利用Hawkes过程模型的移动边缘计算服务质量预测

Service Quality Prediction of Mobile Edge Computing Using Hawkes Process Model

移动边缘计算为用户提供高性能、低延时、高带宽的网络服务.在移动边缘计算环境中,服务质量预测对提高用户的满意度具有重要作用.目标用户的相似用户在历史时刻使用该边缘服务器访问服务的服务质量高,对目标用户访问该边缘服务器有激励作用,并且使用该边缘服务器服务质量高的相似用户越多,起到的激励作用也会累加.考虑到激励作用可以提高服务质量预测准确性,本文提出基于Hawkes过程模型的移动边缘计算服务质量预测方法.方法首先确定目标用户的相似用户,再提取相似用户在边缘服务器上的服务质量数据,使用最大似然估计方法训练Hawkes过程模型,得到训练后的各参数值,最后使用Hawkes过程模型对目标用户使用附近边缘服务器服务质量高的概率进行预测,得到概率最高的边缘服务器,以提高用户的满意度.与现有方法的对比实验表明,本文所提出的方法对移动边缘服务环境中未知QoS的预测更为准确.

Mobile edge computing provides users with high-performance,low-latency,and high-bandwidth network services.In the mobile edge computing environment,service quality prediction plays an important role in improving user satisfaction.Similar users of the target user have used the edge server to access the service at historical moments with high service quality,which has an incentive effect for the target user to access the edge server,and the more similar users who use the edge server with high service quality,the incentive effect will accumulate.Considering that incentives can improve the accuracy of service quality prediction,this paper proposes a mobile edge computing service quality prediction method based on the Hawkes process model.The method first determines the similar users of the target user,then extracts the service quality data of similar users on the edge server,uses the maximum likelihood estimation method to train the Hawkes process model,and obtains the parameter values after training.Finally,the Hawkes process model is used to predict the probability,the target user will use a nearby edge server with high service quality,and obtain the edge server with the highest probability to improve user satisfaction.Comparison experiments with existing methods show that the method proposed in this paper is more accurate in predicting unknown QoS in the mobile edge service environment.