High-Performance Grid and Cloud Computing Workshop (HPGC) 2012, pp.1-5
Language
English
Type
Conference Paper
Abstract
The server-based content delivery system has experienced a large amount of operation costs and also has faced the lack of adaptive control for differentiated streaming services. To address this problem, some works have shown that the possibility of large-scale data dissemination can be achieved over peer-to-peer networks, if the data (particularly video) is constructed by the scalable video coding. Despite the expected strengths of integrating the two techniques, it is still difficult to ensure collective bandwidth (layer) availability in peer-to-peer networks, where large-scalable, volatile, and heterogeneous peers demand different quality of services (QoS). In this paper, we first formulate a layer scheduling problem from understanding some constraints, which originates from the layer dependency, the transmission rule, and the bandwidth heterogeneity. We then propose that this problem can be solved based on the ideas of how a threshold layer index of scalable video can be determined. By differently prioritizing each layer, the proposed layer scheduling scheme can guarantee the differentiated streaming services using a random scheduling algorithm, providing low complexity in decision. To cope with dynamic intensity of churns in super-peer overlay networks, we also propose a peer-utility based promotion (PUP) algorithm that selects the most qualified neighbor to guarantee the sustained quality of streaming. Simulation results show that the proposed layer scheduling scheme with PUP highly outperforms those with different peer selection strategies in terms of the average bandwidth (6.9 % higher at least) and the variation of utilization (11.3 % lower at least) without violating the constraints on streaming video and network properties.
KSP Keywords
Data Dissemination, Delivery systems, Large-scale Data, Low complexity, Network Properties, Overlay networks, Peer selection, Peer-to-Peer(P2P), Random Scheduling, Scalable Video Coding, Scheduling Scheme
Copyright Policy
ETRI KSP Copyright Policy
The materials provided on this website are subject to copyrights owned by ETRI and protected by the Copyright Act. Any reproduction, modification, or distribution, in whole or in part, requires the prior explicit approval of ETRI. However, under Article 24.2 of the Copyright Act, the materials may be freely used provided the user complies with the following terms:
The materials to be used must have attached a Korea Open Government License (KOGL) Type 4 symbol, which is similar to CC-BY-NC-ND (Creative Commons Attribution Non-Commercial No Derivatives License). Users are free to use the materials only for non-commercial purposes, provided that original works are properly cited and that no alterations, modifications, or changes to such works is made. This website may contain materials for which ETRI does not hold full copyright or for which ETRI shares copyright in conjunction with other third parties. Without explicit permission, any use of such materials without KOGL indication is strictly prohibited and will constitute an infringement of the copyright of ETRI or of the relevant copyright holders.
J. Kim et. al, "Trends in Lightweight Kernel for Many core Based High-Performance Computing", Electronics and Telecommunications Trends. Vol. 32, No. 4, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
J. Sim et.al, “the Fourth Industrial Revolution and ICT – IDX Strategy for leading the Fourth Industrial Revolution”, ETRI Insight, 2017, KOGL Type 4: Source Indication + Commercial Use Prohibition + Change Prohibition
If you have any questions or concerns about these terms of use, or if you would like to request permission to use any material on this website, please feel free to contact us
KOGL Type 4:(Source Indication + Commercial Use Prohibition+Change Prohibition)
Contact ETRI, Research Information Service Section
Privacy Policy
ETRI KSP Privacy Policy
ETRI does not collect personal information from external users who access our Knowledge Sharing Platform (KSP). Unathorized automated collection of researcher information from our platform without ETRI's consent is strictly prohibited.
[Researcher Information Disclosure] ETRI publicly shares specific researcher information related to research outcomes, including the researcher's name, department, work email, and work phone number.
※ ETRI does not share employee photographs with external users without the explicit consent of the researcher. If a researcher provides consent, their photograph may be displayed on the KSP.