# A Framework for the Joint Placement of Edge Service Infrastructure and User Plane Functions for 5G
## 1 Introduction  
5G-identified use cases and stringent technical requirements [1] are forcing a deep evolution of current communication technologies and paradigms. Network Function Virtualization (NFV), Edge Computing (EC) and Software Defined Networks (SDNs), just to mention a few examples, are driving radical technological changes that span across all 5G layers. Among these revolutionary proposals, EC [2, 3] has become the solution to upcoming ultra-low latency communication requirements (e.g., real-time services, virtual and augmented reality, etc.). Future ultra-high bandwidth use cases and envisioned service trends under 5G networks will lead to unprecedented demands for hyper/connectivity and ultra-reliable high performance. As a result, a decentralized architecture of geo-distributed computing nodes has emerged as the only feasible deployment scheme to ensure end-user demand satisfaction. However, due to the distributed nature and the expected large number of edge nodes (ENs) in a 5G and EC ecosystem (where storage, computing and networking resources are brought to the network edge), capital and operational expenditures (CAPEX and OPEX) have become critical challenges. 5G networks must be able to provide diverse services with different requirements. For instance, services under the ultra-reliable and low-latency communication (uRLLC) category require high reliability and low response time whereas others belonging to the enhanced mobile broadband (eMBB) class need high bandwidth and processing capacity. Thus, flexible and customizable deployment of the required User Plane Functions (UPFs) is necessary. Concretely, latency and reliability stringentrequirements can be satisfied by placing UPF's closer to the end-users and assigning more than one UPF to the access nodes. However, this kind of approach implies an increase in the number of UPF's by a factor of 20 to 30 times the original amount [4]. A higher number of UPF's will not only increase the costs but also the occurrence of UPF's relocations, mainly conditioned by users mobility and handover procedures in mobile networks. Relocations in the UPF's occur when a user equipment (UE) with an active Protocol Data Unit (PDU) session, registers in a base station (BS) that is served by a UPF different from the one linked to its source BS. Frequent relocations can affect the overall Quality of Experience (QoE) by introducing additional delays during handovers and signaling overhead for bearer establishment [5]. Therefore, the design of effective UPF's placement strategies, capable of meeting the service requirements and minimizing the costs without degrading QoE is of utmost importance. In this context, a core approach to reduce CAPEX/OPEX is the joint optimization of the EN and UPF's placement strategies. A solution to this problem can exponentially increase overall deployment and operation cost savings, while effectively guaranteeing 5G service requirement satisfaction. Solving this problem is challenging due to the numerous trade-offs involved. For instance: (a) only minimizing the number of EN's and UPF's, results in performance degradation and unsatisfied end-user demands, (b) the inter-dependence between EN's and location-dependent costs leads to unmet requirement scenarios due to service demand variation and unexpected events (e.g., emergencies, disaster situations), (c) through the use of current in-use sites (e.g., Internet Exchange Points, IX's) significant cost reductions can be achieved, however, if the forecasted demand does not follow the expected path, it may be better to choose other locations closer to the user demand in spite of its lack of \(\Pi\) capabilities, as it would considerably decrease the expenses over time. Given this situation, this paper proposes a framework for a cost-effective deployment of both the edge service infrastructure and the required UPF's to guarantee overall cost minimization and service demand satisfaction.