• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.406-412
• /
• 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 Korea Multimedia Society
• /
• v.7 no.1
• /
• pp.54-63
• /
• 2004

This paper describes a hybrid QoS guarantee scheme for high quality audio streaming services on the Internet. The continuous playback of the audio data requires the isochronous transmission of the audio data packet through the Internet. In order to retain the QoS at the ultimate destination (client) as the same as servers provide, the transmission protocols should consider the error conditions such as packet loss, and out of order delivery. Generally, the protocols supporting the transmission of continuous media data do not try to recover the errors. The protocols are working somehow for the toll quality multimedia streaming services, but rot for the high quality streaming services, such as the DVD sound/music payback. The hybrid QoS guarantee scheme includes the three mechanisms to overcome the problem. The selective retransmission for the lost packet, the adaptive buffering at client-side, and the adaptive transmission rate at server-side are totally adopted to recover the packet loss with the minimal overhead, to prevent from the buffer starvation during the retransmission, and to maintain the isochronous transmission even after the retransmission. The experiments have shown good results for the high Quality audio streaming services on the Internet.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.4
• /
• pp.485-492
• /
• 2009

In the mobile service environment, patterns generated by temporal synchronization are streamed with different instance values. This paper proposed a variable clustering management method, which manages multiple data streaming dynamically, to support flexible clustering. The method manages synchronization effectively and differently with conventional streaming methods in data streaming environment and manages clustering streaming after the structural presentation level and the fitness presentation level. In the structural presentation level, the stream structure is presented using level matching and accumulation matching, and clustering management is carried out by the management of dynamic segment and static segment. The performance of the proposed method is tested by using k-means method, C/S server method, CDN method, and simulation. The test results showed that the proposed method has better performance than the other methods.

• Journal of Broadcast Engineering
• /
• v.6 no.3
• /
• pp.205-214
• /
• 2001

In this Paper, we present an MP4 file streaming system over IP networks. Using the proposed system a user can access MP4 contents in the servers via H) networks and interact with the contents. The MP4 file format is designed to contain the media information of MPEG-4 and is object-oriented. The presented streaming server system contains GUI, session manager, splitter, SL- packetizer and transmitter. In addition, we knave implemented the client system based on the GUI -2D player, the MPEG-4 reference software. The Presented streaming system is designed use RTF for the media data requiring real-time streaming RTCP for QoS management and TCP for the data such as IOD(Initial Object Descriptor), OD(Object Descriptor) BIFS(Binary Format for Scene), which should be transmitted for the streaming and the data, such as still image and text, which can be entirely transmitted in a packet.

• Journal of KIISE:Computing Practices and Letters
• /
• v.14 no.7
• /
• pp.748-752
• /
• 2008

Various services are developed from advancement of satellite imagery methodologies and internet infrastructure expansions. However, most of these services still rely upon low-resolution satellite images combined with DEM models. In this paper, we have implemented the raw data processing modules and other modules that transfer and render high-spatial resolution satellite images for efficient streaming services in web environments. By utilizing the Bukhan-mountain data as a pilot study, the paper has proposed the efficient approach to solve graphical problems in real time processing the large geographical area.

• Journal of Advanced Navigation Technology
• /
• v.27 no.5
• /
• pp.685-689
• /
• 2023

The proposed system in the study aims to detect forest fires in real-time stream data received from the drone-camera. Recently, the number of wildfires has been increasing, and also the large scaled wildfires are frequent more and more. In order to prevent forest fire damage, many experiments using the drone camera and vision analysis are actively conducted, however there were many challenges, such as network speed, pre-processing, and model performance, to detect forest fires from real-time streaming data of the flying drone. Therefore, this study applied image data processing works to capture five good image frames for vision analysis from whole streaming data and then developed the object detection model based on YOLO_v2. As the result, the classification model performance of forest fire images reached upto 93% of accuracy, and the field test for the model verification detected the forest fire with about 70% accuracy.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.3
• /
• pp.328-335
• /
• 2002

When we want to transfer video streaming data through computer networks, we will have to be allocated a larger bandwidth compared to a general application. In general, it causes a serious network overload inevitably due to the limited bandwidth. In this paper, in order to resolve the problem, we haute taken a method for transmitting video streaming data using RTP and RTCP. With RR(Receiver Report) packet in RTCP we will test it to check whether the traffic in a network has occurred or not. If it happened, we haute tried to reduce the overall network traffic by dynamically changing the quantization factor of the Motion JPEG that is one of the encoding styles in JMF. When the ratio of the average of transmission for each session to the average of overall transmission is greater than 7%, we should adjust the amount of data to be transmitted for each session to reach the session mean values. The experimental results show that the proposed method taken here reduces the overload effectively and therefore improves the efficiency for transmitting video streaming data.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.24 no.1
• /
• pp.31-40
• /
• 2021

The multi-channel video streaming system is an essential device for future ground combat vehicles. For the system, the application of digital interfaces is required instead of the direct analog method to support selectable multiple channels. However, due to the characteristics of the digital interfaces that require en/decoding and signal conversion, the system should support the ability to adapt to quality and delay requirements depending on how video data is utilized. To support addressed issue, this study designs and emulates the multi-channel compressed-video streaming system of ground combat vehicle's fire control system based on commercial standards. Using the system, this study analyzes the quality of video according to the rotational speed of the acquisition device and Glass-to-Glass (G2G) delay between video acquisition and display devices according to video compression rates. Through these experiments and analysis, this paper presents the design direction of the system having scalability on the latest technology while providing high-quality video data streaming flexibly.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.5
• /
• pp.9-13
• /
• 2023

Multimedia streaming data is very large in size and accessed sequentially, making the LRU(Least Recently Used) algorithm widely used to improve I/O performance in traditional caching environments ineffective. Experimental analysis of this has shown the superiority of interval-based caching over LRU, but the theoretical basis has not been proven. In this paper, we design a cache performance model to analyze the optimality of caching for multimedia streaming environments and design a theoretically optimal caching algorithm based on interval caching. Then, we show that the algorithm we design is an optimal algorithm that minimizes cache misses of streaming data based on the proposed model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.4
• /
• pp.800-818
• /
• 2013

Supporting video streaming over multi-hop wireless networks is particularly challenging due to the time-varying and error-prone characteristics of the wireless channel. In this paper, we propose a joint optimization scheme for video streaming over multi-hop wireless networks. Our coding scheme, called Joint Source/Network Coding (JSNC), combines source coding and network coding to maximize the video quality under the limited wireless resources and coding constraints. JSNC segments the streaming data into generations at the source node and exploits the intra-session coding on both the source and the intermediate nodes. The size of the generation and the level of redundancy influence the streaming performance significantly and need to be determined carefully. We formulate the problem as an optimization problem with the objective of minimizing the end-to-end distortion by jointly considering the generation size and the coding redundancy. The simulation results demonstrate that, with the appropriate generation size and coding redundancy, the JSNC scheme can achieve an optimal performance for video streaming over multi-hop wireless networks.