To satisfy mobile terminals ’( MTs) offloading requirements and reduce MTs’ cost,a joint cloud and wireless resource allocation scheme based on the evolutionary game( JRA-EG) is proposed for overlapping heterogeneou...To satisfy mobile terminals ’( MTs) offloading requirements and reduce MTs’ cost,a joint cloud and wireless resource allocation scheme based on the evolutionary game( JRA-EG) is proposed for overlapping heterogeneous networks in mobile edge computing environments. MTs that have tasks offloading requirements in the same service area form a population. MTs in one population acquire different wireless and computation resources by selecting different service providers( SPs). An evolutionary game is formulated to model the SP selection and resource allocation of the MTs. The cost function of the game consists of energy consumption,time delay and monetary cost. The solutions of evolutionary equilibrium( EE) include the centralized algorithm based on replicator dynamics and the distributed algorithm based on Q-learning.Simulation results show that both algorithms can converge to the EE rapidly. The differences between them are the convergence speed and trajectory stability. Compared with the existing schemes,the JRA-EG scheme can save more energy and have a smaller time delay when the data size becomes larger. The proposed scheme can schedule the wireless and computation resources reasonably so that the offloading cost is reduced efficiently.展开更多
A cross-layer resource allocation scheme based on potential game(CLRA_ PG) is proposed for the downlink multi-cell orthogonal frequency-division multiple-access(OFDMA) system with universal frequency reuse.As a method...A cross-layer resource allocation scheme based on potential game(CLRA_ PG) is proposed for the downlink multi-cell orthogonal frequency-division multiple-access(OFDMA) system with universal frequency reuse.As a method to mitigate inter-cell interference(ICI),base station coordination has been considered.In the process of the objective function modeling,this paper adopts a pricing mechanism which not only maximizes the individual utility but also considers the interference to other users.Based on the potential game theory,the objective problem is converted to a potential function which can be easily solved.The Karush-Kuhn-Tucker(KKT) conditions and the iterative water-filling algorithm are employed to solve the constraint objective optimization problem.Moreover,extensive simulations are conducted to evaluate how the pricing factors affect the algorithm.At the same time,comparing with the traditional policy,our simulation results show that the proposed scheme can significantly improve the performance of the system.展开更多
In this paper, we study the virtual resource(VR) allocation problem in LTE-based wireless network virtualization(WNV). A practical network scenario, where multiple virtual wireless service providers(WSPs)request the V...In this paper, we study the virtual resource(VR) allocation problem in LTE-based wireless network virtualization(WNV). A practical network scenario, where multiple virtual wireless service providers(WSPs)request the VR from a unique mobile network operator(MNO) is considered. Our objective is two folds. The first is to guarantee the minimum rate requirements of the MNO and the WSPs. The second is to distribute the system rate among the MNO and the WSPs in the Pareto optimal manner. To this end, an efficient VR allocation scheme based on bargaining game theory is proposed, and the Nash bargaining solution(NBS) method is used to solve the proposed game problem. The proposed game problem is proved to be a convex optimization problem. By using standard convex optimization method, the global optimal NBS of the game is obtained in closed form. The effectiveness of the proposed VR allocation game is testified through numerical results.展开更多
基金The National Natural Science Foundation of China(No.61741102,61471164)
文摘To satisfy mobile terminals ’( MTs) offloading requirements and reduce MTs’ cost,a joint cloud and wireless resource allocation scheme based on the evolutionary game( JRA-EG) is proposed for overlapping heterogeneous networks in mobile edge computing environments. MTs that have tasks offloading requirements in the same service area form a population. MTs in one population acquire different wireless and computation resources by selecting different service providers( SPs). An evolutionary game is formulated to model the SP selection and resource allocation of the MTs. The cost function of the game consists of energy consumption,time delay and monetary cost. The solutions of evolutionary equilibrium( EE) include the centralized algorithm based on replicator dynamics and the distributed algorithm based on Q-learning.Simulation results show that both algorithms can converge to the EE rapidly. The differences between them are the convergence speed and trajectory stability. Compared with the existing schemes,the JRA-EG scheme can save more energy and have a smaller time delay when the data size becomes larger. The proposed scheme can schedule the wireless and computation resources reasonably so that the offloading cost is reduced efficiently.
基金Supported by the National Key Technology R&D Program of China(No.2010ZX03003-001-01,2011 ZX03003-002-01)National Natural Science Foundation of China(No.61101109)the Co-building Project of Beijing Municipal Education Commission"G-RAN based Experimental Platform for Future Mobile Communications"
文摘A cross-layer resource allocation scheme based on potential game(CLRA_ PG) is proposed for the downlink multi-cell orthogonal frequency-division multiple-access(OFDMA) system with universal frequency reuse.As a method to mitigate inter-cell interference(ICI),base station coordination has been considered.In the process of the objective function modeling,this paper adopts a pricing mechanism which not only maximizes the individual utility but also considers the interference to other users.Based on the potential game theory,the objective problem is converted to a potential function which can be easily solved.The Karush-Kuhn-Tucker(KKT) conditions and the iterative water-filling algorithm are employed to solve the constraint objective optimization problem.Moreover,extensive simulations are conducted to evaluate how the pricing factors affect the algorithm.At the same time,comparing with the traditional policy,our simulation results show that the proposed scheme can significantly improve the performance of the system.
基金supported in part by China University of Mining and Technology Funds for Academic Frontier Research(Grant No.2015XKQY18)National High-tech R&D Program of China(863 Program)(Grant Nos.2015AA015701+1 种基金2015AA01A705)National Natural Science Foundation of China(Grant No.61100167)
文摘In this paper, we study the virtual resource(VR) allocation problem in LTE-based wireless network virtualization(WNV). A practical network scenario, where multiple virtual wireless service providers(WSPs)request the VR from a unique mobile network operator(MNO) is considered. Our objective is two folds. The first is to guarantee the minimum rate requirements of the MNO and the WSPs. The second is to distribute the system rate among the MNO and the WSPs in the Pareto optimal manner. To this end, an efficient VR allocation scheme based on bargaining game theory is proposed, and the Nash bargaining solution(NBS) method is used to solve the proposed game problem. The proposed game problem is proved to be a convex optimization problem. By using standard convex optimization method, the global optimal NBS of the game is obtained in closed form. The effectiveness of the proposed VR allocation game is testified through numerical results.
