大规模异构传感通信大数据智能调度仿真

Large Scale Heterogeneous Sensor Communication Large Data Intelligent Scheduling Simulation

传统调度方法没有考虑网络节点剩余能量问题,造成节点过早死亡,网络拥塞严重,平均调度延时较长,收敛速度较慢等问题。针对上述问题,提出了基于改进蚁群算法的大规模异构传感通信大数据智能调度方法。方法采用四元组形式描述异构传感通信大数据智能调度模型,给出了模型成立的3点假设条件,并建立了异构传感通信大数据智能调度成本模型。基于调度模型和调度成本模型模型,通过计算节点剩余能量和实时更新网络节点信息素浓度的方式改进原有蚁群算法,结合定向扩散路由算法,在调度任务执行源节点与目标节点之间建立多条通信路径,均衡各个节点能量消耗,实现大规模异构传感通信大数据智能调度。仿真结果表明,所提方法具有避免网络局部拥塞,减小平均调度延时,加快收敛速度,延长节点生存寿命的优点。

Due to premature death of node,serious network congestion,long average scheduling delay,and slow convergence speed of traditional scheduling method,a new intelligent scheduling method of big data in large scale heterogeneous sensor communication based on the modified ant colony algorithm was presented in this article.Firstly,intelligent scheduling model was described via quadruple form.Three assumed conditions for the succeed model were provided and cost model of the intelligent scheduling was built.Based on the scheduling model and cost model,original ant colony algorithm was modified via calculating residual energy of node and updating pheromone concentration.Directed diffusion routing algorithm was integrated to build multiple communication path between source node of scheduling task execution and goal node.Energy consumption of each node was balanced.Thus,the intelligent scheduling was achieved.Simulation results show that the method can avoid network congestion and decrease long average scheduling delay.Meanwhile,it can accelerate convergence speed and prolong node lifetime.