摘要
针对云环境所含数据信息过于繁杂的问题,为了滤除冗余信息,加强数据采集效率,提出云环境下启发式网络信息采集模型。首先通过分析云环境具备的多用户、高动态等优势与多攻击面、安全威胁等隐患,采用能够与之匹配的启发式算法创建模型,利用约束条件与采集周期得到节点的有效位置。然后根据可用信息传输时间与遍历访问求得节点的效用贡献,并通过WSN网络流的映射发现初始节点与目标节点的关系,从而设定该网络层的频率。将节点连接度与启发式算法结合,完成最大连接度路由的选取,利用其可行度来均衡能耗,最后在合理阈值内与服务水平协议需求的共同作用下,完成网络信息采集模型。仿真结果表明,上述模型能够满足不同的可靠性需求,且使网络功率能耗更加均衡,具备较高的采集精准性与冗余信息过滤的有效性。
In order to filter the redundant information and enhance the efficiency of data collection,a model of collecting heuristic network information in cloud environment was proposed.Firstly,the advantages such as multi-us⁃er and high dynamic performance,and the hidden dangers such as multi-attack surfaces or threats in cloud environ⁃ment were analyzed.Secondly,a heuristic algorithm that could match with cloud environment was adopted to build the model.Thirdly,the constraints and collection cycle were used to find out the effective location of node.According to the transmission time of available information and the traversal access,the effective contribution of node was obtained.Moreover,the relationship between initial node and target node was found through the mapping for WSN network flow,and then the frequency of the network layer was determined.In addition,the node connectivity was combined with heuristic algorithm,so that the maximum connectivity routing could be selected.After that,its feasibility was used to balance the energy consumption.Finally,the network information collection model was built based on reasona⁃ble threshold and service level protocol requirements.Simulation results show that the designed model can meet the different requirements for reliability and make the network power consumption more balanced.In addition,this model has high acquisition accuracy and high effectiveness of filtering redundant information.
作者
伏琰
FU Yan(Zhengzhou University,Zhengzho Henan 450001,China)
出处
《计算机仿真》
北大核心
2020年第9期328-332,共5页
Computer Simulation
基金
国家社会科学基金(16BTQ069)。
关键词
云环境
启发式
信息采集
节点
Cloud environment
Heuristic
Information collection
Node
