基于私有云节点转存机制的突发传感数据优化算法研究

The research of burst sensor data optimization algorithm based on private cloud node ransfer mechanism

为解决当前传感网络部署过程中存在的节点存储能力较弱.动态数据优化效果较低等问题,提出一种基于私有云节点转存机制的突发传感数据优化算法.首先,综合考虑数据传输冗余带宽、数据片调用率、时间片粒度等影响因素,引入周期切片转存机制,以精准执行节点存储流程,提高私有云节点的数据存储能力.然后,采用时间片粒度波动率方式优化存储波动,实现多路数据竞争存储过程中的间歇存储,显著改善数据存储性能.仿真实验表明,与当前传感领域常用的传感数据优化算法相比,本文算法具有更低的数据重传输率和更强的私有云存储能力,可在实践中进一步推广应用.

In order to address the shortcomings of weak node storage capacity and low dynamic data optimization effect in the current deployment process of sensor networks,a burst sensor data optimization algorithm based on private cloud node transfer mechanism is proposed.Firstly,this approach considers factors such as redundant bandwidth for data transmission,data slice call rate,and time slice granularity,a periodic slicing transfer mechanism was introduced to accurately execute node storage processes and improve the data storage capacity of private cloud nodes.Then,the algorithm optimized storage fluctuations using an approach based on time slice granularity fluctuation rates,which achieves intermittent storage capabilities during multi-channel data competition storage processes and further improved data storage performance.Simulation experiments show that compared with the commonly used sensor data optimization algorithm,the proposed algorithm has lower data retransmission rate,which can be further promoted and applied in practice.