• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.21-26
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• 2002

Video stream invoke a variety of traffic with the structure of compression algorithm and image complexity. Thus, it is difficult to allocate the resource on the both sides of sender and receiver, and playout on the Internet such as a packet switched network. Thus, in this paper we proposed video stream smoothing using multistream for the effective transmission of video stream. This method specifies the type of LDU(logical data unit) according to the type of original stream, and then makes a large number of streams as a fixed size, and transfers them. So, the proposed method can reduce the buffering time which occurs during the process of the smoothing and prefetch be robust to the jitter on network, as well. Consequently, it has the effective transmission characteristics of fully utilizing the clients bandwidth.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.101-104
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• 2001

Over the last few years, streaming audio and video content on Internet sites has increased at unprecedented rates. The predominant method of delivering video over the current Internet is video streaming such as SureStream or Intelligent Stream. Since each method provides the client with only one data stream from one server, it often suffers from poor qualify of pictures in the case of network link congestion. In this paper, we propose a novel method of delivering video stream based on wavelet to a client by utilizing multi-threaded parallel connections from the client to multiple servers and to provides a better way to address the scalability functionalities. The experimental results show that the video quality delivered by the proposed multithreaded stream could significantly be improved over the conventional single video stream methods.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1785-1794
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• 2000

This paper presents a computational object model supporting CM(Continuous Media) stream interfaces including QoS(Quality of Service) required in the distributed application method for the proposed stream interface including QoS. A stream interface consists of a data channel and a control channel. In this paper, the CORBA supporting communication channel is used as the control channel and various transport protocols can be used as the dta channel of the stream interface. Also, specifications of the application QoS are included in stream interface specification. In implementation, FIFO queues and timers are used to support transmission rate, delay and jitter control mechanisms of he stream interface.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.445-452
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• 2020

Tributary is a part of life space for people and a very important place that accommodates rest recreation and other daily activities. absolutely insufficient basic data about water quality and flow rate are available for basin management. Efficient water and basin management systems, which are also supported by local residents can be established by securing such basic data of major tributaries in the Nakdong river system. In this study, the fluctuation characteristics of upstream and downstream water pollution levels were compared using the measurement results of the water environment measurement network and the tributary monitoring project for the gyeseong-stream and Hwapo-stream in the Nakdong-miryang watershed. In 2017, when water pollution is the highest, it was confirmed that the annual average rainfall was the lowest. Although the upstream and downstream water quality tendencies of the Gyeseong-stream are similar, the water quality concentrations of the Gyeseong-stream are relatively different. But although the Hwapo stream has various causes of pollution, there was not much difference in the level of pollution between the upper and lower streams. In addition, both rivers need the ability to purify rivers by securing sufficient water for river maintenance, and if the correlation between water quality items can be inferred through continuous monitoring of tributaries where the aspect of water quality change is unclear, water quality management Determined to be efficient operation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1519-1527
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• 2007

In order to combat the security threats that sensor networks are exposed to, a cryptography protocol is implemented at sensor nodes for point-to-point encryption between nodes. Given that nodes have limited resources, symmetric cryptography that is proven to be efficient for low power devices is implemented. Data protection is integrated into a sensor's packet by the means of symmetric encryption with the Dragon stream cipher and incorporating the newly designed Dragon-MAC Message Authentication Code. The proposed algorithm was designed to employ some of the data already computed by the underlying Dragon stream cipher for the purpose of minimizing the computational cost of the operations required by the MAC algorithm. In view that Dragon is a word based stream cipher with a fast key stream generation, it is very suitable for a constrained environment. Our protocol regarded the entity authentication and message authentication through the implementation of authenticated encryption scheme in wireless sensor nodes.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1384-1397
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• 2007

This paper proposes fast storage techniques for hybrid query of data streams. DSMS(Data Stream Management System) have been researched for processing data streams that have busting income. To process hybrid query that retrieve both current incoming data streams and past data streams data streams have to be stored into disk. But due to fast input speed of data stream and memory and disk space limitation, the main research is not about querying to stored data streams but about querying to current incoming data streams. Proposed techniques of this paper use circular buffer for maximizing memory utility and for make non blocking insertion possible. Data in a disk is compressed to maximize the number of data in the disk. Through experiences, proposed technique show that bursting insertion is stored fast.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.27-33
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• 2009

The emergences of GeoSensor and researches about GIS have promoted many researches of u-GIS. The disaster application coupled in the u-GIS can apply to monitor accident area and to prevent spread of accident. The application needs the u-GIS DSMS technique to acquire, to process GeoSensor data and to integrate them with GIS data. The u-GIS DSMS must process big and large-volume data stream such as spatial data and multimedia data. Due to the feature of the data stream, in u-GIS DSMS, query processing can be delayed. Moreover, as increasing the input rate of data in the area generating events, the network traffic is increased. To solve this problem, in this paper we describe TRIGGER ACTION clause in CQ on the u-GIS DSMS environment and proposes data source management. Data source weight table controls GES information and incoming data rate. It controls incoming data rate as increasing weight at GES of disaster area. Consequently, it can contribute query processing rate and accuracy

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.3
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• pp.383-393
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• 2013

Data stream mining is a technique to obtain the useful information by analyzing the data generated in real time. In data stream mining technology, frequent itemset mining is a method to find the frequent itemset while data is transmitting, and these itemsets are used for the purpose of pattern analyze and marketing in various fields. Existing techniques of finding frequent itemset mining are having problems when a malicious attacker sniffing the data, it reveals data provider's real-time information. These problems can be solved by using a method of inserting dummy data. By using this method, a attacker cannot distinguish the original data from the transmitting data. In this paper, we propose a method for privacy preserving frequent itemset mining by using the technique of inserting dummy data. In addition, the proposed method is effective in terms of calculation because it does not require encryption technology or other mathematical operations.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.48-54
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• 2008

This paper analyzes cost tradeoffs between memory usage and computation for window-based operators in data stream environments. It identifies generic operator network constructs, and sets up a cost model for the estimation of the expected memory reduction and the computation overheads when window memory relocations are applied to each operator network construct. This cost model helps to identify the utility of window memory relocations. It also helps to apply window memory relocation to improve a query execution plan to save memory usage. The proposed approach contributes to expand the scope of query processing and optimization in data stream environments. It also provides a basis to develop a cost estimation model for the query optimization using window memory relocations.