to provide a consistent representation of the requirements, boilerplate helps stakeholders avoid ambiguities about what they mean and to define the exact meaning of the requirement. Meanwhile, GSN is recognized notation to prepare a Safety Case to prove to authorities that a system is safe. It can be expressed as a functional goal, e.g., Safety Evidence, etc. The proposed study allows an analyst to easily identify a fault from the early stage of the software development lifecycle. The Boilerplate and GSN Model are designed to specify the requirements of safety critical systems and to prove safety conformity through a connection with Safety Evidence. In addition, the proposed approach is also useful to develop secure software by correcting deficiencies in the requirements found during this process.
Similarity-based Service Recommendation for Service-Mashup Developers
http://doi.org/10.5626/JOK.2017.44.9.908
As web service technologies are widely used, there have been many efforts to develop approaches for recommending appropriate web services to users in complex and dynamic service environments. In addition, for the effective development of service mashups, service recommender systems that are specialized for service composition have been developed. However, existing service recommender systems for service mashups are not effective at recommending services in a personalized manner that reflect developers’ preferences. To deal with this issue, we propose an approach that recommends services based on the similarities between mashup developers who have developed similar service mashups. The proposed approach is then evaluated by using the mashup data retrieved from ProgrammableWeb. The evaluation results clearly show that the proposed approach is an effective way of improving service recommendations compared to the traditional user-based collaborative filtering algorithm.
A Method to Elicit Privacy Requirements and Build Privacy Assurance Cases for Privacy Friendly System
http://doi.org/10.5626/JOK.2017.44.9.918
Recently, the spread of smartphones and various wearable devices has led to increases in the accumulation and usage of personal information. As a result, privacy protection has become an issue. Even though there have been studies and efforts to improve legal and technological security measures for protecting privacy, personal information leakage accidents still occur. Rather than privacy requirements, analysts mostly focus on the implementation of security technology within software development. Previous studies of security requirements strongly focused on supplementing the basic principles and laws for privacy protection and securing privacy requirements without understanding the relationship between privacy and security. As a result, personal information infringement occurs continuously despite the development of security technologies and the revision of the Personal Information Protection Act. Therefore, we need a method for eliciting privacy requirements based on related privacy protection laws that are applicable to software development. We also should clearly specify the relationship between privacy and security. This study aims to elicit privacy requirements and create privacy assurances cases for Privacy Friendly System development.
LASPI: Hardware friendly LArge-scale stereo matching using Support Point Interpolation
Sanghyun Park, Deepak Ghimire, Jung-guk Kim, Youngki Han
http://doi.org/10.5626/JOK.2017.44.9.932
In this paper, a new hardware and software architecture for a stereo vision processing system including rectification, disparity estimation, and visualization was developed. The developed method, named LArge scale stereo matching method using Support Point Interpolation (LASPI), shows excellence in real-time processing for obtaining dense disparity maps from high quality image regions that contain high density support points. In the real-time processing of high definition (HD) images, LASPI does not degrade the quality level of disparity maps compared to existing stereo-matching methods such as Efficient LArge-scale Stereo matching (ELAS). LASPI has been designed to meet a high frame-rate, accurate distance resolution performance, and a low resource usage even in a limited resource environment. These characteristics enable LASPI to be deployed to safety-critical applications such as an obstacle recognition system and distance detection system for autonomous vehicles. A Field Programmable Gate Array (FPGA) for the LASPI algorithm has been implemented in order to support parallel processing and 4-stage pipelining. From various experiments, it was verified that the developed FPGA system (Xilinx Virtex-7 FPGA, 148.5MHz Clock) is capable of processing 30 HD (1280×720 pixels) frames per second in real-time while it generates disparity maps that are applicable to real vehicles.
Assignment Semantic Category of a Word using Word Embedding and Synonyms
http://doi.org/10.5626/JOK.2017.44.9.946
Semantic Role Decision defines the semantic relationship between the predicate and the arguments in natural language processing (NLP) tasks. The semantic role information and semantic category information should be used to make Semantic Role Decisions. The Sejong Electronic Dictionary contains frame information that is used to determine the semantic roles. In this paper, we propose a method to extend the Sejong electronic dictionary using word embedding and synonyms. The same experiment is performed using existing word-embedding and retrofitting vectors. The system performance of the semantic category assignment is 32.19%, and the system performance of the extended semantic category assignment is 51.14% for words that do not appear in the Sejong electronic dictionary of the word using the word embedding. The system performance of the semantic category assignment is 33.33%, and the system performance of the extended semantic category assignment is 53.88% for words that do not appear in the Sejong electronic dictionary of the vector using retrofitting. We also prove it is helpful to extend the semantic category word of the Sejong electronic dictionary by assigning the semantic categories to new words that do not have assigned semantic categories.
Power Consumption Forecasting Scheme for Educational Institutions Based on Analysis of Similar Time Series Data
Jihoon Moon, Jinwoong Park, Sanghoon Han, Eenjun Hwang
http://doi.org/10.5626/JOK.2017.44.9.954
A stable power supply is very important for the maintenance and operation of the power infrastructure. Accurate power consumption prediction is therefore needed. In particular, a university campus is an institution with one of the highest power consumptions and tends to have a wide variation of electrical load depending on time and environment. For this reason, a model that can accurately predict power consumption is required for the effective operation of the power system. The disadvantage of the existing time series prediction technique is that the prediction performance is greatly degraded because the width of the prediction interval increases as the difference between the learning time and the prediction time increases. In this paper, we first classify power data with similar time series patterns considering the date, day of the week, holiday, and semester. Next, each ARIMA model is constructed based on the classified data set and a daily power consumption forecasting method of the university campus is proposed through the time series cross-validation of the predicted time. In order to evaluate the accuracy of the prediction, we confirmed the validity of the proposed method by applying performance indicators.
Cluster Property based Data Transfer for Efficient Energy Consumption in IoT
Chungsan Lee, Soobin Jeon, Inbum Jung
http://doi.org/10.5626/JOK.2017.44.9.966
In Internet of Things (IoT), the aim of the nodes (called ‘Things’) is to exchange information with each other, whereby they gather and share information with each other through self decision-making. Therefore, we cannot apply existing aggregation algorithms of Wireless sensor networks that aim to transmit information to only a sink node or a central server, directly to the IoT environment. In addition, since existing algorithms aggregate information from all sensor nodes, problems can arise including an increasing number of transmissions and increasing transmission delay and energy consumption. In this paper, we propose the clustering and property based data exchange method for energy efficient information sharing. First, the proposed method assigns the properties of each node, including the sensing data and unique resource. The property determines whether the node can respond to the query requested from the other node. Second, a cluster network is constructed considering the location and energy consumption. Finally, the nodes communicate with each other efficiently using the properties. For the performance evaluation, TOSSIM was used to measure the network lifetime and average energy consumption.
LTRE: Lightweight Traffic Redundancy Elimination in Software-Defined Wireless Mesh Networks
Gwangwoo Park, Wontae Kim, Joonwoo Kim, Sangheon Pack
http://doi.org/10.5626/JOK.2017.44.9.976
Wireless mesh network (WMN) is a promising technology for building a cost-effective and easily-deployed wireless networking infrastructure. To efficiently utilize limited radio resources in WMNs, packet transmissions (particularly, redundant packet transmissions) should be carefully managed. We therefore propose a lightweight traffic redundancy elimination (LTRE) scheme to reduce redundant packet transmissions in software-defined wireless mesh networks (SD-WMNs). In LTRE, the controller determines the optimal path of each packet to maximize the amount of traffic reduction. In addition, LTRE employs three novel techniques: 1) machine learning (ML)-based information request, 2) ID-based source routing, and 3) popularity-aware cache update. Simulation results show that LTRE can significantly reduce the traffic overhead by 18.34% to 48.89%.
Synthesizing Imperative Programs from Examples
Sunbeom So, Tae-Hyoung Choi, Jun Jung, Hakjoo Oh
http://doi.org/10.5626/JOK.2017.44.9.986
In this paper, we present a method for synthesizing imperative programs from input-output examples. Given (1) a set of input-output examples, (2) an incomplete program, and (3) variables and integer constants to be used, the synthesizer outputs a complete program that satisfies all of the given examples. The basic synthesis algorithm enumerates all possible candidate programs until the solution program is found (enumerative search). However, it is too slow for practical use due to the huge search space. To accelerate the search speed, our approach uses code optimization and avoids unnecessary search for the programs that are syntactically different but semantically equivalent. We have evaluated our synthesis algorithm on 20 introductory programming problems, and the results show that our method improves the speed of the basic algorithm by 10x on average.
Image Quality Assessment Considering both Computing Speed and Robustness to Distortions
Suk-Won Kim, Seongwoo Hong, Jeong-Chan Jin, Young-Jin Kim
http://doi.org/10.5626/JOK.2017.44.9.992
To assess image quality accurately, an image quality assessment (IQA) metric is required to reflect the human visual system (HVS) properly. In other words, the structure, color, and contrast ratio of the image should be evaluated in consideration of various factors. In addition, as mobile embedded devices such as smartphone become popular, a fast computing speed is important. In this paper, the proposed IQA metric combines color similarity, gradient similarity, and phase similarity synergistically to satisfy the HVS and is designed by using optimized pooling and quantization for fast computation. The proposed IQA metric is compared against existing 13 methods using 4 kinds of evaluation methods. The experimental results show that the proposed IQA metric ranks the first on 3 evaluation methods and the first on the remaining method, next to VSI which is the most remarkable IQA metric. Its computing speed is on average about 20% faster than VSI’s. In addition, we find that the proposed IQA metric has a bigger amount of correlation with the HVS than existing IQA metrics.
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