摘要
对于成本约束下的网络可靠性优化这一个 NP难题 ,针对已知的网络拓扑结构 ,提出了在 k种交换设备和 m种传输介质中选择合适的设备组合方案的粗粒度并行遗传算法 ,在满足成本预算的同时 ,优化网络的可用性 .仿真结果表明 ,对比传统的串行遗传算法 ,粗粒度并行遗传算法不但加速比高 。
Reliability optimization for computer networks, subjects to cost constraints, is a NP\|hard combinational problem. Regarding a known network topology, the problem of choosing links and switchers among alternatives different in reliability and cost is settled by a Coarse\|grained parallel genetic algorithm, which maximize the network availablity within a fixed budget. The simulations on a dedicated cluster demonstrate that contracting to the sequential counterpart, our parallel GA improves the quality of plans greatly with an evident speed\|up.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2003年第1期31-36,共6页
Systems Engineering-Theory & Practice
