Cloud computing and network slicing are essential concepts of forthcoming 5G mobile systems. Network slices are essentially chunks of virtual computing and connectivity resources, configured and provisioned for particular services according to their characteristics and requirements. The success of cloud computing and network slicing hinges on the efficient allocation of virtual resources (e.g. VCPU, VMDISK) and the optimal placement of Virtualized Network Functions (VNFs) composing the network slices. In this context, this paper elaborates issues that may disrupt the placement of VNFs and VMs. The paper classifies the existing solutions for VM Placement (VMP) based on their nature, whether the placement is dynamic or static, their objectives, and their metrics. The paper then proposes a classification of VNF Placement (VNFP) approaches, first, regarding the general placement and management issues of VNFs, and second, based on the target VNF type.
Many ongoing research activities relevant to 5G mobile systems concern the virtualization of the mobile core network, including the evolved packet core (EPC) elements, aiming for system scalability, elasticity, flexibility, and cost-efficiency. Virtual EPC (vEPC)/5G core will principally rely on some key technologies, such as network function virtualization, software defined networking, and cloud computing, enabling the concept of mobile carrier cloud. The key idea beneath this concept, also known as core network as a service, consists in deploying virtual instances (i.e., virtual machines or containers) of key core network functions [i.e., virtual network functions (VNF) of 4G or 5G], such as the mobility management entity (MME), Serving GateWay (SGW), Packet Data network gateWay (PGW), access and mobility management function (AMF), session management function (SMF), authentication server function (AUSF), and user plane functions, over a federated cloud. In this vein, an efficient VNF placement algorithm is highly needed to sustain the quality of service (QoS) while reducing the deployment cost. Our contribution in this paper is twofold. First, we devise an algorithm that derives the optimal number of virtual instances of 4G (MME, SGW, and PGW) or 5G (AMF, SMF, and AUSF) core network elements to meet the requirements of a specific mobile traffic. Second, we propose an algorithm for the placement of these virtual instances over a federated cloud. While the first algorithm is based on mixed integer linear programming, the second is based on coalition formation game, wherein the aim is to build coalitions of cloud networks to host the virtual instances of the vEPC/5G core elements. The obtained results clearly indicate the advantages of the proposed algorithms in ensuring QoS given a fixed cost for vEPC/5G core deployment, while maximizing the profits of cloud operators.
To support the much desired ultra-short latency of 5G mobile systems, many micro-data centers will be deployed in the vicinity of mobile users, defining a distributed edge cloud. Over this edge cloud, it is important to create optimal network slices to support different 5G verticals. Optimality is defined in terms of cost efficiency and QoS support. Therefore, it is important to understand the behavior of mobile users in terms of mobile service consumption. In this paper, we present, on one hand, a tool for developing a spatio-temporal model of mobile service usage over a particular geographical area. This tool will help to define the behavior of mobile users in terms of mobility patterns and mobile service consumption. On the other hand, based on this tool, we present a benchmark of some interesting Virtualized Network Functions (VNF) placement algorithms, among them our enhanced version of the predictive placement strategy. The comparison is based on data overload, overload of Virtual Machines (VMs) and QoS.
5G is the next telecommunications standards that will enable the sharing of physical infrastructures to provision ultra short-latency applications, mobile broadband services, Internet of Things, etc. Network slicing is the virtualization technique that is expected to achieve that, as it can allow logical networks to run on top of a common physical infrastructure and ensure service level agreement requirements for different services and applications. In this vein, our paper proposes a novel and complete solution for planning network slices of the LTE EPC, tailored for the enhanced Mobile BroadBand use case. The solution defines a framework which consists of: i) an abstraction of the LTE workload generation process, ii) a compound traffic model, iii) performance models of the whole LTE network, and iv) an algorithm to jointly perform the resource dimensioning and network embedding. Our results show that the aggregated signaling generation is a Poisson process and the data traffic exhibits self-similarity and long-range-dependence features. The proposed performance models for the LTE network rely on these results. We formulate the joint optimization problem of resources dimensioning and embedding of a virtualized EPC and propose a heuristic to solve it. By using simulation tools, we validate the proper operation of our solution.
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