Design of an Integrated SDN/NFV management and orchestration architecture

This project aims at explaining and defining the SDN technology with integration of the NFV technology. We will also see the logic of this technology applied to a program designed for this project. The objective of this project is to understand the purpose of this technology, where is it going to be used, why companies like Google or Microsoft for over 2 years have been investing time and resources to develop and to implement the technology on the corporate level, as well as on the level of regular user like you and me. Firstly we will focus on the explanation of the SDN technology, what it is, what for is it going to be used and what is the future of this technology. Why the SDN is so important? Next, we will explain the use of the NFV and show how it is going to change the way we see the network right now. NFV also works with the SDN. Once we define the basics of the two technologies, we will proceed to the explanation of the practical part of this project. I would like to comment on the software used for this project is open source, since the OS used on the machine that carried out the simulations, and wrote this lines, to the package Rstudio. The practical part is to simulate how will work the network flows when this technology is used. The program will optimize the resources that we want for the proper performance of the global system. For example, we can optimize the path, the number of machines the flow has to cross, optimize the global delay of the flow, etc. Finally, we will reach specific conclusions based on the work we have done, as well as some personal outcome, such as the analysis of the difficulties encountered during the performance, as well as training and finally knowledge gained through work

MeDICINE: Rapid Prototyping of Production-Ready Network Services in Multi-PoP Environments

Virtualized network services consisting of multiple individual network functions are already today deployed across multiple sites, so called multi-PoP (points of presence) environ- ments. This allows to improve service performance by optimizing its placement in the network. But prototyping and testing of these complex distributed software systems becomes extremely challenging. The reason is that not only the network service as such has to be tested but also its integration with management and orchestration systems. Existing solutions, like simulators, basic network emulators, or local cloud testbeds, do not support all aspects of these tasks. To this end, we introduce MeDICINE, a novel NFV prototyping platform that is able to execute production-ready network func- tions, provided as software containers, in an emulated multi-PoP environment. These network functions can be controlled by any third-party management and orchestration system that connects to our platform through standard interfaces. Based on this, a developer can use our platform to prototype and test complex network services in a realistic environment running on his laptop.Comment: 6 pages, pre-prin

Understand Your Chains: Towards Performance Profile-based Network Service Management

Allocating resources to virtualized network functions and services to meet service level agreements is a challenging task for NFV management and orchestration systems. This becomes even more challenging when agile development methodologies, like DevOps, are applied. In such scenarios, management and orchestration systems are continuously facing new versions of functions and services which makes it hard to decide how much resources have to be allocated to them to provide the expected service performance. One solution for this problem is to support resource allocation decisions with performance behavior information obtained by profiling techniques applied to such network functions and services. In this position paper, we analyze and discuss the components needed to generate such performance behavior information within the NFV DevOps workflow. We also outline research questions that identify open issues and missing pieces for a fully integrated NFV profiling solution. Further, we introduce a novel profiling mechanism that is able to profile virtualized network functions and entire network service chains under different resource constraints before they are deployed on production infrastructure.Comment: Submitted to and accepted by the European Workshop on Software Defined Networks (EWSDN) 201

Automated Network Service Scaling in NFV: Concepts, Mechanisms and Scaling Workflow

Next-generation systems are anticipated to be digital platforms supporting innovative services with rapidly changing traffic patterns. To cope with this dynamicity in a cost-efficient manner, operators need advanced service management capabilities such as those provided by NFV. NFV enables operators to scale network services with higher granularity and agility than today. For this end, automation is key. In search of this automation, the European Telecommunications Standards Institute (ETSI) has defined a reference NFV framework that make use of model-driven templates called Network Service Descriptors (NSDs) to operate network services through their lifecycle. For the scaling operation, an NSD defines a discrete set of instantiation levels among which a network service instance can be resized throughout its lifecycle. Thus, the design of these levels is key for ensuring an effective scaling. In this article, we provide an overview of the automation of the network service scaling operation in NFV, addressing the options and boundaries introduced by ETSI normative specifications. We start by providing a description of the NSD structure, focusing on how instantiation levels are constructed. For illustrative purposes, we propose an NSD for a representative NS. This NSD includes different instantiation levels that enable different ways to automatically scale this NS. Then, we show the different scaling procedures the NFV framework has available, and how it may automate their triggering. Finally, we propose an ETSI-compliant workflow to describe in detail a representative scaling procedure. This workflow clarifies the interactions and information exchanges between the functional blocks in the NFV framework when performing the scaling operation.Comment: This work has been accepted for publication in the IEEE Communications Magazin

Process management and orchestration

Process automation is a concept used in logistics that has been adopted in some data centre management software suites recently as “Orchestration managers”. This project is about mapping out and comparing approaches to process management. Specifically, two popular and very different process modelling methods were compared. One is the BPMN (Business Process Management Notation) that uses the traditional method to model the process in a flow. The other is the Promise Theory that models the process in a network of interacting autonomous agents. Our research question is what’s the differences between two methods. We used Promise Theory in two ways: as a framework for discussing modeling of processes, and as a tool for modeling. Results show that Promise Theory can model more features of a process than BPMN. Promise Theory with fewer symbols is easier to learn but requires more thinking when using than BPMN. Under the circumstances where there are many asynchronous activities or many agents/roles involved in the process, Promise Theory has better performance to model the agents’ autonomous behavior and the interaction between them.Master i nettverks- og systemadministrasjo

APMEC: An Automated Provisioning Framework for Multi-access Edge Computing

Novel use cases and verticals such as connected cars and human-robot cooperation in the areas of 5G and Tactile Internet can significantly benefit from the flexibility and reduced latency provided by Network Function Virtualization (NFV) and Multi-Access Edge Computing (MEC). Existing frameworks managing and orchestrating MEC and NFV are either tightly coupled or completely separated. The former design is inflexible and increases the complexity of one framework. Whereas, the latter leads to inefficient use of computation resources because information are not shared. We introduce APMEC, a dedicated framework for MEC while enabling the collaboration with the management and orchestration (MANO) frameworks for NFV. The new design allows to reuse allocated network services, thus maximizing resource utilization. Measurement results have shown that APMEC can allocate up to 60% more number of network services. Being developed on top of OpenStack, APMEC is an open source project, available for collaboration and facilitating further research activities

NFV Orchestrator Placement for Geo-Distributed Systems

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.Comment: This paper has been accepted for presentation in 16th IEEE International Symposium on Network Computing and Applications (IEEE NCA 2017