• Journal of information and communication convergence engineering
• /
• v.8 no.4
• /
• pp.427-432
• /
• 2010

The fast-emerging of cloud computing technology today has sufficiently benefited its wide range of users from individuals to large organizations. It carries an attractive characteristic by renting myriad virtual storages, computing resources and platform for users to manipulate their data or utilize the processing resources conveniently over Internet without the need to know the exact underlying infrastructure which is resided remotely at cloud servers. However due to the loss of direct control over the systems/applications, users are concerned about the risks of cloud services if it is truly secured. In the literature, there are cases where attackers masquerade as cloud users, illegally access to their accounts, by stealing the static login password or breaking the poor authentication gate. In this paper, we propose a two-factor authentication framework to enforce cloud services' authentication process, which are Public Key Infrastructure (PKI) authentication and mobile out-of-band (OOB) authentication. We discuss the framework's security analysis in later session and conclude that it is robust to phishing and replay attacks, prohibiting fraud users from accessing to the cloud services.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.1-4
• /
• 2019

Edge Computing 환경에서는 데이터 처리와 시스템 제어를 위한 별도의 서버가 존재하지 않는다. 서버를 통한 중앙통제 방식이 아닌 Edge computing에 사용된 IoT기기들이 연동되어 데이터 분산 처리와 연산을 통해 전체 시스템이 동작된다. 이러한 Edge computing 시스템 구조 특성상 전체 시스템이 과부하를 피하기 위해 각 IoT 기기에서 동시다발적으로 감지되는 실시간 상황 정보를 효율적으로 처리 하여야한다. 이에 따라 실시간 상황 정보를 효율적으로 처리하거나, 다양한 데이터 분석처리 알고리즘들이 연구 개발되어 데이터 처리에 적용되어 왔다. 하지만 데이터의 정보 흐름과 타입에 초점을 맞춘 것이 아니라 예상분석 및 획일화된 알고리즘을 통해서 분석되기 때문에 해당 플랫폼이 주로 지향하는 데이터 형식에 맞지 않으면 성능저하를 수반하며 사용에 제약이 많은 문제점이 있다. 따라서 본 논문에서는 IoT 환경에서 실시간 반응성 향상을 목표로 오픈소스 기반 스트림 데이터 처리 방법에 대한 비교 분석과 Fast-reaction을 위한 데이터 처리 도구 비교 분석을 연구를 진행한다.

• Journal of the Korean Society of Industry Convergence
• /
• v.27 no.1
• /
• pp.87-95
• /
• 2024

This study is on modulo scheduling algorithms for multicore processor in machine learning applications. Machine learning algorithms are designed to perform a large amount of operations such as vectors and matrices in order to quickly process large amounts of data stream. To support such large amounts of computations, processor architectures to support applications such as artificial intelligence, neural networks, and machine learning are designed in the form of parallel processing such as multicore. To effectively utilize these multi-core hardware resources, various compiler techniques are being used and studied. In this study, among these compiler techniques, we analyzed the modular scheduler, which is especially important in one core's computation pipeline. This paper looked at and compared the iterative modular scheduler and the swing modular scheduler, which are the most widely used and studied. As a result, both schedulers provided similar performance results, and when measuring register pressure as an indicator, it was confirmed that the swing modulo scheduler provided slightly better performance. In this study, a technique that divides recurrence edge is proposed to improve the minimum initiation interval of the modulo schedulers.

• Journal of Korea Spatial Information System Society
• /
• v.9 no.2
• /
• pp.25-34
• /
• 2007

Existing approaches that select an order for the join of three or more data streams have always used the simple heuristics. For their disadvantage - only one factor is considered and that is join selectivity or arrival rate, these methods lead to poor performance and inefficiency In some applications. The graph-based sliding window multi -join algorithm with optimal join sequence is proposed in this paper. In this method, sliding window join graph is set up primarily, in which a vertex represents a join operator and an edge indicates the join relationship among sliding windows, also the vertex weight and the edge weight represent the cost of join and the reciprocity of join operators respectively. Then the optimal join order can be found in the graph by using improved MVP algorithm. The final result can be produced by executing the join plan with the nested loop join procedure, The advantages of our algorithm are proved by the performance comparison with existing join algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.43 no.3 s.345
• /
• pp.111-117
• /
• 2006

Developing a home network and a ubiquitous infrastructure requires various communication techniques and devices with more advanced hardware. With this development, increasing realtime access to multimedia data results in rapid degradation of qualify for multimedia playback. This paper presents a traffic allocation technique based on MPP(Media Preference for Presentation) that can steadily maintain multimedia playback quality by adaptively allocating streaming traffic requested from clients with different playback performances. Media preference is defined in accordance with content popularity and playback performance of client devices. Through experiments when requested stream data exceeds processing ability of a midea server, the proposed allocation technique shows 10% quality improvement comparing to the system without applying the proposed allocation technique.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.4
• /
• pp.141-150
• /
• 2008

In this mobile computing environment, data broadcasting is widely used to resolve the problem of limited power and bandwidth of mobile equipments. Most previous broadcast indexing methods concentrate on flat data. However. with the growing popularity of XML, an increasing amount of information is being stored and exchanged in the XML format. We propose a novel indexing method. called TOP tree(Tree Ordering based Path summary tree), for indexing XML document on mobile broadcast environments. TOP tree is a path summary tree which provides a concise structure summary at group level using global IDs and element information at local level using local IDs. Based on the TOP tree representation, we suggest a broadcast stream generation and query Processing method that efficiently handles not only simple Path queries but also multiple path queries. We have compared our indexing method with other indexing methods. Evaluation results show that our approaches can effectively improve the access time and tune-in time in a wireless broadcasting environment.

• KIISE Transactions on Computing Practices
• /
• v.21 no.5
• /
• pp.351-358
• /
• 2015

As smart phones with built-in sensors are developed, research on recognition using wearable devices is increasing. Existing papers are mostly limited on research to personal activity recognition. In this paper, we propose a method to recognize conceptual group activity. Before doing recognition, we generate new data based on the analysis of the conceptual group activity in a classroom. The study focuses on three activities in the classroom environment: Taking Lesson, Doing Presentation and Discussing. With the proposed algorithm, the recognition rate is over 96%. Using this method in real time will make it easy to automatically analyze the activity and the purpose of the classrooms. Moreover, it can increase the utilization of the classroom through the data analysis. Further research will focus on group activity recognition in other environments and the design of an group activity recognition system.

• Journal of Internet Computing and Services
• /
• v.15 no.3
• /
• pp.45-52
• /
• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• The Transactions of the Korea Information Processing Society
• /
• v.5 no.6
• /
• pp.1441-1456
• /
• 1998

The concept of a hyperpresmtation, as an extension of a hypermedia, is the presentation in which time-varying multimedia presentations are dynamically linked together and a hyperlink's context can be changed over time at any time during a continuous presentation. Problems caused by integrating the hyperpresentation into an existing multimedia system which handles a sequential presentation only are, how to describe the hyperprcsentation, how to set up a hyperlink on a continuous media, and how to check the consistency of the synchronized presentations. In this paper. a new synchronization description method for the hyperpresentation and a method for setting a hyper link on a continuous media during" presentation are proposed after havin!; SHrvey of existing methods, The proposed method deals with only the DC value in a stream ut a DCT based compressed data for checking a condition of te link. Finally, the method for checking the consistency of mixed presentations before actual play of the hnlerpresentation is described. Proposed methods are implemented on MuX(Multimedia IO Server) where a sample scenario is tested.

• The Transactions of the Korea Information Processing Society
• /
• v.3 no.5
• /
• pp.1070-1081
• /
• 1996

In this research, a model was developed for estimating the queue length of vehicles, based on occupancy time of each vehicle collected by loop detectors which were setup at the upstream of urban street. The estimation model suggestes a method which minimizes architectural effects of the street, such as existence of pedestrian crossing, for future applications to the field. The estimation model suggested in this research was established based on real traffic data collected at up-stream detectors in Kangnam Subway station, Seoul, and the formula of the model is based on Multi-Polynomial equations. Consequence of the experiments showed that the model can adequately and in real-time mode measure length of the queue which were constructed at the 80 to 90 meters away from the upstream detectors. The estimation accuracy of the model was verified in statistical analysis conducted by regressing analysis and test results in real traffic situation.