基于类脑智能的复杂网络机会数据竞争规避机制

Opportunity competition and evasion mechanism data with brain intelligent in complex networks

为了解决复杂网络的数据竞争和规避问题,基于类脑智能与复杂网络相结合提出了一种机会数据竞争规避机制。首先,针对大规模多变和动态复杂网络,基于拓扑演变建立了复杂网络机会数据竞争模型;其次,在已发生竞争的数据集合与复杂子网之间建立映射矩阵,通过类脑智能优化数据竞争序列,机会控制复杂网络大规模信息处理和数据规避。实验结果表明,所建立的数据竞争规避算法对于数据集损耗较低且具有较高的数据竞争检测效率;同时,所提出的算法与插入随机延迟规避机制相比具有低能耗优势。

In order to solve the problem of data competition and avoidance of complex net-works , this paper proposed a kind of opportunity data competition avoidance mechanism based on the combination of brain l ike intell igence and complex network. Firstly , according to the large-scale and dynamic complex network, it established the competition opportunity data based on the topological evolution. Secondly, it established the mapping between data matrix and complexnet-works in the competition , through brain intelligent optimization competition data sequence , opportunity to control the large-scale complex net-work information processing and data to avoid. The experimental results show that the efficiency of the data race detection data competition avoidance algorithm for data sets with low loss and high. At the same time , the proposed algo-rithm and insert random delay mechanism to avoid advantages compared with low energy consumption.