Softwarization of networks allows simplifying deployment, configuration and management of network functions. The driving force towards this evolution is represented by Software Defined Networking (SDN) that allows more flexible and dynamic network resource allocation and management. Efficient resource allocation and orchestration are two primary targets of this softwarization process; however, centralized methodologies result complex, and exhibit scalability issues. So, distributed solutions are to be preferred but, in order to be effective, should quickly converge towards equilibrium solutions. In this paper, we focus on making distributed resource allocation and orchestration a viable approach, and prove convergence of the relevant mechanisms. Specifically, we exploit game theory to model interactions between users requesting network functions and servers providing these functions. Accordingly, a two-stage Stackelberg game is presented where servers act as leaders of the game and users as followers. Servers have conflicting interests and try to maximize their utility; users, on the other hand, use a replicator behavior and try to imitate other users decisions to improve their benefit. The framework proves the existence and uniqueness of an equilibrium, and a learning mechanism to converge to such equilibrium is proposed. Numerical results show the effectiveness of the approach.
|Titolo:||A Game Theoretic Approach for Distributed Resource Allocation and Orchestration of Softwarized Networks|
|Data di pubblicazione:||2017|
|Appare nelle tipologie:||1.1 Articolo in rivista|