局域网限速状态下的资源调度模型仿真

Simulation of Resource Scheduling Model under LAN Speed Limit State

在局域网限速状态下进行资源调度时,网络资源受到传输区域的影响,在调度过程中存在较大的流量突变随机性。传统的网络资源调度算法在应对海量突变流量时,采用延迟限制通信的方法,随便能缓解流量峰值,但仅仅通过外加通信约束条件约束、延迟流量突变的通信过程,调度过程存在弊端。提出采用混合蚁群算法的局域网限速状态下资源调度方法,将禁忌搜索作为蚁群算法局部搜索策略,并通过结合分布估计提高算法的收敛速度,把局域网限速状态下资源均衡与优化问题转化为组合优化的最短路径问题,进行计算求精确解。仿真结果表明,利用混合蚂蚁算法在局域网限速状态下进行资源调度,具一定鲁棒性和分布性,提升了调度工作效率。

The paper put forward a resource scheduling method under Local area network （LAN） speed limit state, based on hybrid ant colony algorithm. We took tabu search as the local search strategy of ant colony algorithm and, and improved the convergence speed of the algorithm by combining distribution estimation. The resources balanced and optimization problem under the LAN speed limit state was transformed into the combinatorial optimization of shortest path problem, to calculate exact solution. Simulation experimental results show that the hybrid ant algorithm in local area network resource scheduling under the limit state is of certain robustness and distributed resistance, which can improve the efficiency of dispatching work.