The emergence of multi-access edge computing(MEC)aims at extending cloud computing capabilities to the edge of the radio access network.As the large-scale internet of things(IoT)services are rapidly growing,a single e...The emergence of multi-access edge computing(MEC)aims at extending cloud computing capabilities to the edge of the radio access network.As the large-scale internet of things(IoT)services are rapidly growing,a single edge infrastructure provider(EIP)may not be sufficient to handle the data traffic generated by these services.Most of the existing work addressed the computing resource shortage problem by optimizing tasks schedule,whereas others overcome such issue by placing computing resources on demand.However,when considering a multiple EIPs scenario,an urgent challenge is how to generate a coalition structure to maximize each EIP’s gain with a suitable price for computing resource block corresponding to a container.To this end,we design a scheme of EIPs collaboration with a market price for containers under a scenario that considers a collection of service providers(SPs)with different budgets and several EIPs distributed in geographical locations.First,we bring in the net profit market price model to generate a more reasonable equilibrium price and select the optimal EIPs for each SP by a convex program.Then we use a mathematical model to maximize EIP’s profits and form stable coalitions between EIPs by a distributed coalition formation algorithm.Numerical results demonstrate that our proposed collaborative scheme among EIPs enhances EIPs’gain and increases users’surplus.展开更多
The airspace congestion is becoming more and more severe.Although there are traffic flow management（TFM）initiatives based on CDM widely applied,how to reschedule these disrupted flights of different airlines integra...The airspace congestion is becoming more and more severe.Although there are traffic flow management（TFM）initiatives based on CDM widely applied,how to reschedule these disrupted flights of different airlines integrating TFM initiatives and allocate the limited airspace resources to these airlines equitably and efficiently is still a problem.The air traffic management（ATM）authority aims to minimizing the systemic costs of congested airspaces.And the airlines are self-interested and profit-oriented.Being incorporated into the collaborative decision making（CDM）process,the airlines can influence the rescheduling decisions to profit themselves.The airlines maybe hide the flight information that is disadvantageous to them,but is necessary to the optimal system decision.To realize the coincidence goal between the ATM authority and airlines for the efficient,and equitable allocation of airspace resources,this paper provides an auction-based market method to solve the congestion airspace problem under the pre-tactic and tactic stage of air traffic flow management.Through a simulation experiment,the rationing results show that the auction method can decrease the total delay costs of flights in the congested airspace compared with both the first schedule first service（FSFS）tactic and the ration by schedule（RBS）tactic.Finally,the analysis results indicate that if reallocate the charges from the auction to the airlines according to the proportion of their disrupted flights,the auction mechanism can allocate the airspace resource in economy equitably and decrease the delay losses of the airlines compared with the results of the FSFS tactic.展开更多
The satellite-terrestrial cooperative network is considered an emerging network architecture,which can adapt to various services and applications in the future communication network.In recent years,the combination of ...The satellite-terrestrial cooperative network is considered an emerging network architecture,which can adapt to various services and applications in the future communication network.In recent years,the combination of satellite communication and Mobile Edge Computing(MEC)has become an emerging research hotspot.Satellite edge computing can provide users with full coverage on-orbit computing services by deploying MEC servers on satellites.This paper studies the task offloading of multi-user and multi-edge computing satellites and proposes a novel algorithm that joint task offloading and communication computing resource optimization(JTO-CCRO).The JTO-CCRO is decoupled into task offloading and resource allocation sub-problems.After the mutual iteration of the two sub-problems,the system utility function can be further reduced.For the task offloading sub-problem,it is first confirmed that the offloading problem is a game problem.The offloading strategy can be obtained from the Nash equilibrium solution.We confirm resource optimization sub-problem is a convex optimization problem that can be solved by the Lagrange multiplier method.Simulation shows that the JTO-CCRO algorithm can converge quickly and effectively reduce the system utility function.展开更多
In this paper, we investigate the link resource management problem for optical networks, to achieve the resource cost during the information transmission. We use the differential game to formulate the cost control pro...In this paper, we investigate the link resource management problem for optical networks, to achieve the resource cost during the information transmission. We use the differential game to formulate the cost control problem for the link resource management, to minimize the resource allocation cost functions, which dynamic behaviours are described by differential equations. Each link controls its transmission bandwidth based on the Nash equilibriums of the differential game. The effectiveness of the proposed model is given through numerical simulations.展开更多
In this paper, we propose a non-cooperative differential game theory based resource allocation approach for the network security risk assessment. For the risk assessment, the resource will be used for risk assess, inc...In this paper, we propose a non-cooperative differential game theory based resource allocation approach for the network security risk assessment. For the risk assessment, the resource will be used for risk assess, including response cost and response negative cost. The whole assessment process is considered as a differential game for optimal resource control. The proposed scheme can be obtained through the Nash Equilibrium. It is proved that the game theory based algorithm is applicable and the optimal resource level can be achieved based on the proposed algorithm.展开更多
基金supported by National Natural Science Foundation of China(No.6206020135)Key Research and Development Program of Gansu Province(No.20YF8GA123)+1 种基金Gansu Provincial Department of Education University Faculty Innovation Fund Project(No.2024B-059)Youth Science Fund Project of Lanzhou Jiaotong University(No.1200061307).
文摘The emergence of multi-access edge computing(MEC)aims at extending cloud computing capabilities to the edge of the radio access network.As the large-scale internet of things(IoT)services are rapidly growing,a single edge infrastructure provider(EIP)may not be sufficient to handle the data traffic generated by these services.Most of the existing work addressed the computing resource shortage problem by optimizing tasks schedule,whereas others overcome such issue by placing computing resources on demand.However,when considering a multiple EIPs scenario,an urgent challenge is how to generate a coalition structure to maximize each EIP’s gain with a suitable price for computing resource block corresponding to a container.To this end,we design a scheme of EIPs collaboration with a market price for containers under a scenario that considers a collection of service providers(SPs)with different budgets and several EIPs distributed in geographical locations.First,we bring in the net profit market price model to generate a more reasonable equilibrium price and select the optimal EIPs for each SP by a convex program.Then we use a mathematical model to maximize EIP’s profits and form stable coalitions between EIPs by a distributed coalition formation algorithm.Numerical results demonstrate that our proposed collaborative scheme among EIPs enhances EIPs’gain and increases users’surplus.
基金Supported by the National High Technology Research and Development Program of China("863"Program)(20060AA12A105)the Chinese Airspace Management Commission Researching Program(GKG200802006)~~
文摘The airspace congestion is becoming more and more severe.Although there are traffic flow management（TFM）initiatives based on CDM widely applied,how to reschedule these disrupted flights of different airlines integrating TFM initiatives and allocate the limited airspace resources to these airlines equitably and efficiently is still a problem.The air traffic management（ATM）authority aims to minimizing the systemic costs of congested airspaces.And the airlines are self-interested and profit-oriented.Being incorporated into the collaborative decision making（CDM）process,the airlines can influence the rescheduling decisions to profit themselves.The airlines maybe hide the flight information that is disadvantageous to them,but is necessary to the optimal system decision.To realize the coincidence goal between the ATM authority and airlines for the efficient,and equitable allocation of airspace resources,this paper provides an auction-based market method to solve the congestion airspace problem under the pre-tactic and tactic stage of air traffic flow management.Through a simulation experiment,the rationing results show that the auction method can decrease the total delay costs of flights in the congested airspace compared with both the first schedule first service（FSFS）tactic and the ration by schedule（RBS）tactic.Finally,the analysis results indicate that if reallocate the charges from the auction to the airlines according to the proportion of their disrupted flights,the auction mechanism can allocate the airspace resource in economy equitably and decrease the delay losses of the airlines compared with the results of the FSFS tactic.
基金supported by the National Key Research and Development Program of China under Grant 2021YFB2900500the Natural Science Foundation for Outstanding Young Scholars of Heilongjiang Province under Grant YQ2020F001the Fundamental Research Funds for the Central Universities under Grant FRFCU 9803503821.
文摘The satellite-terrestrial cooperative network is considered an emerging network architecture,which can adapt to various services and applications in the future communication network.In recent years,the combination of satellite communication and Mobile Edge Computing(MEC)has become an emerging research hotspot.Satellite edge computing can provide users with full coverage on-orbit computing services by deploying MEC servers on satellites.This paper studies the task offloading of multi-user and multi-edge computing satellites and proposes a novel algorithm that joint task offloading and communication computing resource optimization(JTO-CCRO).The JTO-CCRO is decoupled into task offloading and resource allocation sub-problems.After the mutual iteration of the two sub-problems,the system utility function can be further reduced.For the task offloading sub-problem,it is first confirmed that the offloading problem is a game problem.The offloading strategy can be obtained from the Nash equilibrium solution.We confirm resource optimization sub-problem is a convex optimization problem that can be solved by the Lagrange multiplier method.Simulation shows that the JTO-CCRO algorithm can converge quickly and effectively reduce the system utility function.
基金supported by National Science Foundation Project of P. R. China (No.61501026,U1603116)the Fundamental Research Funds for the Central Universities (No.FRF-TP-15-032A1)
文摘In this paper, we investigate the link resource management problem for optical networks, to achieve the resource cost during the information transmission. We use the differential game to formulate the cost control problem for the link resource management, to minimize the resource allocation cost functions, which dynamic behaviours are described by differential equations. Each link controls its transmission bandwidth based on the Nash equilibriums of the differential game. The effectiveness of the proposed model is given through numerical simulations.
基金supported by the China Postdoctoral Science Foundation(No.2015M570936)National Science Foundation Project of P.R.China(No.61501026,61272506)Fundamental Research Funds for the Central Universities(No.FRF-TP-15032A1)
文摘In this paper, we propose a non-cooperative differential game theory based resource allocation approach for the network security risk assessment. For the risk assessment, the resource will be used for risk assess, including response cost and response negative cost. The whole assessment process is considered as a differential game for optimal resource control. The proposed scheme can be obtained through the Nash Equilibrium. It is proved that the game theory based algorithm is applicable and the optimal resource level can be achieved based on the proposed algorithm.
