摘要
为提升能源星火链网络群智感知效果,降低任务分配成本,提出能源星火链网络群智感知任务分配方法。以最初成本、代价成本、时间成本最低作为目标函数,构建任务分配模型,采用鲸鱼优化算法求解获取最佳任务分配结果。根据任务与感知设备起始位置距离、时间窗大小确定已分配任务优先执行顺序,结合感知设备用户弹性时间限制及信誉水平,弹性调节分配任务,判断感知设备用户是否接收额外任务,完成感知任务分配。实验结果表明:该方法任务分配的成本较低,感知设备用户数量较多、任务执行效率较高。
In order to improve the crowdsensing effect of Xinghuo chain network and reduce the task allocation cost,a crowdsensing task allocation method of energy Xinghuo network is proposed.The lowest initial cost,cost and the lowest time cost are taken as the objective function to construct the task allocation model,and the whale optimization algorithm is used to obtain the best task allocation result.The priority execution order of the allocated tasks is determined according to the distance between the task and the starting position of the sensing device and the size of the time window.The allocated tasks are adjusted flexibly in combination with the elastic time limit and reputation level of the sensing device user.Then,whether the sensing device user receives additional tasks is judged and the sensing task allocation is completed.The experiment results show that this method has the advantages of low cost of task allocation,large number of sensing device users and high task execution efficiency.
作者
杨明杰
王军
李瑞琪
郭名康
裴之垣
寇小霞
YANG Ming-jie;WANG Jun;LI Rui-qi;GUO Ming-kang;PEI Zhi-yuan;KOU Xiao-xia(Internet Division,State Grid Gansu Electric Power Company,Lanzhou 730050,China;Dingxi Power Company,State Grid Gansu Electric Power Company,Dingxi 744300,Gansu Province,China)
出处
《信息技术》
2024年第2期166-171,179,共7页
Information Technology
关键词
星火链网络
群智感知
任务分配
感知设备
优先级
Xinghuo chain network
crowdsensing
task assignment
sensing device
priority
