海量存储网络中高维数据传输能耗优化仿真

Mass Storage Network of High-Dimensional Data Transmission Energy Consumption Optimization Simulation

针对海量存储网络中高维数据传输能耗过大的问题,需要对海量存储网络中传输能耗进行计算。但是采用当前方法进行数据传输能耗计算时,无法给出感知节点的覆盖范围,存在数据传输效率低问题。为此,提出一种基于免疫规划的海量存储网络中高维数据传输能耗优化方法。上述方法先利用连通支配集构造海量存储网络的节点调度机制,计算出每个节点覆盖区域面积,建立了以网络覆盖率和节点率为目标函数的数学模型,得到节点调度适应度函数,融合免疫理论思想将高维数据传输能耗优化问题定义为抗原,将能耗优化的可行解定义为抗体,利用亲和度函数来判断可行解的优劣,并完成对海量存储网络中高维数据传输能耗优化。仿真证明,所提方法优化性能好,可以有效地提升海量存储网络中高维数据传输的效率。

An optimization method for energy consumption of high - dimensional data transmission in mass storage network based on immunization program is proposed. Firstly, connected dominating set is used to build scheduling mechanism of the network node, and area of coverage region of each node is worked out. Then, mathematic model u- sing network coverage rate and node rate as objective function is buih and fitness function of node scheduling is ob- tained. Moreover, integrated with theory of immunity, the energy consumption problem is defined as antigen, and feasi- ble solution of energy consumption optimization is defined as antibody. Affinity function is used to judge advantages and disadvantages of the feasible solution. Finally, the optimization of energy consumption is completed. Simulation results show that the proposed method has excellent optimization performance. It can improve efficiency of the high - dimensional data transmission effectively.