• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권12호
• /
• pp.3200-3219
• /
• 2013

This paper proposes an adaptive combined scalable video coding (CSVC) system for video transmission over MIMO-OFDM (Multiple-Input Multiple-Output-Orthogonal Frequency Division Multiplexing) broadband wireless communication systems. The scalable combination method of CSVC adaptively combines the medium grain scalable (MGS), the coarse grain scalable (CGS) and the scalable spatial modes with the limited feedback partially from channel state information (CSI) of MIMO-OFDM systems. The objective is to improve the average of peak signal-to-noise ratio (PSNR) and bit error rate (BER) of the received video stream by exploiting partial CSI of video sources and channel condition. Experimental results show that the delivered quality using the proposed adaptive CSVC over MIMO-OFDM system performs better than those proposed previously in the literature.

• IEIE Transactions on Smart Processing and Computing
• /
• 제4권6호
• /
• pp.434-442
• /
• 2015

In this paper, we propose an integrated spatial and view scalable video codec based on high efficiency video coding (HEVC). The proposed video codec is developed based on similarity and uniqueness between the scalable extension and 3D multi-view extension of HEVC. To improve compression efficiency using the proposed scalable multi-view video codec, inter-layer and inter-view predictions are jointly employed by using high-level syntaxes that are defined to identify view and layer information. For the inter-view and inter-layer predictions, a decoded picture buffer (DPB) management algorithm is also proposed. The inter-view and inter-layer motion predictions are integrated into a consolidated prediction by harmonizing with the temporal motion prediction of HEVC. We found that the proposed scalable multi-view codec achieves bitrate reduction of 36.1%, 31.6% and 15.8% on the top of ${\times}2$, ${\times}1.5$ parallel scalable codec and parallel multi-view codec, respectively.

• Journal of information and communication convergence engineering
• /
• 제8권1호
• /
• pp.71-76
• /
• 2010

Scalable video coding (SVC) has been standardized as an extension of the H.264/AVC standard. SVC allows straightforward adaptation of video streams by providing layered bit streams. In this paper, we propose a SVC video-based multicasting system preserving scalable security which is able to provide a SVC video service while maintaining information security. In order to maintain information security between a server and a client during all transmission time, the proposed system immediately performs a packet filtering process without decoding with respect to encrypted data received in a routing device, thereby reducing an amount of calculations and latency.

• 한국정보전자통신기술학회논문지
• /
• 제9권4호
• /
• pp.313-322
• /
• 2016

본 논문에서는 멀티캐스트 패킷 재전송을 담당하는 기능을 기지국에 탑재하여 신뢰성있는 멀티캐스트 전송 프로토콜인 Scalable Multicast Protocol 성능을 개선하고자 한다. 유무선 통합망에서 Scalable Multicast Protocol 동작시, 무선 네트워크에서의 비트 에러나 단말의 이동성으로 패킷 재전송이 많이 발생한다. 이런 재전송 때문에 Scalable Multicast Protocol의 그룹에 제어 메시지 및 재전송 메시지가 증가하게 되며, 이는 또한 Scalable Multicast Protocol 세션 전체 성능을 저하시킨다. 본 논문은 기지국에 무선 환경에 있는 단말의 복구 요구 메시지에 대한 복구 메시지 전송을 담당하는 기능을 추가하여 전체 세션의 성능을 높이고자 한다. ARENA를 이용하여 제안한 방법이 멀티캐스트 세션에의 복구 요구 및 복구 메시지의 수를 줄일 수 있고 멀티캐스트 그룹 세션 전체의 성능을 향상시킬 수 있음을 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권9호
• /
• pp.2268-2283
• /
• 2013

Scalable video coding can handle peer heterogeneity of P2P streaming applications, but there is still a lack of comprehensive studies on how to use it to improve video playback quality. In this paper we propose a capacity aware scalable video coding mechanism for P2P on demand streaming system. The proposed mechanism includes capacity based neighbor selection, adaptive data scheduling and streaming layer adjustment, and can enable each peer to select appropriate streaming layers and acquire streaming chunks with proper sequence, along with choosing specific peers to provide them. Simulation results show that the presented mechanism can decrease the system's startup and playback delay, and increase the video playback quality as well as playback continuity, and thus it provides a better quality of experience for users.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권12호
• /
• pp.3096-3117
• /
• 2013

To execute the performance driven Grid applications, an effective and scalable workflow scheduling is seen as an essential. To optimize cost & makespan, in this paper, we propose a Scalable Cost-Time Trade-off (SCTT) model for scheduling workflow tasks. We have developed a heuristic algorithm known as Scalable Cost-Time Trade-off Scheduling (SCTTS) with a lower runtime complexity based on the proposed SCTT model. We have compared the performance of our proposed approach with other heuristic and meta-heuristic based scheduling strategies using simulations. The results show that the proposed approach improves performance and scalability with different workflow sizes, task parallelism and heterogeneous resources. This method, therefore, outperforms other methods.

• ETRI Journal
• /
• 제28권2호
• /
• pp.239-242
• /
• 2006

In this letter, we propose a new functionality to scalable video coding (SVC), that is, the support of multiple region of interests (ROIs) for heterogeneous display resolution. The main objective of SVC is to provide temporal, spatial, and quality scalability of an encoded bitstream. The ROI is an area that is semantically important to a particular user, especially users with heterogeneous display resolutions. Less transmission bandwidth is needed compared to when the entire region is transmitted/decoded and then sub-sampled or cropped. To support multiple ROIs in SVC, we adopt flexible macroblock ordering (FMO), a tool defined in H.264, and based on it, we propose a way to encode and, independently, decode ROIs. The proposed method is implemented on the joint scalable video model (JSVM) and its functionality verified.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2017년도 추계학술대회
• /
• pp.247-249
• /
• 2017

NIST에서 표준으로 정의된 P-192, P-224, P-256, P-384 타원곡선 상의 스칼라 곱셈(scalar multiplication) 연산을 지원하는 Scalable 타원곡선 암호(Elliptic Curve Cryptography; ECC) 프로세서의 설계에 대해 기술한다. 투영(projective) 좌표계를 이용하여 하드웨어 자원 소모가 큰 나눗셈 연산을 제거하였으며, GF(p) 상의 덧셈, 뺄셈, 곱셈 등의 유한체 연산을 지원한다. 워드 기반 몽고메리 곱셈기를 이용하여 다양한 크기의 필드(field)에서 고정된 하드웨어 자원을 통하여 곱셈 연산을 수행하도록 하였으며, 필드의 크기에 따라 연산 사이클이 증가하거나 감소한다. 설계된 Scalable ECC 프로세서는 Verilog HDL로 모델링 되었으며, Modelsim을 이용한 기능검증을 하였다. Xilinx Virtex5 FPGA 디바이스 합성결과 5,376-비트 RAM과 970 슬라이스로 구현되었으며, 최대 55 MHz의 동작 주파수를 갖는다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권10호
• /
• pp.4108-4125
• /
• 2015

This paper presents a scalable coding method for depth images by considering the quality of synthesized images in virtual views. First, we design a new edge detection algorithm that is based on calculating the depth difference between two neighboring pixels within the depth map. By choosing different thresholds, this algorithm generates a scalable bit stream that puts larger depth differences in front, followed by smaller depth differences. A scalable scheme is also designed for coding depth pixels through a layered sampling structure. At the receiver side, the full-resolution depth image is reconstructed from the received bits by solving a partial-differential-equation (PDE). Experimental results show that the proposed method improves the rate-distortion performance of synthesized images at virtual views and achieves better visual quality.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권1호
• /
• pp.288-301
• /
• 2017

In this paper, we propose an optimized algorithm for texture classification by computing a completed modeling of the local binary pattern (CLBP) instead of the traditional LBP of a scalable block size in an image. First, we show that the CLBP descriptor is a better representative than LBP by extracting more information from an image. Second, the CLBP features of scalable block size of an image has an adaptive capability in representing both gross and detailed features of an image and thus it is suitable for image texture classification. This paper successfully implements a machine learning scheme by applying the CLBP features of a scalable size to the Support Vector Machine (SVM) classifier. The proposed scheme has been evaluated on Outex and CUReT databases, and the evaluation result shows that the proposed approach achieves an improved recognition rate compared to the previous research results.