Optimal placement of User Plane Functions in 5G networks

Because of developments in society and technology, new services and use cases have emerged, such as vehicle-to-everything communication and smart manufacturing. Some of these services have stringent requirements in terms of reliability, bandwidth, and network response time and to meet them, deploying network functions (NFs) closer to users is necessary. Doing so will lead to an increase in costs and the number of NFs. Under such circumstances, the use of optimization strategies for the placement of NFs is crucial to offer Quality of Service (QoS) in a cost-effective manner. In this vein, this paper addresses the User Plane Functions Placement (UPFP) problem in 5G networks. The UPFP is modeled as a Mixed-Integer Linear Programming (MILP) problem aimed at determining the optimal number and location of User Plane Functions (UPFs). Two optimization models are proposed that considered various parameters, such as latency, reliability and user mobility. To evaluate their performance, two services under the Ultra-Reliable an Low-Latency Communication (URLLC) category were selected. The acquired results showcase the effectiveness of our solutions.Postprint (author's final draft

Virtualized Local Core Network Functions Placement in Mobile Networks

International audienceA novel trend in mobile networks is to co-locate the base stations with virtualized core network functions, such as session management and routing. The goal is to lose the long-standing physical dependency between the radio access and the core network, and improve network resiliency. In this work, we focus on the placement of virtualized core functions within a network of multiple base stations interconnected via a potentially limited backhaul. Since all data and signaling traffic are exchanged on the links interconnecting the base stations, the placement of these functions deeply impacts the backhaul load. We compare centralized and distributed placement strategies, with respect to the overall backhaul bandwidth consumption. Results show that distributing instances of the core functions (e.g., routing) in the network is significantly less costly from a backhaul point of view, and can economize backhaul consumption by 86%

A framework for the joint placement of edge service infrastructure and User Plane Functions for 5G

Achieving less than 1 ms end-to-end communication latency, required for certain 5G services and use cases, is imposing severe technical challenges for the deployment of next-generation networks. To achieve such an ambitious goal, the service infrastructure and User Plane Function (UPF) placement at the network edge, is mandatory. However, this solution implies a substantial increase in deployment and operational costs. To cost-effectively solve this joint placement problem, this paper introduces a framework to jointly address the placement of edge nodes (ENs) and UPFs. Our framework proposal relies on Integer Linear Programming (ILP) and heuristic solutions. The main objective is to determine the ENs and UPFs’ optimal number and locations to minimize overall costs while satisfying the service requirements. To this aim, several parameters and factors are considered, such as capacity, latency, costs and site restrictions. The proposed solutions are evaluated based on different metrics and the obtained results showcase over 20% cost savings for the service infrastructure deployment. Moreover, the gap between the UPF placement heuristic and the optimal solution is equal to only one UPF in the worst cases, and a computation time reduction of over 35% is achieved in all the use cases studied.Postprint (author's final draft

Gateway Relocation Avoidance-Aware Network Function Placement in Carrier Cloud

International audienc

Edge computing infrastructure for 5G networks: a placement optimization solution

This thesis focuses on how to optimize the placement of the Edge Computing infrastructure for upcoming 5G networks. To this aim, the core contributions of this research are twofold: 1) a novel heuristic called Hybrid Simulated Annealing to tackle the NP-hard nature of the problem and, 2) a framework called EdgeON providing a practical tool for real-life deployment optimization. In more detail, Edge Computing has grown into a key solution to 5G latency, reliability and scalability requirements. By bringing computing, storage and networking resources to the edge of the network, delay-sensitive applications, location-aware systems and upcoming real-time services leverage the benefits of a reduced physical and logical path between the end-user and the data or service host. Nevertheless, the edge node placement problem raises critical concerns regarding deployment and operational expenditures (i.e., mainly due to the number of nodes to be deployed), current backhaul network capabilities and non-technical placement limitations. Common approaches to the placement of edge nodes are based on: Mobile Edge Computing (MEC), where the processing capabilities are deployed at the Radio Access Network nodes and Facility Location Problem variations, where a simplistic cost function is used to determine where to optimally place the infrastructure. However, these methods typically lack the flexibility to be used for edge node placement under the strict technical requirements identified for 5G networks. They fail to place resources at the network edge for 5G ultra-dense networking environments in a network-aware manner. This doctoral thesis focuses on rigorously defining the Edge Node Placement Problem (ENPP) for 5G use cases and proposes a novel framework called EdgeON aiming at reducing the overall expenses when deploying and operating an Edge Computing network, taking into account the usage and characteristics of the in-place backhaul network and the strict requirements of a 5G-EC ecosystem. The developed framework implements several placement and optimization strategies thoroughly assessing its suitability to solve the network-aware ENPP. The core of the framework is an in-house developed heuristic called Hybrid Simulated Annealing (HSA), seeking to address the high complexity of the ENPP while avoiding the non-convergent behavior of other traditional heuristics (i.e., when applied to similar problems). The findings of this work validate our approach to solve the network-aware ENPP, the effectiveness of the heuristic proposed and the overall applicability of EdgeON. Thorough performance evaluations were conducted on the core placement solutions implemented revealing the superiority of HSA when compared to widely used heuristics and common edge placement approaches (i.e., a MEC-based strategy). Furthermore, the practicality of EdgeON was tested through two main case studies placing services and virtual network functions over the previously optimally placed edge nodes. Overall, our proposal is an easy-to-use, effective and fully extensible tool that can be used by operators seeking to optimize the placement of computing, storage and networking infrastructure at the users’ vicinity. Therefore, our main contributions not only set strong foundations towards a cost-effective deployment and operation of an Edge Computing network, but directly impact the feasibility of upcoming 5G services/use cases and the extensive existing research regarding the placement of services and even network service chains at the edge

Integração do paradigma de cloud computing com a infraestrutura de rede do operador

Doutoramento em Engenharia InformáticaThe proliferation of Internet access allows that users have the possibility to use services available directly through the Internet, which translates in a change of the paradigm of using applications and in the way of communicating, popularizing in this way the so-called cloud computing paradigm. Cloud computing brings with it requirements at two different levels: at the cloud level, usually relying in centralized data centers, where information technology and network resources must be able to guarantee the demand of such services; and at the access level, i.e., depending on the service being consumed, different quality of service is required in the access network, which is a Network Operator (NO) domain. In summary, there is an obvious network dependency. However, the network has been playing a relatively minor role, mostly as a provider of (best-effort) connectivity within the cloud and in the access network. The work developed in this Thesis enables for the effective integration of cloud and NO domains, allowing the required network support for cloud. We propose a framework and a set of associated mechanisms for the integrated management and control of cloud computing and NO domains to provide endto- end services. Moreover, we elaborate a thorough study on the embedding of virtual resources in this integrated environment. The study focuses on maximizing the host of virtual resources on the physical infrastructure through optimal embedding strategies (considering the initial allocation of resources as well as adaptations through time), while at the same time minimizing the costs associated to energy consumption, in single and multiple domains. Furthermore, we explore how the NO can take advantage of the integrated environment to host traditional network functions. In this sense, we study how virtual network Service Functions (SFs) should be modelled and managed in a cloud environment and enhance the framework accordingly. A thorough evaluation of the proposed solutions was performed in the scope of this Thesis, assessing their benefits. We implemented proof of concepts to prove the added value, feasibility and easy deployment characteristics of the proposed framework. Furthermore, the embedding strategies evaluation has been performed through simulation and Integer Linear Programming (ILP) solving tools, and it showed that it is possible to reduce the physical infrastructure energy consumption without jeopardizing the virtual resources acceptance. This fact can be further increased by allowing virtual resource adaptation through time. However, one should have in mind the costs associated to adaptation processes. The costs can be minimized, but the virtual resource acceptance can be also reduced. This tradeoff has also been subject of the work in this Thesis.A proliferação do acesso à Internet permite aos utilizadores usar serviços disponibilizados diretamente através da Internet, o que se traduz numa mudança de paradigma na forma de usar aplicações e na forma de comunicar, popularizando desta forma o conceito denominado de cloud computing. Cloud computing traz consigo requisitos a dois níveis: ao nível da própria cloud, geralmente dependente de centros de dados centralizados, onde as tecnologias de informação e recursos de rede têm que ser capazes de garantir as exigências destes serviços; e ao nível do acesso, ou seja, dependendo do serviço que esteja a ser consumido, são necessários diferentes níveis de qualidade de serviço na rede de acesso, um domínio do operador de rede. Em síntese, existe uma clara dependência da cloud na rede. No entanto, o papel que a rede tem vindo a desempenhar neste âmbito é reduzido, sendo principalmente um fornecedor de conectividade (best-effort) tanto no dominio da cloud como no da rede de acesso. O trabalho desenvolvido nesta Tese permite uma integração efetiva dos domínios de cloud e operador de rede, dando assim à cloud o efetivo suporte da rede. Para tal, apresentamos uma plataforma e um conjunto de mecanismos associados para gestão e controlo integrado de domínios cloud computing e operador de rede por forma a fornecer serviços fim-a-fim. Além disso, elaboramos um estudo aprofundado sobre o mapeamento de recursos virtuais neste ambiente integrado. O estudo centra-se na maximização da incorporação de recursos virtuais na infraestrutura física por meio de estratégias de mapeamento ótimas (considerando a alocação inicial de recursos, bem como adaptações ao longo do tempo), enquanto que se minimizam os custos associados ao consumo de energia. Este estudo é feito para cenários de apenas um domínio e para cenários com múltiplos domínios. Além disso, exploramos como o operador de rede pode aproveitar o referido ambiente integrado para suportar funções de rede tradicionais. Neste sentido, estudamos como as funções de rede virtualizadas devem ser modeladas e geridas num ambiente cloud e estendemos a plataforma de acordo com este conceito. No âmbito desta Tese foi feita uma avaliação extensa das soluções propostas, avaliando os seus benefícios. Implementámos provas de conceito por forma a demonstrar as mais-valias, viabilidade e fácil implantação das soluções propostas. Além disso, a avaliação das estratégias de mapeamento foi realizada através de ferramentas de simulação e de programação linear inteira, mostrando que é possível reduzir o consumo de energia da infraestrutura física, sem comprometer a aceitação de recursos virtuais. Este aspeto pode ser melhorado através da adaptação de recursos virtuais ao longo do tempo. No entanto, deve-se ter em mente os custos associados aos processos de adaptação. Os custos podem ser minimizados, mas isso implica uma redução na aceitação de recursos virtuais. Esta compensação foi também um tema abordado nesta Tese