Working as aerial base stations,mobile robotic agents can be formed as a wireless robotic network to provide network services for on-ground mobile devices in a target area.Herein,a challenging issue is how to deploy t...Working as aerial base stations,mobile robotic agents can be formed as a wireless robotic network to provide network services for on-ground mobile devices in a target area.Herein,a challenging issue is how to deploy these mobile robotic agents to provide network services with good quality for more users,while considering the mobility of on-ground devices.In this paper,to solve this issue,we decouple the coverage problem into the vertical dimension and the horizontal dimension without any loss of optimization and introduce the network coverage model with maximum coverage range.Then,we propose a hybrid deployment algorithm based on the improved quick artificial bee colony.The algorithm is composed of a centralized deployment algorithm and a distributed one.The proposed deployment algorithm deploy a given number of mobile robotic agents to provide network services for the on-ground devices that are independent and identically distributed.Simulation results have demonstrated that the proposed algorithm deploys agents appropriately to cover more ground area and provide better coverage uniformity.展开更多
Mobile Edge Computing(MEC)is proposed to solve the needs of Inter-net of Things(IoT)users for high resource utilization,high reliability and low latency of service requests.However,the backup virtual machine is idle w...Mobile Edge Computing(MEC)is proposed to solve the needs of Inter-net of Things(IoT)users for high resource utilization,high reliability and low latency of service requests.However,the backup virtual machine is idle when its primary virtual machine is running normally,which will waste resources.Overbooking the backup virtual machine under the above circumstances can effectively improve resource utilization.First,these virtual machines are deployed into slots randomly,and then some tasks with cooperative relationship are off-loaded to virtual machines for processing.Different deployment locations have different resource utilization and average service response time.We want tofind a balanced solution that minimizes the average service response time of the IoT application while maximizing resource utilization.In this paper,we propose a task scheduler and exploit a Task Deployment Algorithm(TDA)to obtain an optimal virtual machine deployment scheme.Finally,the simulation results show that the TDA can significantly increase the resource utilization of the system,while redu-cing the average service response time of the application by comparing TDA with the other two classical methods.The experimental results confirm that the perfor-mance of TDA is better than that of other two methods.展开更多
基金supported by the National Natural Science Foundation of China(No.62102280)Fundamental Research Program of Shanxi Province(No.20210302124167)+1 种基金Key Research and Development Program of Shanxi Province(No.202102020101001)National Major Scientific Research Instrument Development Project of China(No.62027819).
文摘Working as aerial base stations,mobile robotic agents can be formed as a wireless robotic network to provide network services for on-ground mobile devices in a target area.Herein,a challenging issue is how to deploy these mobile robotic agents to provide network services with good quality for more users,while considering the mobility of on-ground devices.In this paper,to solve this issue,we decouple the coverage problem into the vertical dimension and the horizontal dimension without any loss of optimization and introduce the network coverage model with maximum coverage range.Then,we propose a hybrid deployment algorithm based on the improved quick artificial bee colony.The algorithm is composed of a centralized deployment algorithm and a distributed one.The proposed deployment algorithm deploy a given number of mobile robotic agents to provide network services for the on-ground devices that are independent and identically distributed.Simulation results have demonstrated that the proposed algorithm deploys agents appropriately to cover more ground area and provide better coverage uniformity.
基金supported by the National Natural Science Foundation of China under Grant No.62173126the National Natural Science Joint Fund project under Grant No.U1804162+2 种基金the Key Science and Technology Research Project of Henan Province under Grant No.222102210047,222102210200 and 222102320349the Key Scientific Research Project Plan of Henan Province Colleges and Universities under Grant No.22A520011 and 23A510018the Key Science and Technology Research Project of Anyang City under Grant No.2021C01GX017.
文摘Mobile Edge Computing(MEC)is proposed to solve the needs of Inter-net of Things(IoT)users for high resource utilization,high reliability and low latency of service requests.However,the backup virtual machine is idle when its primary virtual machine is running normally,which will waste resources.Overbooking the backup virtual machine under the above circumstances can effectively improve resource utilization.First,these virtual machines are deployed into slots randomly,and then some tasks with cooperative relationship are off-loaded to virtual machines for processing.Different deployment locations have different resource utilization and average service response time.We want tofind a balanced solution that minimizes the average service response time of the IoT application while maximizing resource utilization.In this paper,we propose a task scheduler and exploit a Task Deployment Algorithm(TDA)to obtain an optimal virtual machine deployment scheme.Finally,the simulation results show that the TDA can significantly increase the resource utilization of the system,while redu-cing the average service response time of the application by comparing TDA with the other two classical methods.The experimental results confirm that the perfor-mance of TDA is better than that of other two methods.
