Optimizing Placement and Scheduling for VNF by a Multi-objective Optimization Genetic Algorithm

Virtual network functions (VNFs) have gradually replaced the implementation of traditional network functions. Through efficient placement, the VNF placement technology strives to operate VNFs consistently to the greatest extent possible within restricted resources. Thus, VNF mapping and scheduling tasks can be framed as an optimization problem. Existing research efforts focus only on optimizing the VNFs scheduling or mapping. Besides, the existing methods focus only on one or two objectives. In this work, we proposed addressing the problem of VNFs scheduling and mapping. This work proposed framing the problem of VNFs scheduling and mapping as a multi-objective optimization problem on three objectives, namely (1) minimizing line latency of network link, (2) reducing the processing capacity of each virtual machine, and (3) reducing the processing latency of virtual machines. Then, the proposed VNF-NSGA-III algorithm, an adapted variation of the NSGA-III algorithm, was used to solve this multi-objective problem. Our proposed algorithm has been thoroughly evaluated through a series of experiments on homogeneous and heterogeneous data center environments. The proposed method was compared to several heuristic and recent meta-heuristic methods. The results reveal that the VNF-NSGA-III outperformed the comparison methods

Placement and Scheduling of Network Traffic on Virtual Network Functions

Hardware MiddleBoxes represent a vital part in today's networks. Despite their important roles, they are accompanied by several problems, namely, their lack of flexibility, high capital and operational expenditures, and power consumption. Network Function Virtualization is one promising solution to address these problems. This trend replaces the MiddleBoxes by software-based entities. Indeed, these Virtual Network Functions promise to alleviate the numerous disadvantages brought by their hardware counterparts. One of these most serious issues is the steadily increasing power consumption. Studies suggest that the Virtual Network Functions will reduce the electricity costs needed to turn on and operate the hardware functions. In order to further optimize the power consumption of the network, an efficient framework, capable of placing and scheduling traffic on these VNFs, is needed. Such a framework allows to optimally map and schedule the flows to be serviced, and place the unused servers in energy saving modes. In this thesis, we assume VNFs are already placed on physical machines. We consider traffic flows with deadlines. We aim at assigning and scheduling flows to VNFs in the most energy efficient manner. We formulate this problem mathematically and, owing to its complexity, present an efficient algorithmic method for solving the problem. We compare our heuristic with two other approaches, one of which aims to minimize the makespan, and the other to minimize number of servers used. We show that our heuristic combines the advantages of both approaches and generates better results by consuming up to 31.3% and 46.1% energy less than other two approaches respectively. Further, we extend the existing work in the literature, and solve the problem of placement of traffic flows on VNFs while taking into account the transmission delay between pairs of VNFs, and the routing of the virtual links on the underlying physical network

Provisioning Ultra-Low Latency Services in Softwarized Network for the Tactile Internet

The Internet has made several giant leaps over the years, from a fixed to a mobile Internet, then to the Internet of Things, and now to a Tactile Internet. The Tactile Internet is envisioned to deliver real-time control and physical tactile experiences remotely in addition to conventional audiovisual data to enable immersive human-to-machine interaction and allow skill-set delivery over networks. To realize the Tactile Internet, two key performance requirements, namely ultra-low latency and ultra-high reliability need to be achieved. However, currently deployed networks are far from meeting these stringent requirements and cannot efficiently cope with dynamic service arrivals/departures and the significant growth of traffic demands. To fulfill these requirements, a softwarized network enabled by network function virtualization (NFV) and software-defined network (SDN) technologies is introduced as a new promising concept of a future network due to its flexibility, agility, scalability and cost efficiency. Despite these benefits, provisioning Tactile Internet network services (NSs) in an NFV-based infrastructure remains a challenge, as network resources must be allocated for virtual network function (VNF) deployment and traffic routing in such a way that the stringent requirements are met, and network operator’s objectives are optimized. This problem is also well-known, as NFV resource allocation (NFV-RA) and can be further divided into three stages: (i) VNF composition, (ii) VNF embedding/placement and (iii) VNF scheduling. This thesis addresses challenges on NFV-RA for Tactile Internet NSs, especially ultra-low latency NSs. We first conduct a survey on architectural and algorithmic solutions proposed so far for the Tactile Internet. Second, we propose a joint VNF composition and embedding algorithm to efficiently determine the number of VNF instances to form a VNF forward graph (VNF-FG) and their embedding locations to serve ultra-low latency NSs, as in some cases, multiple instances of each VNF type with proper embedding may be needed to guarantee the stringent latency requirements. The proposed algorithm relies on a Tabu search method to solve the problem with a reasonable time. Third, we introduce real-time VNF embedding algorithms to efficiently support ultra-low latency NSs that require fast service provisioning. By assuming that a VNF-FG is given, our proposed algorithms aim to minimize the cost while meeting the stringent latency requirement. Finally, we focus on a joint VNF embedding and scheduling problem, assuming that ultra-low latency NSs can arrive in the network any time and have specific service deadlines. Moreover, VNF instances once deployed can be shared by multiple NSs. With these assumptions, we aim to optimally determine whether to schedule NSs on already deployed VNFs or to deploy new VNFs and schedule them on newly deployed VNFs to maximize profits while guaranteeing the stringent service deadlines. Two efficient heuristics are introduced to solve this problem with a feasible time

Service Chaining Placement Based on Satellite Mission Planning in Ground Station Networks

As the increase in satellite number and variety, satellite ground stations should be required to offer user services in a flexible and efficient manner. Network function virtualization (NFV) can provide a new paradigm to allocate network resources on-demand for user services over the underlying network. However, most of the existing work focuses on the virtual network function (VNF) placement and routing traffic problem for enterprise data center networks, the issue needs to further study in satellite communication scenarios. In this paper, we investigate the VNF placement and routing traffic problem in satellite ground station networks. We formulate the problem of resource allocation as an integer linear programming (ILP) model and the objective is to minimize the link resource utilization and the number of servers used. Considering the information about satellite orbit fixation and mission planning, we propose location-aware resource allocation (LARA) algorithms based on Greedy and IBM CPLEX 12.10, respectively. The proposed LARA algorithm can assist in deploying VNFs and routing traffic flows by predicting the running conditions of user services. We evaluate the performance of our proposed LARA algorithm in three networks of Fat-Tree, BCube, and VL2. Simulation results show that our proposed LARA algorithm performs better than that without prediction, and can effectively decrease the average resource utilization of satellite ground station networks

Orchestration and Scheduling of Resources in Softwarized Networks

The Fifth Generation (5G) era is touted as the next generation of mobile networks that will unleash new services and network capabilities, opening up a whole new line of businesses recognized by a top-notch Quality of Service (QoS) and Quality of Experience (QoE) empowered by many recent advancements in network softwarization and providing an innovative on-demand service provisioning on a shared underlying network infrastructure. 5G networks will support the immerse explosion of the Internet of Things (IoT) incurring an expected growth of billions of connected IoT devices by 2020, providing a wide range of services spanning from low-cost sensor-based metering services to low-latency communication services touching health, education and automotive sectors among others. Mobile operators are striving to find a cost effective network solution that will enable them to continuously and automatically upgrade their networks based on their ever growing customers demands in the quest of fulfilling the new rising opportunities of offering novel services empowered by the many emerging IoT devices. Thus, departing from the shortfalls of legacy hardware (i.e., high cost, difficult management and update, etc.) and learning from the different advantages of virtualization technologies which enabled the sharing of computing resources in a cloud environment, mobile operators started to leverage the idea of network softwarization through several emerging technologies. Network Function Virtualization (NFV) promises an ultimate Capital Expenditures (CAPEX) reduction and high flexibility in resource provisioning and service delivery through replacing hardware equipment by software. Software Defined Network (SDN) offers network and mobile operators programmable traffic management and delivery. These technologies will enable the launch of Multi-Access Edge Computing (MEC) paradigm that promises to complete the 5G networks requirements in providing low-latency services by bringing the computing resources to the edge of the network, in close vicinity of the users, hence, assisting the limited capabilities of their IoT devices in delivering their needed services. By leveraging network softwarization, these technologies will initiate a tremendous re-design of current networks that will be transformed to self-managed, software-based networks exploiting multiple benefits ranging from flexibility, programmability, automation, elasticity among others. This dissertation attempts to elaborate and address key challenges related to enabling the re-design of current networks to support a smooth integration of the NFV and MEC technologies. This thesis provides a profound understanding and novel contributions in resource and service provisioning and scheduling towards enabling efficient resource and network utilization of the underlying infrastructure by leveraging several optimization and game theoretic techniques. In particular, we first, investigate the interplay existing between network function mapping, traffic routing and Network Service (NS) scheduling in NFV-based networks and present a Column Generation (CG) decomposition method to solve the problem with considerable runtime improvement over mathematical-based formulations. Given the increasing interest in providing low-latency services and the correlation existing between this objective and the goal of network operators in maximizing their network admissibility through efficiently utilizing their network resources, we revisit the latter problem and tackle it under different assumptions and objectives. Given its complexity, we present a novel game theoretic approach that is able to provide a bounded solution of the problem. Further, we extend our work to the network edge where we promote network elasticity and alleviate virtualization technologies by addressing the problem of task offloading and scheduling along with the IoT application resource allocation problem. Given the complexity of the problem, we propose a Logic-Based Benders (LBBD) decomposition method to efficiently solve it to optimality

Energy-Efficient Softwarized Networks: A Survey

With the dynamic demands and stringent requirements of various applications, networks need to be high-performance, scalable, and adaptive to changes. Researchers and industries view network softwarization as the best enabler for the evolution of networking to tackle current and prospective challenges. Network softwarization must provide programmability and flexibility to network infrastructures and allow agile management, along with higher control for operators. While satisfying the demands and requirements of network services, energy cannot be overlooked, considering the effects on the sustainability of the environment and business. This paper discusses energy efficiency in modern and future networks with three network softwarization technologies: SDN, NFV, and NS, introduced in an energy-oriented context. With that framework in mind, we review the literature based on network scenarios, control/MANO layers, and energy-efficiency strategies. Following that, we compare the references regarding approach, evaluation method, criterion, and metric attributes to demonstrate the state-of-the-art. Last, we analyze the classified literature, summarize lessons learned, and present ten essential concerns to open discussions about future research opportunities on energy-efficient softwarized networks.Comment: Accepted draft for publication in TNSM with minor updates and editin

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-aware placement solution using a robust optimization approach based on service demand uncertainty in order to minimize the power consumption in the system constrained by network service latency requirements and infrastructure terms. Then, we discuss the results of the proposed placement mechanism in 5G scenarios that combine several service flavours and robust protection values. Once the impact of the service flavour and robust protection on the global power consumption of the system is analyzed, numerical results indicate that our proposal succeeds in efficiently placing the virtual network functions that compose the network services in the available hardware infrastructure while fulfilling service constraints.The research leading to these results has been supported by the EU funded H2020 5G-PPP Project SESAME (Grant Agreement 671596) and the Spanish MINECO Project 5GRANVIR (TEC2016-80090-C2-2-R)