论文部分内容阅读
To address the issues that middleboxes as a fundamental part of today’s networks are facing, Network Function Virtualization(NFV)has been recently proposed, which in essence asserts to migrate hardware-based middleboxes into software-based virtualized function entities.Due to the demands of virtual services placement in NFV network environment, this paper models the service amount placement problem involving with the resources allocation as a cooperative game and proposes the placement policy by Nash Bargaining Solution(NBS). Specifically,we first introduce the system overview and apply the rigorous cooperative game-theoretic guide to build the mathematical model, which can give consideration to both the responding efficiency of service requirements and the allocation fairness.Then a distributed algorithm corresponding to NBS is designed to achieve predictable network performance for virtual instances placement.Finally, with simulations under various scenarios,the results show that our placement approach can achieve high utilization of network through the analysis of evaluation metrics namely the satisfaction degree and fairness index. With the suitable demand amount of services, the average values of two metrics can reach above 90%. And by tuning the base placement, our solution can enable operators to flexibly balance the tradeoff between satisfaction and fairness of resourcessharing in service platforms.
To address the issues that middleboxes as a fundamental part of today’s networks are facing, Network Function Virtualization (NFV) has been recently proposed, which in essence asserts to migrate hardware-based middleboxes into software-based virtualized function entities. Subject to demands virtual services placement in NFV network environment, this paper models the service amount placement problem involving with the resources allocation as a cooperative game and viage the placement policy by Nash Bargaining Solution (NBS). Specifically, we first introduce the system overview and apply the rigorous cooperative game-theoretic guide to build the mathematical model, which can give consideration to both the responding efficiency of service requirements and the allocation fairness.Then a distributed algorithm corresponding to NBS is designed to achieve predictable network performance for virtual instances placement .Finally, with simulations under various scenarios, the results show that our placement approach can achieve high utilization of network through the analysis of evaluation metrics that the degree and fairness index. With the suitable demand amount of services, the average values of two metrics can reach above 90%. And by tuning the base placement, our solution can enable operators to flexibly balance the tradeoff between satisfaction and fairness of resourcessharing in service platforms.