Slices were introduced in 5G to enable the co-existence of applications with different requirements on a single infrastructure. Slices may be delay-constrained for mission-critical applications such as Tactile Internet applications. When delay-constrained slices are implemented as collections of virtual network function (VNF) chains, a key challenge is to place the VNFs and route the traffic through the chains to meet a strict delay constraint. Parallel VNF processing has been proposed as a promising approach. However, this approach increases the number of physical nodes in the chains, and thus decreases the reliability, which is also critical for Tactile Internet applications. Furthermore, the cost depends upon the specific VNF placement and traffic routing, as nodes and links are heterogeneous. This article tackles the issues of reliability and cost when embedding delay-constrained slices. We model the problem as an optimization problem that minimizes reliability degradation and cost while ensuring the strict delay constraint when a parallel VNF processing approach is used. Due to the complexity of the formulated problem, we also propose a Tabu search-based algorithm to find sub-optimal solutions. The results indicate that our proposed algorithm can significantly improve cost and reliability while meeting a strict delay constraint.

Fog computing reduces the latency induced by distant clouds by enabling the deployment of some application components at the edge of the network, on fog nodes, while keeping others in the cloud. Application components can be implemented as Virtual Network Functions (VNFs) and their execution sequences can be modeled by a combination of sub-structures like sequence, parallel, selection, and loops. Efficient placement algorithms are required to map the application components onto the infrastructure nodes. Current solutions do not consider the mobility of fog nodes, a phenomenon which may happen in real systems. In this paper, we use the random waypoint mobility model for fog nodes to calculate the expected makespan and application execution cost. We then model the problem as an Integer Linear Programming (ILP) formulation which minimizes an aggregated weighted function of the makespan and cost. We propose a Tabu Search-based Component Placement (TSCP) algorithm to find sub-optimal placements. The results show that the proposed algorithm improves the makespan and the application execution cost.

The European Telecommunications Standards Institute (ETSI) developed Network Functions Virtualization (NFV) Management and Orchestration (MANO) framework. Within that framework, NFV orchestrator (NFVO) and Virtualized Network Function (VNF) Manager (VNFM) functional blocks are responsible for managing the lifecycle of network services and their associated VNFs. However, they face significant scalability and performance challenges in large-scale and geo-distributed NFV systems. Their number and location have major implications for the number of VNFs that can be accommodated and also for the overall system performance. NFVO and VNFM placement is therefore a key challenge due to its potential impact on the system scalability and performance. In this paper, we address the placement of NFVO and VNFM in large-scale and geo-distributed NFV infrastructure. We provide an integer linear programming formulation of the problem and propose a two-step placement algorithm to solve it. We also conduct a set of experiments to evaluate the proposed algorithm.

The European Telecommunications Standards Institute management and orchestration framework is designed to enable automated management of the network services and their corresponding virtualized network functions (VNFs). In that context, the network function virtualization (NFV) orchestrator (NFVO) manages the lifecycle of the network services and coordinates with the VNF managers (VNFMs) which manage the VNFs lifecycle. In large-scale and distributed NFV deployments, these management functions face critical challenges such as delays, and variations in VNFs workload. Placing NFVO and VNFM in a large-scale distributed NFV deployment is therefore a very challenging problem due to the potential negative impact on performance and operational cost. However, to the best of our knowledge, the problem has not yet been addressed in the literature. This paper is a first step toward a solution to the overall problem. It focuses on the VNFM placement and aims at minimizing the operational cost without violating the performance requirements. We call this the VNFM placement problem (MPP). We provide an integer linear programming formulation and propose a tabu search algorithm to solve larger instances of the MPP. We evaluate our algorithm in a real-world large-scale scenario. The results show that it leads to significant reductions in the operational cost of large-scale distributed NFV deployments.

Home Subscriber Server (HSS) is the main database of the current generation's cellular communications systems. It contains subscriber-related information, such as the authentication information and the list of services to which each user is subscribed. The anticipated tremendous increase in the number of subscribers, services and devices (M2M) in 5G networks brings new challenges with regard to HSS provisioning. It calls for more scalability and elasticity regarding information storage, access and management. The current method for increasing the number of HSSs deployed is certainly not the most cost efficient solution. On the other hand, advanced virtualization techniques can aid in tackling the challenges while enabling a smooth migration to 5G. This paper proposes a new architecture for a scalable and elastic HSS using virtualization. The new architecture enables easy and rapid deployment of new HSS instances at a minimal cost, while increasing efficiency of the use of resources. The paper presents the architecture, demonstrates its use via a case scenario, describes the implemented proof of concept prototype and evaluates the performance results.