基于链路预测的手机节能方法

移动云计算为部署大量移动服务提供了技术支持，但用户在不稳定的通信条件下访问云资源往往需要大量的能耗，制约了移动云计算的广泛应用.对此，提出了基于用户交互行为最大化的链路预测方法.首先在数据预测模型的基础上利用基于互动关系改进的交互度方法对已知用户访问的数据进行预测；再结合基于用户行为的社交网络Friendlink方法对预测数据进行数据分析筛选，利用数据预存储机制来预存上述预测数据.实验结果表明，在保证不涉及用户隐私信息，并提高用户下次访问命中率的情况下，达到了预期的手机节能目的.

Mobile Phone Energy Saving Based on Link Prediction

The technology of mobile cloud computing is benefit for deploying various mobile applications. However, there is an energy consumption problem to access cloud resources via mobile phone, which needs to establish connections many times under unstable communication conditions. To solve this problem, a link prediction method based on maximum user interaction behavior was proposed. Firstly, based on data prediction model, an interaction degree method based on improved interaction relationship is used to predict the data accessed by users. Then, combined with the friend link method of social network based on user behavior, the prediction data is analyzed and filtered, and the pre-storage mechanism is used to pre-store the above prediction data. Experiments show that the expected energy saving of mobile phones can be achieved without involving users' private information and improving the hit rate of users' next visit.