移动网络数据传输路径负载均衡性配置仿真
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摘要
对移动网络数据传输路径负载的均衡性配置,能够有效改善网络大量数据传输引起的链路拥塞现象。对数据路径负载的均衡性配置,需要通过链路评估算法考虑通信链路关键度,选择最佳转发链路,完成负载均衡性配置。传统方法结合最小权值方法,对转发节点进行广泛选取,到忽略了对最佳转发链路的获取,导致负载配置精度偏低。提出基于移动网络节点和链路评估的负载均衡性配置方法,根据节点带宽利用率,去除节点负载最接近设置的节点转发阈值上限的节点,计算各个节点的可调用带宽,选择出最佳的转发节点;采用链路评估算法综合考虑通信链路关键度,根据通信链路剩余带宽选择最佳转发链路;通过调整动态负载均衡性配置阈值对传输的数据进行的调度,实现数据传输路径负载均衡性配置。实验证明,所提方法在数据传输成功率、吞吐率、网络资源利用率方面均有所改善。
This paper proposes a collocation method for load balance based on evaluation of node and link of mobile network. We eliminate node whose load is the nearest to the set upper forwarding threshold and calculate callable bandwidth of each node,then select the optimum forwarding node. The link evaluation algorithm is used to consider criticality of communication link and selected optimum forwarding link according to remaining bandwidth of the communication link. The transmission data are dispatched via adjusting collocation threshold of dynamic load balance.Thus,the collocation of the load balance is achieved. Simulation proves that the method improves transmission rate of data,throughput rate and network resource utilization.
This paper proposes a collocation method for load balance based on evaluation of node and link of mobile network. We eliminate node whose load is the nearest to the set upper forwarding threshold and calculate callable bandwidth of each node,then select the optimum forwarding node. The link evaluation algorithm is used to consider criticality of communication link and selected optimum forwarding link according to remaining bandwidth of the communication link. The transmission data are dispatched via adjusting collocation threshold of dynamic load balance.Thus,the collocation of the load balance is achieved. Simulation proves that the method improves transmission rate of data,throughput rate and network resource utilization.
引文
[1]刘海客,李集林,尤启迪,等.一种Open Flow网络的动态负载均衡方法[J].计算机工程,2016,42(8):85-90.
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[7]翟岩龙,贾娜娜,张鑫宇,等.拓扑结构感知的保守同步仿真动态负载均衡方法[J].系统仿真学报,2015,27(9):2008-2014.
[8]孙乔,赵蕾,邓卜侨,等.低开销的分布式数据库负载均衡技术[J].计算机应用,2017,37(s1):240-242.
[9]李颖.基于云计算的非连续层次数据挖掘方法.[J].西安工程大学学报,2016,4(30):498-503.
[10]杨杨,欧群雍.云环境下数据流量异常行为网络负载均衡设计[J].计算机仿真,2016,33(2):345-349.
[2]崔海莉,黄戈.基于Moose FS分布式云存储系统负载均衡方法的研究[J].合肥工业大学学报:自然科学版,2016,39(1):73-78.
[3]陶晓玲,韦毅,王勇.一种基于分层多代理的云计算负载均衡方法[J].电子学报,2016,44(9):2106-2113.
[4]张鹏.云平台网络负载均衡调度仿真研究[J].计算机仿真,2017,34(6):372-375.
[5]薛涛,马腾.基于资源权重最大资源利用率的动态资源调度算法[J].计算机应用研究,2016,33(5):1374-1378.
[6]孙凌宇,冷明,朱平,等.云计算环境下基于禁忌搜索的负载均衡任务调度优化算法[J].小型微型计算机系统,2015,36(9):1948-1952.
[7]翟岩龙,贾娜娜,张鑫宇,等.拓扑结构感知的保守同步仿真动态负载均衡方法[J].系统仿真学报,2015,27(9):2008-2014.
[8]孙乔,赵蕾,邓卜侨,等.低开销的分布式数据库负载均衡技术[J].计算机应用,2017,37(s1):240-242.
[9]李颖.基于云计算的非连续层次数据挖掘方法.[J].西安工程大学学报,2016,4(30):498-503.
[10]杨杨,欧群雍.云环境下数据流量异常行为网络负载均衡设计[J].计算机仿真,2016,33(2):345-349.