摘要： 现有P2P分层流媒体中的数据分配算法是基于贪婪思想的确定性启发式算法，不能得到全局最优解。为此，提出一种基于备选数据块编码方式的粒子群遗传算法。定义备选数据块，建立问题的无约束整数规划模型。仿真实验表明，该算法在优化效果上能比现有算法提高5%~25%。
关键词:
对等网络,
分层流媒体,
数据分配,
NP完全问题,
粒子群遗传算法
Abstract: Data allocation in layered P2P streaming media is proved to be a NP-complete problem. The existing algorithm is a heuristic algorithm based on the greedy idea, which can not get the global solution. In order to develop a new algorithm for this problem, it defines the concept of data blocks for choosing, sets up a mathematic model of integer programming without restriction, and proposes a novel Particle Swarm Genetic Algorithm(PSGA) based on the encoding manner of Data Blocks for Choosing. Simulation demonstrates that the proposed PSGA’s performance improves 5%~25% than that of the existing algorithm.
Key words:
Peer-to-Peer(P2P) network,
layered streaming media,
data allocation,
NP-complete problem,
Particle Swarm Genetic Algorithm (PSGA)
中图分类号:
黄继海, 杨志宏, 赵建勋. P2P分层流媒体数据分配的粒子群遗传算法[J]. 计算机工程, 2011, 37(17): 188-190.
HUANG Ji-Hai, YANG Zhi-Hong, DIAO Jian-Xun. Particle Swarm Genetic Algorithm of Data Allocation in P2P Layered Streaming Media[J]. Computer Engineering, 2011, 37(17): 188-190.