# Joint Pricing, Server Orchestration and Network Slice Deployment in Mobile Edge Computing Networks  
[PERSON]  
1 School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China; [EMAIL_ADDRESS] (Y.H. ); [EMAIL_ADDRESS] (G.C. ); [EMAIL_ADDRESS] (W.G.) [PERSON]  
1 School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China; [EMAIL_ADDRESS] (Y.H. ); [EMAIL_ADDRESS] (G.C. ); [EMAIL_ADDRESS] (W.G.) [PERSON]  
1 School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China; [EMAIL_ADDRESS] (Y.H. ); [EMAIL_ADDRESS] (G.C. ); [EMAIL_ADDRESS] (W.G.) [PERSON]  
2 School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China; [EMAIL_ADDRESS] (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China; [EMAIL_ADDRESS] (Correspondence: [EMAIL_ADDRESS] 2025)14841  
slice, is formed [3]. Network slicing has become a key technology for efficiently managing diverse use cases. Recent studies have shown its effectiveness across various domains, including vehicular communication, industrial applications, and mission-critical services. For instance, ref. [4] proposed a network slicing solution for vehicular networks, effectively isolating traffic types such as safety messages and infotainment services. Ref. [5] described a network architecture framework based on network slicing that provides high service quality for data-intensive mission critical tasks. Ref. [6] explored the dynamic resource allocation of network slicing for ultra reliable and low-latency communication and enhanced mobile broadband services. In practical applications, the authors of [7] conducted an experiment at the Hamburg Seaport, demonstrating how network slicing can provide tailored services for various applications. These works highlight the importance of network slicing in meeting the diverse and demanding requirements of modern networks. In MEC networks, MEC servers often have limited computational and storage resources compared with cloud servers [8]. Introducing network slicing technology allows for a more efficient allocation of resources. Each slice can request edge resources and perform targeted optimization, enhancing resource utilization. Moreover, edge resources can be managed through software-defined methods without adding additional hardware deployment. This reduces hardware construction and maintenance costs while increasing network flexibility. Therefore, integrating MEC and network slicing technologies will improve resource utilization, offer personalized services and enhance the configurability of the MEC network. In such integrated wireless networks, the orchestration of MEC servers, the deployment network slices and the pricing schemes all have an impact on network performance. In the following, we will discuss these issues in detail and analyze their interrelationships. The orchestration of MEC servers involves planning their locations and managing their association with base stations, both of which are critical elements in MEC networks. Because the geographic distribution of services may change over time, the dynamic server placement is desirable. However, the migration of servers will incur unavoidable labor costs and service disruptions [9], which are often ignored in previous studies [10; 11; 12; 13]. Transforming the MEC server location optimization problem into a server activation problem is proposed in [8; 14], where the locations of MEC servers are fixed but the servers to be activated need to be determined. This would not only avoid the frequent migration of servers but also allow for dynamic change of the number of servers based on demand. Accordingly, we will address the MEC server activation problem in this paper. With the help of software-defined networking (SDN) and NFV, network slicing can provide customized VNF chains [15].