Efficient solutions to the placement and chaining problem of User Plane Functions in 5G Networks

This study attempts to solve the placement and chaining problem of 5G User Plane Functions (UPFs) in a Multi-access Edge Computing (MEC) ecosystem. The problem is formalized as a multi-objective Integer Linear Programming (ILP) model targeted at optimizing provisioning costs and quality of service. Our model takes into account several aspects of the system such as UPF-specific considerations, the Service Function Chain (SFC) requests topology (single and multiple branches), Virtual Network Function (VNF) order constraints, service demands, and physical network capacities. Since the formulated problem is NP-hard, two heuristic solutions are devised to enhance solution efficiency. Specifically, an algorithm called Priority and Cautious-UPF Placement and Chaining (PC-UPC) and a simulated annealing (SA) meta-heuristic are proposed. Through extensive simulation experiments, we evaluated the performance of the proposed solutions. The results revealed that our solutions outperformed the baselines (i.e., two greedy-based heuristics and a variant of the classical SA) and that we had obtained nearly optimal solutions with significant reductions in running time. Moreover, the PC-UPC algorithm can effectively avoid SFC rejections and improve provisioning costs by considering session requirements, current network conditions, and the effects of VNF mapping decisions. Additionally, the proposed SA approach incorporates several mechanisms (e.g., variable Markov chain length and restart–stop) that allow the improvement of not only the quality of the solutions but also their computation time.Postprint (published version

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

A Data Distribution Service in a hierarchical SDN architecture: implementation and evaluation

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Software-defined networks (SDNs) have caused a paradigm shift in communication networks as they enable network programmability using either centralized or distributed controllers. With the development of the industry and society, new verticals have emerged, such as Industry 4.0, cooperative sensing and augmented reality. These verticals require network robustness and availability, which forces the use of distributed domains to improve network scalability and resilience. To this aim, this paper proposes a new solution to distribute SDN domains by using Data Distribution Services (DDS). The DDS allows the exchange of network information, synchronization among controllers and auto-discovery. Moreover, it increases the control plane robustness, an important characteristic in 5G networks (e.g., if a controller fails, its resources and devices can be managed by other controllers in a short amount of time as they already know this information). To verify the effectiveness of the DDS, we design a testbed by integrating the DDS in SDN controllers and deploying these controllers in different regions of Spain. The communication among the controllers was evaluated in terms of latency and overhead.Postprint (author's final draft

The resources placement problem in a 5G hierarchical SDN control plane

In this paper, we address the SDN Controllers and Virtual Network Functions (VNFs) placement problem in 5G networks. To this aim, we propose an architecture for the 5G Control Plane and a method to determine the optimal placement of controllers and VNFs. The placement is determined according not only to latency and capacity requirements but also to type of Network Function (NF).Peer ReviewedPostprint (author's final draft

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

An SDN-based solution for horizontal auto-scaling and load balancing of transparent VNF clusters

© 2021 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/)This paper studies the problem of the dynamic scaling and load balancing of transparent virtualized network functions (VNFs). It analyzes different particularities of this problem, such as loop avoidance when performing scaling-out actions, and bidirectional flow affinity. To address this problem, a software-defined networking (SDN)-based solution is implemented consisting of two SDN controllers and two OpenFlow switches (OFSs). In this approach, the SDN controllers run the solution logic (i.e., monitoring, scaling, and load-balancing modules). According to the SDN controllers instructions, the OFSs are responsible for redirecting traffic to and from the VNF clusters (i.e., load-balancing strategy). Several experiments were conducted to validate the feasibility of this proposed solution on a real testbed. Through connectivity tests, not only could end-to-end (E2E) traffic be successfully achieved through the VNF cluster, but the bidirectional flow affinity strategy was also found to perform well because it could simultaneously create flow rules in both switches. Moreover, the selected CPU-based load-balancing method guaranteed an average imbalance below 10% while ensuring that new incoming traffic was redirected to the least loaded instance without requiring packet modification. Additionally, the designed monitoring function was able to detect failures in the set of active members in near real-time and active new instances in less than a minute. Likewise, the proposed auto-scaling module had a quick response to traffic changes. Our solution showed that the use of SDN controllers along with OFS provides great flexibility to implement different load-balancing, scaling, and monitoring strategies.Postprint (published version

Dynamic Scheduling and Optimal Reconfiguration of UPF Placement in 5G Networks

Multi-access Edge Computing (MEC) is a key technology in the road to 5G and beyond networks. Significant reductions in both latency and backhaul traffic can be achieved by placing server applications, and network functions at the network edge. However, this implies new challenges for their dynamic placement and management. In this paper, we tackle the problem of dynamic placement reconfiguration of 5G User Plane Functions (UPFs) in a MEC ecosystem to adapt to changes in user locations while ensuring QoS and network operator expenditures reduction. In this vein, an Integer Linear Programming (ILP) solution is proposed to determine the optimal UPF placement configuration (e.g., number of UPFs and user-UPF mapping) by considering several cost components along with service requirements. Moreover, a scheduling technique based on Optimal Stopping Theory (OST) is presented to decide the optimal reconfiguration time according to instantaneous values of latency violations and established QoS thresholds. Extensive simulation results demonstrate their effectiveness, achieving significant improvements in metrics such as number of re-computation events, reconfiguration costs, and number of latency violations over time

An architecture for the 5G control plane based on SDN and data distribution service

The tremendous growth of services and costumers’ demands have rendered traditional networks inefficient. Telecommunication operators need a more flexible, scalable, faster and programmable architecture to offer users these new services. Software Defined Networking (SDN) has emerged as a natural solution to this situation as it enables network programmability. This article provides a review of the SDN architectures applied to fifth generation (5G) networks. In this work, the prime focus is a proposal of control plane for a 5G architecture with a hybrid hierarchical set of controllers. The architecture is based on a federation of multiple sub-network controllers, each managing only a section of the network, conveniently coordinated by a hierarchically-superior controller. The use of Data Distribution Service (DDS) as a standard of the Object Management Group (OMG) is explored to improve the performance of the proposed architecture. DDS is used taking into account empirical results which have demonstrated a significant improvement in the performance compared to other existing solutions that do not use DDS. We illustrate the flexibility of our approach by presenting some use cases describing how the different elements of this architecture works.Postprint (author's final draft

Software defined networks and data distribution service as key features for the 5G control plane

The latency and flexible requirements of the 5G network are challenging telecommunication operators to have a more flexible, scalable, faster and programmable architecture. To solve this problem, this paper proposes a hybrid hierarchical set of Software Defined Networks (SDN) controllers as the control plane for 5G networks. The architecture is based on a federation of hierarchically-superior controllers which use Data Distribution Service (DDS) to communicate among each other and coordinate multiple sub-network controllers.Peer ReviewedPostprint (author's final draft

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