利用改进ILP和二进制穷举择优法的低成本物联网流量多目标路由感知方法

针对无线网络不能为多样化应用需求提供支持及卸载移动通信核心成本较高的问题,提出了一种改进整数线性规划模型(IILP)结合二进制穷举择优法的低成本混合物联网流量多目标路由感知方法。首先,基于IILP对混合物联网流量路由感知进行建模,获得准确的能量感知模型;其次,采用多目标MAXI路由感知算法对多目标路由感知模型进行了求解,降低了流量路由求解的延时;最后,采用二进制穷举择优法对流量路由感知的吞吐量进行扩展。仿真实验表明,与现有算法相比,提出方法降低了求解的延时,提高了流量的吞吐量,减少了流量的丢包率,同时还降低了混合物联网多目标路由感知的成本。

Multi-objective routing perception method using improved ILP and binary exhaustive selection method for low cost IoT traffic

Aiming at the problem that integer linear programming model combined with the preferred method of binary exhaustive multi-objective routing perception mixture low cost network flow method for wireless network can’t support the demand for diverse applications and uninstall mobile communication core problem of high cost,this paper proposed an integer linear programming model combining with the preferred method of binary exhaustive mixture low cost network flow multi-objective routing technology.Firstly,based on the improved integer linear programming(IILP)model,it modeled the traffic routing perception of the mixture network to obtain the accurate energy perception model.Secondly,it used the multi-objective routing sensing model by using the multi-objective MAXI routing sensing algorithm,which reduced the latency of traffic routing solving.Finally,it extended the throughput of traffic routing perception by binary exhaustive selection method.Experiments show that compared with the existing algorithm,the proposed exhaustive mixture low cost network flow multi-objective routing method has reduced the delay of solving perception,improved the traffic throughput,reduce the packet loss rate of the flow,at the same time,also reduce the cost of mixture networking multi-objective routing perception.