# Joint Pricing, Server Orchestration and Network Slice Deployment in Mobile Edge Computing Networks
In the MEC network, VNF chains can be deployed on edge servers based on factors such as delay demand and users' locations [16]. Optimizing the VNF chain deployment can improve resource utilization and reduce network operating costs. In addition to the VNF chains deployed on MEC servers, the access functions of the base station can also be virtualized as VNFs, which are responsible for user access control, signal transmission and reception, data forwarding, radio resource management, etc. Unlike the deployment of VNF chains on edge servers, the deployment of access functions on base stations directly affects the geographical coverage of slices. Providing full coverage for all network slices may lead to cost inefficiencies. Therefore, in the MEC network, slice deployment needs to consider both the deployment of VNF chains on edge servers and the deployment of access functions on base stations [17]. However, most studies have neglected the deployment of access functions [8; 14; 18]. In addition, while addressing the slice deployment problem, it also requires the allocation schemes for radio, computational and storage resources. Tenants are entities or organizations that use specific network slices, such as individuals, enterprises, and government agencies [3]. Tenants can submit requests to the InP to create slices based on the demand of theirs subscribers. In response, the InP virtualizes the corresponding network slice and selects network nodes for its deployment. Then, the InP is responsible for the installation, configuration, and ongoing maintenance of the slices. Consequently, the InP charges the tenant for both deployment costs and resource costs [17; 19]. The tenant needs to provide services to its users through the network slice and guarantee their QoS requirements. Additionally, the tenant expects to reduce the fees paid to the InP. These two objectives can be achieved by optimizing the orchestration of MEC servers, the deployment of slices and the resource allocation strategies, which were addressed in our previous work [20]. Because the InP needs to bear the construction and maintenance costs of servers [10], the utility of the InP is influenced by the fees paid by tenants and the number of active services. Generally, higher income and fewer servers result in greater utility for the InP. Additionally, the InP's income is affected by pricing schemes. Specifically, low prices may lead to lower revenue, while high prices may discourage tenants from deploying more access functions and VNF chains as well as renting more resources. Therefore, the InP not only needs to optimize MEC server orchestration to reduce costs, but also needs to optimize the prices of resource and deployment to improve income, which was not considered in our previous work [20]. The previous analysis revealed that the pricing strategy affects the network slice deployment strategy. In addition, only if the MEC server is associated with the base station on which the access function of a slice is deployed can the VNF chain associated with the slice be deployed on the server. Thus, the server orchestration, VNF chain deployment, access function deployment and pricing strategy are coupled with each other and need to be considered simultaneously. However, previous studies failed to address this joint problem and instead only focused on one or two aspects [8; 9; 10; 11; 12; 13; 14; 17; 18]. Accordingly, we jointly address the issues of pricing, server orchestration and network slice deployment in this paper. Specifically, the considered system is divided into the InP layer (IPL), network planning layer (NPL) and resource allocation layer (RAL). The IPL achieves the goal of maximizing the average revenue generated by each activated server through pricing optimization. The NPL is responsible for optimizing the server activation and slice deployment, while the RAL is in charge of optimizing the radio, computational and storage resource allocation.