光纤网络中噪声干扰下的云数据调度模型优化

Optimization of Cloud Data Scheduling Model with Noise Interference in Optical Fiber Network

光纤网络中受到复杂的电磁色噪声干扰,云数据调度在干扰下容易产生资源蜕变,导致调度实时性和准确性不好。传统方法采用优先级列表调度方法,在变异尺度调整中产生时间漂移,影响调度准确性。提出一种基于自相关匹配滤波和时分多址时隙分配的光纤网络中云数据分簇调度算法。对光纤网络中噪声干扰进行自相关匹配滤波抑制,进行了云数据调度模型的总体设计和云数据特征信息流提取,对提取的光纤网络噪声干扰下的特征信息流进行自相关匹配滤波处理,采用时分多址时隙分配方法实现滤波后的云数据的优化调度,按照前导时隙的分配机制,使待调度的光纤网络云数据特征形成最佳匹配。仿真结果表明,该模型进行云数据调度的抗噪性能较好,云数据的特征匹配度较高,调度准确度较高。

Due to the complexity of electromagnetic interference in the optical fiber network, it is easy to generate resources under the interference of cloud data scheduling under the interference, which leads to the scheduling of real -time and accuracy is not good. In the traditional method, the priority list scheduling method is used to generate time drift in the variation scale adjustment, which affects the accuracy of the scheduling. The optical fiber network data cloud cluster scheduling algorithm based on auto correlation matched filtering and TDMA slot allocation points. Auto- correlation matching filter to suppress, the cloud data scheduling model of overall design and cloud data feature information flow to extract the noise interference in optical fiber network, on the extraction of optical fiber network noise characteristics of information flow for optimal scheduling of auto correlation matched filtering processing, using TDMA time slot assignment method to achieve filtering after the cloud data, in accordance with the preceding time slot allocation mechanism, so that to be scheduling of optical network cloud data features form the best match. The simulation resuits show that the proposed model is better in anti noise performance of cloud data scheduling, the characteristics of the cloud data is higher, and the scheduling accuracy is higher.