A Centralized Algorithm for Assigning MDC Video Application in Virtual Network

作     者：ZHU Kai WU Chunming ZHOU Boyang CHEN Fei WANG Haoxue 

作者机构：Next Generation Network Laboratory College of Computer Science and Technology Zhejiang University Henan Electrical Power Research Institute State Grid Corporation of China Information Engineering University 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2016年第13卷第S1期

页      面：158-166页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081001[工学-通信与信息系统] 

基　　金：supported by the National Basic Research Program of China (2012CB315903) the National Science and Technology Support Program (2014BAH24F01) the Program for Key Science and Technology Innovation Team of Zhejiang Province (2011R50010-21, 2013TD20) 863 Program of China (2015AA016103) the National Natural Science Foundation of China (61379118) the Fundamental Research Funds for the Central Universities 

主　　题：multiple description coding video multipath programming hierarchical clustering scheme multicast tree construction network virtualization 

摘      要：Providing services on demand is a major contributing factor to drive the increasingly development of the software defined network. However, it should supply all the current popular applications before it really attains widespread development. Multiple Description Coding(MDC) video applications, as a popular application in the current network, should be reasonably supported in this novel network virtualization environment. In this paper, we address this issue to assign MDC video application into virtual networks with an efficient centralized algorithm(CAMDV). Since this problem is an NP-hard problem, we design an algorithm that can effectively balance the user satisfaction and network resource cost. Previous work just builds a global multicast tree for each description to connect all the destination nodes by breadth-first search strategy or shortest path tree algorithm. But those methods could not achieve an optimal balance or a high-level user satisfaction. By introducing the hierarchical clustering scheme, our algorithm decomposes the whole mapping procedure into multicast tree construction and multipath description distribution. A serial of simulation experiments show that our centralized algorithm could achieve a better performance in balancing the user satisfaction and average mapping cost in comparison with its rivals.