Resource Virtualization Technologies Research Articles

The product quality inspection scheme based on software-defined edge intelligent controller in industrial internet of things

The Industrial Internet of Things (IIoT) enables the improvement of the productivity and intelligent level of factory. The procedure of product quality inspection has generally adopted machine intelligence algorithms instead of manual operation to improve efficiency. In this paper, we propose a product quality inspection system scheme based on software-defined edge intelligent controller (SD-EIC). By adopting the software definition and resource virtualization technologies, the hardware platform of SD-EIC is designed to support the real-time control tasks and non-real-time edge computing tasks at the same time. To this end, we propose the scheme and architecture of product quality inspection system based on SD-EIC. Multiple virtual controllers and virtual edge computing nodes are constructed on a set of SD-EIC hardware platform to realize the integrated deployment of the real-time control for terminal devices and the AI model reasoning of product defect recognition algorithm based on machine vision respectively. In addition, the management and control scheme of product quality inspection system based on industrial information model is proposed. By constructing the semantic-based digital twin information model of terminal device, the flexible adjustment and parameter configuration of terminal device are realized to meet the demands of flexible production and manufacturing. The proposed product quality inspection system solution can effectively improve the utilization of hardware resources and the efficiency of product quality inspection, and reduce the overall deployment cost of the system. It can flexibly adapt to product diversity and different industrial scenarios.

Advanced data analytics using three-stage intelligent model pipelining for containerized microservices in 5G networks and beyond

The recent rapid advancement of cloud-native networking infrastructure has leveraged the resource virtualization technology of containers to realize diverse microservice-based applications in 5G/6G networks and clouds. Containers drastically enhance the efficiency of computational resource allocation and utilization as compared to the related virtualization technology of Virtual Machines (VMs). The networking environment leveraging both VM and container mixed virtualization technologies makes the most use of them to realize a computational platform whose resources can be dynamically adjusted to a fine granularity. To continuously meet the required levels of quality of services in 5G/6G networks and clouds in that platform, an agile and autonomous data analytics system in the control plane is essential for the accurate prediction of server workloads and dynamic allocation of enough amount of computational resource. In this paper, we introduce a framework, which complies with Recommendation ITU-T Y.3177, for autonomous computational resource control and management. The framework consists of an advanced data analytics system and a resource control system. We propose an architecture for the advanced data analytics system consisting of learning and prediction components. The learning component includes a three-stage intelligent model pipelining with three cascaded machine learning models, nonlinear regression, clustering, and multiple regression. These models determine the fluctuation trends in CPU utilization, classify services with similarities in the trends, and predict the peak CPU utilization of each containerized microservice. We evaluate the proposed models through experiments and numerical analysis. The results prove that the models support agile data analytics, which can complete data processing in the time granularity of seconds and achieve higher prediction accuracy of CPU utilization.

SDN-Empowered Reliable and Dynamic Scheduling Scheme for Security Resources

By endowing network with the ability of reliable scheduling of security resources, it can realize the dynamic deployment of security resources as well as the efficient configuration of protection resources, and further can quickly respond to network security threats and emergencies timely. Furthermore, due to the network is increasingly complex, it is of great importance to make it reliable by invoking appropriate security resources. However, the security mechanism and response speed of traditional network based on security domain division, network boundary protection are hard to meet the requirements of the virtual network. In this paper, we propose the SDN-empowered reliable and dynamic scheduling scheme for security resources. In the scheme, we use network security resource virtualization technology to virtualize and modularize network security software and hardware resources; at the SDN control layer, we propose meta-security function combination technology to provide on-demand customization for various security applications’ security service; by using role-based conflict detection and conflict resolution technology, we can detect and handle security rule conflicts. The experiments show that the scheme is reliable and efficient with low latency and great throughput.

Reliability in cloud computing system: a review

As a new computing paradigm, cloud computing has attracts extensive concerns from both academic and industrial fields. Based on resource virtualization technology, cloud computing provides users with services in the forms of infrastructure, platform and software in a pay-as-you-go manner. In the meanwhile, since cloud computing provides highly scalable computing resources, more and more enterprises and organizations choose cloud computing platforms to deploy their scientific or commercial applications. However, with the increasing number of cloud users, cloud data centers continuously expand and the architecture becomes increasingly complex, leading to growing runtime failures in cloud computing systems. Therefore, how to ensure the system reliability in cloud computing systems with large scale and complex architecture has become a huge challenge. This paper first summarizes various failures in cloud systems, introduces several methods to evaluate the reliability of cloud computing, and describes some key fault management mechanisms. Since fault management techniques inevitably increase energy consumption of cloud systems, this paper reviews current researches on the trade-off between reliability and energy efficiency in cloud computing. In the end, we propose some major challenges in current research of cloud computing reliability and concludes our paper.

A Hybrid Virtualization Approach to Emulate Network Nodes of Heterogeneous Architectures

In the recent years, resource virtualization technologies of different types have been widely used in the ICT industry, particularly in cloud computing domain. These virtualization technologies can squeeze out hardware potential and consequently can significantly save CAPEX and OPEX. Virtualization technologies are adopted in network emulation to emulate heterogeneous nodes of target networks. At present, network emulators typically utilize legacy x86-based virtual machines (VMs) and light-weighted containers to emulate network nodes of heterogeneous architectures including ARM, SPARC, PPC, etc., which introduces software incompatibility to the original system software, protocols and applications, and may consequently jeopardize emulation fidelity. This paper focuses on mitigating the emulation incompatibility problem caused by node heterogeneity. Firstly, this problem is thoroughly investigated and analyzed on a cloud-based network emulation platform. Then, a hybrid virtualization approach concurrently utilizing multiple virtualization technologies, namely KVM, QEMU, and Docker to emulate heterogeneously architected nodes is derived and then implemented in the cloud-based network emulation platform. Functional verification and performance evaluation experiments have been carried out and have led to the conclusion that the elaborated hybrid virtualization approach can effectively dispose of the emulation incompatibility problem with affordable performance degradations. In addition, a case study of applying the hybrid virtualization approach to emulate a space-ground integrated network (SGIN) is conducted to show its effectivity and efficiency.

Manufactured by Software: SDN-Enabled Multi-Operator Composite Services with the 5G Exchange

Foreseen 5G verticals hold the promise of being true value-added services, hence bringing significant income to their respective providers. However, the nature of these verticals are very demanding in terms of both economic and technical requirements, such as multi-operator cooperation, end-to-end quality assurance, and the unified orchestration of network and cloud resources. Existing systems fall short of satisfying these requirements, but emerging network softwarization and resource virtualization technologies, such as SDN and NFV, show promise for being key enablers in this context. In this article, we introduce the 5G Exchange (5GEx) concept that builds on SDN and NFV, and facilitates the provisioning of multi-operator 5G services by means of inter-operator management and orchestration of virtualized network, compute, and storage resources. We present potential 5GEx use cases, conceptual architecture, and value proposition. We also outline open research questions on how to exchange information in such a coopetitive environment, and provide an outlook on the impact of 5GEx on a network service provider's business and operation.

Research of Resource Virtualization Technology Based on Cloud Manufacturing

A method of virtualization technology of manufacturing resources was analyzed and designed in Cloud Manufacturing environment toward the new type of networked manufacturing. Diverse-grained information such as the abstract, description, interface, packages have been put forward on basis of resource virtualization technology of manufacturing grid in order to implement resource virtualization. Virtualization of manufacturing hardware and software resources were mainly analyzed and researched in this paper. The primary research shows that this resource virtualization technology of Cloud Manufacturing can provide an important basis and premise for the further development of Cloud Manufacturing theory.

Virtualization of Grid Networking Resources for Computation Mobility Support

The paper analyses Grid networking resource virtualization technologies and requirements in the context of computational mobility. The mechanisms of network virtualization supported by Xen and xVM/Crossbow are presented and compared. A network virtualization model, consisting of three layers, is presented. Changes in virtual network infrastructures resulting from VM or zone mobility are investigated in detail. Typical migration process scenarios are presented, in addition to system commands used prior to and following migration in order to restore network communication. The concept of automating this process is also described.