Large-scale cooperative caching and application-level multicast in multimedia content delivery networks

2005 ◽  
Vol 43 (5) ◽  
pp. 98-105 ◽  
Author(s):  
Jian Ni ◽  
D.H.K. Tsang
Keyword(s):  
Large Scale ◽  
Content Delivery ◽  
Multimedia Content ◽  
Cooperative Caching ◽  
Content Delivery Networks ◽  
Application Level Multicast ◽  
Multimedia Content Delivery ◽  
Delivery Networks

Large-scale multimedia content delivery over optical networks for interactive TV services

2006 ◽  
Vol 22 (8) ◽  
pp. 1018-1024 ◽  
Author(s):  
Miroslaw Czyrnek ◽  
Ewa Kusmierek ◽  
Cezary Mazurek ◽  
Maciej Stroinski
Keyword(s):  
Optical Networks ◽  
Large Scale ◽  
Content Delivery ◽  
Multimedia Content ◽  
Interactive Tv ◽  
Multimedia Content Delivery

An Incentive Compatible Mechanism for Replica Placement in Peer-Assisted Content Distribution

2020 ◽  
Vol 12 (1) ◽  
pp. 47-67 ◽  
Author(s):  
Prabir Bhattacharya ◽  
Minzhe Guo
Keyword(s):  
Design Theory ◽  
Large Scale ◽  
State Of The Art ◽  
Incentive Compatibility ◽  
Content Delivery ◽  
Replica Placement ◽  
Key Technology ◽  
Incentive Compatible ◽  
Content Delivery Networks ◽  
Delivery Networks

Content delivery is a key technology on the Internet to achieve large scale, low-latency, reliable, and intelligent data delivery. Replica placement (RP) is a key machinery in content delivery systems to achieve efficient and effective content delivery. This work proposes a novel decentralized algorithm for the replica placement in peer-assisted content delivery networks with simultaneous considerations for peer incentives. By applying techniques from the algorithmic mechanism design theory, the authors show the incentive compatibility of the proposed algorithm. Experiments were conducted to validate the properties of the proposed method and comparisons were made with the state-of-the-art RP algorithms.

Network Coordinates-Based Request Routing Approach to Improve Multimedia Content Delivery

2012 ◽  
Vol 182-183 ◽  
pp. 888-892
Author(s):  
Wen Hui ◽  
Hai Ying Zhao ◽  
Chuang Lin ◽  
Yang Yang
Keyword(s):  
Large Scale ◽  
Content Delivery ◽  
Coordinate Space ◽  
Multimedia Content ◽  
Status Change ◽  
Content Delivery Network ◽  
Request Routing ◽  
Network Coordinates ◽  
Multimedia Content Delivery ◽  
Server Clusters

In order to solve the problem of large-scale multimedia content delivery, we present Multimedia Content Delivery Network (MM-CDN). For providing multimedia services with high quality in MM-CDN, the traditional request routing approaches in CDN face two key challenges, namely performance and cost. To balance the tradeoff between performance and cost in MM-CDN, we propose an improved request routing approach. First, based on the idea of network coordinates, the computation and transfer costs of different server clusters are computed depending on the network and server status change. Then, all the server clusters are reorganized in the coordinate space. Finally, user requests can be adaptively redirected to the server clusters with minimum cost without sacrificing performance. Computational results show that the effectiveness of our approach with acceptable time performance.

Data Replication in Large Scale Content Delivery Networks: A Genetic Algorithm Approach

2018 ◽  
Vol 27 (12) ◽  
pp. 1850189 ◽  
Author(s):  
Hadi Zare Fatin ◽  
Shahram Jamali ◽  
Gholamreza Zare Fatin
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Service Level ◽  
Content Delivery ◽  
Mixed Integer ◽  
Content Delivery Networks ◽  
Delivery Costs ◽  
Geographically Distributed ◽  
Genetic Algorithm Approach ◽  
Delivery Networks

Content delivery networks (CDN) bring the content close to the users employing the replicated servers. In this context, main issue is allocation of the content replicas to these geographically distributed replica servers. The allocation goal is to minimize the storage and the delivery costs and at the same time to satisfy service-level agreements. In this paper, a mixed integer programming (MIP) formulation for the problem of the allocation has been proposed and then by utilization of the genetic algorithm (GA) its optimum solutions were extracted. Numerical evaluation results show that the proposed algorithm outperforms others in terms of the storage cost, delivery cost and computation complexity.

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