چكيده به لاتين
As the next generation of communications will be driven by the 5G network and the main reason for its development is to support new and different services based on user needs, so network operators should be able to group based on users Based on their specific needs, provide the expected service with maximum efficiency and minimum cost. The tool that has been proposed to accomplish this is the use of network slicing.
One of the most important challenges in network slicing is the issue of resource allocation among the business roles within the 5G network. Accordingly, the problem is defined as how to properly adapt network slices to the resources they need to provide the service or services their users want, so that both the operators and the network providers get the most benefit and the users. Slices receive the services they need appropriately. Related work only seeks to maximize the profitability of centralized network providers, as opposed to the primary goal of 5G, providing quality service, taking into account the needs of users of slices, while realistic constraints on resource efficiency, fairness, prioritization of business roles, and support for critical SLAs in None of these tasks have been seen as resource allocation, so to address this challenge, provide a resource allocation approach in the domain of well-known game-based core network slicing. Stackelberg is recommended to be able to allocate resources appropriately across the network for each slice so that both users, network providers, and tenants gain the most benefit simultaneously, and realistic constraints on resource efficiency, fairness, priority, critical SLAs Support among slices and tenants. Despite these realistic constraints, for the flexibility and scalability of the proposed solution algorithm for the proposed method, the problem fits into one of the lucrative games of game theory under the name of Stackelberg. By adapting the proposed approach to the Stackelberg game, a solution algorithm is proposed that can allocate the required resources in a distributed way and utilize the equilibrium of Stackelberg method to create the best equilibrium among users, tenants and network providers. According to the simulations, the proposed algorithm is able to improve the average utility of the community by 10.45% by obtaining the best equilibrium.
