Virtual Infrastructure Manager Research Articles

Improvement of 5G Core Network Performance using Network Slicing and Deep Reinforcement Learning

Users have increasingly been having more use cases for the network while expecting the best Quality of Service (QoS) and Quality of Experience (QoE). The Fifth Generation of mobile telecommunications technology (5G) network had promised to satisfy most of the expectations and network slicing had been introduced in 5G to be able to satisfy various use cases. However, creating slices in a real-life environment with just the resources required while having optimized QoS has been a challenge. This has necessitated more intelligence to be required in the network and machine learning (ML) has been used recently to add the intelligence and ensure zero-touch automation. This research addresses the open question of creating slices to satisfy various use cases based on their QoS requirements, managing, and orchestrating them optimally with minimal resources while allowing the isolation of services by introducing a Deep reinforcement Machine Learning (DRL) algorithm. This research first evaluates the previous work done in improving QoS in the 5G core. 5G architecture is simulated by following the ETSI NFV MANO (European Telecommunications Standards Institute for Network Function Virtualization Management and Orchestration) framework and uses Open5G in 5G core, UERANISM for RAN, Openstack for Virtual Infrastructure Manager (VIM), and Tacker for Virtual Network Function Management and orchestration (VNFMO). The research simulates network slicing at the User Plane Function (UPF) level and evaluates how it has improved QoS. The network slicing function is automated by following ETSI Closed Loop Architecture and using Deep Reinforcement Learning (DRL) by modeling the problem as a Markov Decision Problem (MDP). Throughput is the Reward for the actions of the DRL agent. Comparison is done on the impact of slicing on throughput and compares models that have not been sliced, the ones that have been sliced and combined to work together, and models with slices that have been assigned more bandwidth. Sliced networks have better throughput than the ones not sliced. If more slices are load-balanced the throughput is increased. Deep Reinforcement Learning has managed to achieve the dynamic assigning of slices to compensate for declining throughput.

Implementation of Decision-Making Algorithms and Key Requirement Approach for Vendor Selection in Telecommunication Device Bidding

The influence of perceived quality is a classic problem in a vendor selection process. To overcome this problem, many algorithms have been used in decision making. In this paper we have carried out the identification of planning team needs and the optimization of the bidding scheme using key requirements to minimize the influence of quality perceptions. The Kano Model Analysis method, the Analytical Hierarchy Process and Technique for Order Preference by Similarity to the Ideal Solution are used to analyze and determine the key requirements in the bidding process for telecommunications equipment needed by the planning team. Vendor selection based on key of requirements specifications is carried out in six stages, namely the preparation stage, requirements search, selection of Key of Requirements specifications, vendor selection, accuracy testing and conclusions. The results of the analysis show that the need for new planning and architecture of telecommunication service providers can increase to NFVi and services. An important criterion for NVFi (Hardware) development is Virtual Infrastructure Management (VIM) with a weight of 22%, while the service criteria are Fixed Services with a weight of 50.94%. Based on the analysis results, the preference value of each telecommunication equipment vendor (supplier) is also obtained.

Smart5Grid Solutions for enhanced TSO grid observability and manageability in massive RES penetration environment

Background This article elaborates on Horizon 2020 Smart5Grid Research and Innovation (R&I) project and reports the Smart5Grid Open Experimentation Platform (OEP), including its Open Service Repository (OSR), Verification and Validation (V&V), NetApp Controller (NAC), and Multi-access Edge Computing Orchestrator (MECO), as key results of this project. It then translates those results into energy vertical implications of the Smart5Grid for Transmission System Operators (TSOs), focusing on two particular Use Cases (UCs): UC3 Millisecond Level Precise Distribution Generation Control and UC4 Real-time Wide Area Monitoring pilot demonstrator of 5G virtual PDC capabilities for WAM of end-to-end electricity grids. More specifically, this work exhibits UC3 and UC4 NetApps developed as one of the key project deliverables. All use cases generate openly accessible data, except where specific security restrictions are applicable. Methods The Smart5Grid development methodology is based on the concept of Network Applications (NetApps). Their main mission is to hide the complexity of a 5G telco network for energy application developers in a way that empowers them to develop a NetApp without having to deal with the underlying network. A Virtual Infrastructure Manager (VIM) such as OpenStack or Kubernetes hosts every unit that composes a NetApp. The VIM provides monitoring data to a Network Function Vurtualisation Manager and Orchestrator (NFV MANO) framework, which airs information to the NAC that employs analysis algorithms to propose the optimal Virtual Network Function (VNF) and NetApp placing. A Slice Manager (SM) reserves resources for all these capabilities. Results The Smart5Grid architecture represents the main result that this work delineates in the context of its enhanced 5G telecommunication provider (telco) capabilities for transmission and distribution grids to face and manage more efficiently high Renewable Energy Sources (RES) penetration in a decarbonisation context.

On the Fly Orchestration of Unikernels: Tuning and Performance Evaluation of Virtual Infrastructure Managers

Network operators are facing significant challenges meeting the demand for more bandwidth, agile infrastructures, innovative services, while keeping costs low. Network Functions Virtualization (NFV) and Cloud Computing are emerging as key trends of 5G network architectures, providing flexibility, fast instantiation times, support of Commercial Off The Shelf hardware and significant cost savings. NFV leverages Cloud Computing principles to move the data-plane network functions from expensive, closed and proprietary hardware to the so-called Virtual Network Functions (VNFs). In this paper we deal with the management of virtual computing resources (Unikernels) for the execution of VNFs. This functionality is performed by the Virtual Infrastructure Manager (VIM) in the NFV MANagement and Orchestration (MANO) reference architecture. We discuss the instantiation process of virtual resources and propose a generic reference model, starting from the analysis of three open source VIMs, namely OpenStack, Nomad and OpenVIM. We improve the aforementioned VIMs introducing the support for special-purpose Unikernels and aiming at reducing the duration of the instantiation process. We evaluate some performance aspects of the VIMs, considering both stock and tuned versions. The VIM extensions and performance evaluation tools are available under a liberal open source licence.

The NECOS Approach to End-to-End Cloud-Network Slicing as a Service

Cloud-network slicing is a promising approach to serve vertical industries delivering their services over multiple administrative and technological domains. However, there are numerous open challenges to provide end-to-end slices due to complex business and engineering requirements from service and resource providers. This article presents a reference architecture for the cloud-network slicing concept and the practical realization of the slice-as-a-service paradigm, which are key results from the Novel Enablers in Cloud Slicing (NECOS) project. The NECOS platform has been designed to consider modularity, separation of concerns, and multi-domain dynamic operation as prime attributes. The architecture comprises a set of interworking components to automatically create, manage, and decommission end-to-end cloud-network slice instances in a lightweight manner. NECOS orchestrates slices at runtime, spanning across core/edge data centers and wired/wireless network infrastructures. The novelties of the multi-domain NECOS platform are validated through three proof-of-concept experiments: (i) a touristic content delivery service slice deployment featuring on-demand virtual infrastructure management across three countries on different continents to meet particular slice requirements; (ii) intelligent slice elasticity driven by machine learning techniques; and (iii) market-place-based resource discovery capabilities.

Adaptive Resource Optimized Edge Federated Learning in Real-Time Image Sensing Classifications

With the exponential growth of the Internet of things (IoT) in remote sensing image applications, network resource orchestration and data privacy are significant aspects to handle in bigdata cellular networks. The image data sharing procedure toward central cloud servers in order to perform real-time classifications has leaked client personalization and heavily burdened the communication networks. Thus, the deployment of IoT image sensors in privacy-constrained sectors requires an optimized federated learning (FL) scheme to efficiently consider both aspects of securing data privacy and maximizing the model accuracy with sufficient communication and computation resources. In this article, an adaptive model communication scheme with virtual resource optimization for edge FL is proposed by converging a deep q-learning algorithm to enforce a self-learning agent interacting with network functions virtualization orchestrator and software-defined networking based architecture. The agent targets to optimize the resource control policy of virtual multi-access edge computing entities in virtualized infrastructure manager. The proposed scheme trains the learning model and weighs the optimal actions for particular network states by using an epsilon-greedy strategy. In the exploitation phase, the scheme considers multiple spatial-resolution sensing conditions and allocates computation offloading resources for global multiconvolutional neural networks model aggregation based on the congestion states. In the simulation results, the quality of service and global collaborative model performance metrics were evaluated in terms of delay, packet drop ratios, packet delivery ratios, loss values, and overall accuracy.

Service Orchestration Over Wireless Network Slices: Testbed Setup and Integration

Network Functions Virtualization Management and Orchestration (NFV-MANO) provides a standardized approach for the management and effortless deployment of (virtual) services. Although NFV-MANO initially focused on the deployment of services over datacenters, the introduction of fully softwarized network architectures even for the wireless network creates fertile ground for the re-conception of the manner through which the underlying hardware is managed. In this article, we consider the case of an open experimentation testbed, with focus on wireless networking, and adopt the Open Source MANO framework for provisioning virtual services on top of the experimentation equipment. We extend the Virtual Infrastructure Managers (VIMs) of the NFV-MANO architecture in two well-known frameworks (Openstack and OpenVIM) for the testbed in order to create and handle virtualized wireless network interfaces, hosted on the generic networking nodes of the testbed. Through our contributions, existing VNFs can be deployed over the testbed interconnected over wireless links, specified during the on-boarding phase. The extensions are introduced transparently to the existing operation of the platform, in order to allow the portability of network services and network functions to other instances as well. We focus on providing virtual functions inter-networked over wireless links, which traditionally are not handled by the framework, and allow easier interaction of the end-users with the testbed. We benchmark the framework in terms of performance and analyze the deployment case of a softwarized 5G Radio Access Network in a real testbed deployment.

Scalable edge cloud platforms for IoT services

Nowadays, online applications are moving to the cloud, and for delay-sensitive ones, the cloud is being extended with edge/fog domains. Emerging cloud platforms that tightly integrate compute and network resources enable novel services, such as versatile IoT (Internet of Things), augmented reality or Tactile Internet applications. Virtual infrastructure managers (VIMs), network controllers and upper-level orchestrators are in charge of managing these distributed resources. A key and challenging task of these orchestrators is to find the proper placement for software components of the services. As the basic variant of the related theoretical problem (Virtual Network Embedding) is known to be NP-hard, heuristic solutions and approximations can be addressed. In this paper, we propose two architecture options together with proof-of-concept prototypes and corresponding embedding algorithms, which enable the provisioning of delay-sensitive IoT applications. On the one hand, we extend the VIM itself with network-awareness, typically not available in today's VIMs. On the other hand, we propose a multi-layer orchestration system where an orchestrator is added on top of VIMs and network controllers to integrate different resource domains. We argue that the large-scale performance and feasibility of the proposals can only be evaluated with complete prototypes, including all relevant components. Therefore, we implemented fully-fledged solutions and conducted large-scale experiments to reveal the scalability characteristics of both approaches. We found that our VIM extension can be a valid option for single-provider setups encompassing even 100 edge domains (Points of Presence equipped with multiple servers) and serving a few hundreds of customers. Whereas, our multi-layer orchestration system showed better scaling characteristics in a wider range of scenarios at the cost of a more complex control plane including additional entities and novel APIs (Application Programming Interfaces).

IT and Multi-layer Online Resource Allocation and Offline Planning in Metropolitan Networks

Metropolitan networks are undergoing a major technological breakthrough leveraging the capabilities of software-defined networking (SDN) and network function virtualization (NFV). NFV permits the deployment of virtualized network functions (VNFs) on commodity hardware appliances which can be combined with SDN flexibility and programmability of the network infrastructure. SDN/NFV-enabled networks require decision-making in two time scales: short-term online resource allocation and mid-to-long term offline planning. In this paper, we first tackle the dimensioning of SDN/NFV-enabled metropolitan networks paying special attention to the role that latency plays in the capacity planning. We focus on a specific use-case: the metropolitan network that covers the Murcia - Alicante Spanish regions. Then, we propose a latency-aware multilayer service-chain allocation (LA-ML-SCA) algorithm to explore a range of maximum latency requirements and their impact on the resources for dimensioning the metropolitan network. We observe that design costs increase for low latency requirements as more data center facilities need to be spread to get closer to the network edge, reducing the economies of scale on the IT infrastructure. Subsequently, we review our recent joint computation of multi-site VNF placement and multilayer resource allocation in the deployment of a network service in a metro network. Specifically, a set of subroutines contained in LA-ML-SCA are experimentally validated in a network optimization-as-a-service architecture that assists an Open-Source MANO instance, virtual infrastructure managers and WAN controllers in a metro network test-bed.

A UAV-based moving 5G RAN for massive connectivity of mobile users and IoT devices

Currently, the coexistence of multiple users and devices challenges the network's ability to reliably connect them. This article proposes a novel communication architecture that satisfies the requirements of fifth-generation (5G) mobile network applications. In particular, this architecture extends and combines ultra-dense networking (UDN), multi-access edge computing (MEC), and virtual infrastructure manager (VIM) concepts to provide a flexible network of moving radio access (RA) nodes, flying or moving to areas where users and devices struggle for connectivity and data rate. Furthermore, advances in radio communications and non-orthogonal multiple access (NOMA), virtualization technologies and energy-awareness mechanisms are integrated towards a mobile UDN that not only allows RA nodes to follow the user but also enables the virtualized network functions (VNFs) to adapt to user mobility by migrating from one node to another. Performance evaluation shows that the underlying network improves connectivity of users and devices through the flexible deployment of moving RA nodes and the use of NOMA.

Обзор служб сертификации Active Directory для защиты сценариев PowerShell при управлении виртуальной инфраструктурой

Обзор служб сертификации Active Directory для защиты сценариев PowerShell при управлении виртуальной инфраструктурой

On the Construction of a Cybervisor for the Intelligent Monitoring and Control of Data Centers

In this paper, we propose a cybervisor architecture for the data center. The concept of cybervisor construction is based on three components: modeling the operation of the data center, monitoring its performance and cybersecurity characteristics, and support of control decision making to improve the efficiency of the computational process. A conceptual model of the intelligent cybervisor with the compensation for the degradation of the computational process is proposed. The characteristics of virtual infrastructure management are substantiated and the functions of the cybervisor are described.

Design and Implementation of virtualized infrastructure manager based on Micro Service Architecture

Design and Implementation of virtualized infrastructure manager based on Micro Service Architecture

Need for a Transport API in 5G for Global Orchestration of Cloud and Networks Through a Virtualized Infrastructure Manager and Planner [Invited

The new 5G paradigm seeks for a scalable architecture that is able to efficiently manage the increasing volume of traffic generated by smart devices to be processed in a distributed cloud infrastructure. To this end, coordinated management of the network and the cloud resources forming an end-to-end system is of great importance. Software defined networking and network function virtualization architectures are the key enablers for integrating network and cloud resources, enabling cross optimization on both sides. This optimization requires efficient resource allocation algorithms, which take into account computing and network resources. In this paper, we propose an end-to-end orchestration architecture for distributed cloud and network resources aligned with the European Telecommunications Standards Institute management and orchestration architecture. The proposed architecture includes the virtual infrastructure manager and planner (VIMaP) component to enable dynamic resource allocation for interconnected virtual instances in distributed cloud locations. A heuristic algorithm for dynamic virtual machine graphs resource allocation is included to validate the VIMaP architecture and exploit its functionalities. Moreover, the control orchestration protocol is included between the architecture components to offer end-to-end transport services. Finally, the proposed architecture is experimentally validated, and the heuristic algorithm performance is evaluated.

A PCE-based architecture for green management of virtual infrastructures

Recent evolutions of virtualization technologies allow carriers to optimize and monetize their network infrastructures in new ways, acting as virtual infrastructure providers. By assuming an underlying GMPLS-enabled network infrastructure connecting a number of geographically dispersed data centers, in this paper we define an architectural framework that allows infrastructure providers to optimally use their resources to provide Virtual Infrastructures on demand. The architecture we propose is designed as an extension of the standard Path Computation Element (PCE) architecture. A centralized entity, named VRO, is responsible for optimally allocating the physical resources needed to deploy a requested Virtual Infrastructure. In the paper, we also present how it is possible to apply our framework to pursue green management objectives so that OPEX expenditures can be reduced, while preserving contractual SLAs. We also describe a prototype of our framework that is able to configure GMPLS-enabled network nodes and Cloud-enabled data centers in order to create Virtual Infrastructures.

A service-aware virtualized software-defined infrastructure

The Internet infrastructure is gradually improving its flexibility and adaptability due to the incorporation of new promising technologies, such as the software-defined networks and the network function virtualization. The main goal is to meet the diverse communication needs of the users, while the global system operation satisfies the business and societal goals of the infrastructure and service providers. This calls for solutions that consider both local and global network viewpoints and provide sophisticated system control in a stable and predictable way, while being service-aware. We propose a fully integrated solution along these lines: the VLSP, a service-aware software-defined infrastructure for networks and clouds. The VLSP consists of three main distributed systems: a facility performing uniformly logically-centralized management and control of the infrastructure, called the virtual infrastructure management; an information management infrastructure able to maintain an accurate view of the infrastructure environment at both the local and system levels, called the virtual infrastructure information service; and a lightweight virtualization hypervisor able to perform configuration changes in the infrastructure resources, called the lightweight network hypervisor. We discuss representative use-case scenarios, while we demonstrate how VLSP tunes performance trade-offs for particular service demands.

On Achieving High Survivability in Virtualized Data Centers

As businesses are increasingly relying on the cloud to host their services, cloud providers are striving to offer guaranteed and highly-available resources. To achieve this goal, recent proposals have advocated to offer both computing and networking resources in the form of Virtual Data Centers (VDCs). Subsequently, several attempts have been made to improve the availability of VDCs through reliability-aware resource allocation schemes and redundancy provisioning techniques. However, the research to date has not considered the heterogeneity of the underlying physical components. Specifically, it does not consider recent findings showing that failure rates and availability of data center equipments can vary significantly depending on various parameters including their types and ages. To address this limitation, in this paper we propose a High-availability Virtual Infrastructure management framework (Hi-VI) that takes into account the heterogeneity of cloud data center equipments to dynamically provision backup resources in order to ensure required VDC availability. Specifically, we propose a technique to compute the availability of a VDC that considers both (1) the heterogeneity of data center networking and computing equipments in terms of failure rates and availability, and (2) the number of redundant virtual nodes and links provisioned as backups. We then leverage this technique to propose an allocation scheme that jointly provisions resources for VDCs and backups of virtual components with the goal of achieving the required VDC availability while minimizing energy costs. Through simulations, we demonstrate the effectiveness of our framework compared to heterogeneity-oblivious solutions.

Efficient autonomic cloud computing using online discrete event simulation

Interest is growing in open source tools that let organizations build IaaS clouds using their own internal infrastructures, alone or in conjunction with external ones. A key component in such private/hybrid clouds is virtual infrastructure management, i.e., the dynamic orchestration of virtual machines, based on the understanding and prediction of performance at scale, with uncertain workloads and frequent node failures. Part of the research community is trying to solve this and other IaaS problems looking to Autonomic Computing techniques, that can provide, for example, better management of energy consumption, quality of service (QoS), and unpredictable system behaviors. In this context, we first recall the main features of the NAM framework devoted to the design of distributed autonomic systems. Then we illustrate the organization and policies of a NAM-based Workload Manager, focusing on one of its components, the Capacity Planner. We show that, when it is not possible to obtain optimal energy-aware plans analytically, sub-optimal plans can be autonomically obtained using online discrete event simulation. Specifically, the proposed approach allows to cope with a broader range of working conditions and types of workloads.

CyberGuarder: A virtualization security assurance architecture for green cloud computing

As the sizes of IT infrastructure continue to grow, cloud computing is a natural extension of virtualisation technologies that enable scalable management of virtual machines over a plethora of physically connected systems. The so-called virtualisation-based cloud computing paradigm offers a practical approach to green IT/clouds, which emphasise the construction and deployment of scalable, energy-efficient network software applications ( NetApp) by virtue of improved utilisation of the underlying resources. The latter is typically achieved through increased sharing of hardware and data in a multi-tenant cloud architecture/environment and, as such, accentuates the critical requirement for enhanced security services as an integrated component of the virtual infrastructure management strategy. This paper analyses the key security challenges faced by contemporary green cloud computing environments, and proposes a virtualisation security assurance architecture, CyberGuarder, which is designed to address several key security problems within the ‘green’ cloud computing context. In particular, CyberGuarder provides three different kinds of services; namely, a virtual machine security service, a virtual network security service and a policy based trust management service. Specifically, the proposed virtual machine security service incorporates a number of new techniques which include (1) a VMM-based integrity measurement approach for NetApp trusted loading, (2) a multi-granularity NetApp isolation mechanism to enable OS user isolation, and (3) a dynamic approach to virtual machine and network isolation for multiple NetApp’s based on energy-efficiency and security requirements. Secondly, a virtual network security service has been developed successfully to provide an adaptive virtual security appliance deployment in a NetApp execution environment, whereby traditional security services such as IDS and firewalls can be encapsulated as VM images and deployed over a virtual security network in accordance with the practical configuration of the virtualised infrastructure. Thirdly, a security service providing policy based trust management is proposed to facilitate access control to the resources pool and a trust federation mechanism to support/optimise task privacy and cost requirements across multiple resource pools. Preliminary studies of these services have been carried out on our iVIC platform, with promising results. As part of our ongoing research in large-scale, energy-efficient/green cloud computing, we are currently developing a virtual laboratory for our campus courses using the virtualisation infrastructure of iVIC, which incorporates the important results and experience of CyberGuarder in a practical context.

Performance Issues in Clouds: An Evaluation of Virtual Image Propagation and I/O Paravirtualization

As a technology, cloud computing has become an IT buzzword for the past few years. Cloud computing has often been used with synonymous terms such as software as a service, platform as a service, and infrastructure as a service (IaaS). Cloud computing has the potential to advance research discoveries by making data and computing resources readily available at an unprecedented economy of scale and with tremendous scalability. This paper discusses the importance of QoS and Iaas performance in cloud computing. The results of a quantitative evaluation are presented into the performance overheads of propagating virtual machine (VM) images to physical resources, at the Iaas layer and then accessing the images, via a Hypervisor's virtual block I/O device. Two virtual infrastructure managers are evaluated: Nimbus and OpenNebula, alongside two VM managers: XEN and KVM. Nimbus is found to outperform OpenNebula, while XEN outperforms KVM in the majority of cases. Conclusions are drawn from the results on the suitability of these technologies for data-intensive applications and applications requiring highly dynamic resource sets, where making an uninformed decision on what technology to use could prevent an application reaching its full potential, once deployed onto a cloud.