The problem of cloud cooperation of military service providers(MSPs) is addressed for allocating limited resources to military service users(MSUs) that are geographically distributed. The MSPs, also called militar...The problem of cloud cooperation of military service providers(MSPs) is addressed for allocating limited resources to military service users(MSUs) that are geographically distributed. The MSPs, also called military organization clouds, are virtualized and encapsulated by the services they can offer and each of them contains different kinds of resources that MSU needs. The MSPs are also geographically dispersed. They are required to allocate their resources to the MSU complying with the corresponding quality of service(QoS), so that each MSU gathers the services it needs to guarantee its task to be implemented. The outline of military organization cloud cooperation is discussed and the method of service optimal selection is proposed based on QoS evaluation. The QoS evaluation method based on exponential approximation is put forward to include the users' will. Simulation results verify the effectiveness of the proposed algorithm.展开更多
Nowadays,emergency accidents could happen at any time.The accidents occur unpredictably and the accidents requirements are diversely.The accidents happen in a dynamic environment and the resource should be cooperative...Nowadays,emergency accidents could happen at any time.The accidents occur unpredictably and the accidents requirements are diversely.The accidents happen in a dynamic environment and the resource should be cooperative to solve the accidents.Most methods are focusing on minimizing the casualties and property losses in a static environment.However,they are lack in considering the dynamic and unpredictable event handling.In this paper,we propose a representative environmental model in representation of emergency and dynamic resource allocation model,and an adaptive mathematical model based on Genetic Algorithm(GA)to generate an optimal set of solution domain.The experimental results show that the proposed algorithm can get a set of better candidate solutions.展开更多
This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s...This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.展开更多
基金supported by the National Natural Science Foundation of China(61573283)the National Basic Research Program of China(973 Program)(2010CB734104)
文摘The problem of cloud cooperation of military service providers(MSPs) is addressed for allocating limited resources to military service users(MSUs) that are geographically distributed. The MSPs, also called military organization clouds, are virtualized and encapsulated by the services they can offer and each of them contains different kinds of resources that MSU needs. The MSPs are also geographically dispersed. They are required to allocate their resources to the MSU complying with the corresponding quality of service(QoS), so that each MSU gathers the services it needs to guarantee its task to be implemented. The outline of military organization cloud cooperation is discussed and the method of service optimal selection is proposed based on QoS evaluation. The QoS evaluation method based on exponential approximation is put forward to include the users' will. Simulation results verify the effectiveness of the proposed algorithm.
基金This work is supported by the National Science Foundation of China under Grant No.F020803,and No.61602254the National Science Foundation of Jiangsu Province,China,under Grant No.BK20160968the Project through the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions,the China-USA Computer Science Research Center.
文摘Nowadays,emergency accidents could happen at any time.The accidents occur unpredictably and the accidents requirements are diversely.The accidents happen in a dynamic environment and the resource should be cooperative to solve the accidents.Most methods are focusing on minimizing the casualties and property losses in a static environment.However,they are lack in considering the dynamic and unpredictable event handling.In this paper,we propose a representative environmental model in representation of emergency and dynamic resource allocation model,and an adaptive mathematical model based on Genetic Algorithm(GA)to generate an optimal set of solution domain.The experimental results show that the proposed algorithm can get a set of better candidate solutions.
基金supported by National Natural Science Foundation of China (No.60972059)Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions+3 种基金Fundamental Research Funds for the Central Universities of China (No.2010QNA27)China Postdoctoral Science Foundation(No.20100481185)Postdoctoral Research Funds of Jiangsu Province(No.1101108C)Postdoctoral Fellowship Program of the China Scholarship Council
文摘This paper proposes a bargaining game theoretic resource(including the subcarrier and the power) allocation scheme for wireless orthogonal frequency division multiple access(OFDMA) networks.We define a wireless user s payoff as a function of the achieved data-rate.The fairness resource allocation problem can then be modeled as a cooperative bargaining game.The objective of the game is to maximize the aggregate payoffs for the users.To search for the Nash bargaining solution(NBS) of the game,a suboptimal subcarrier allocation is performed by assuming an equal power allocation.Thereafter,an optimal power allocation is performed to maximize the sum payoff for the users.By comparing with the max-rate and the max-min algorithms,simulation results show that the proposed game could achieve a good tradeoff between the user fairness and the overall system performance.