MEDAL: An AI-Driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence

Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective. Consequently, Edge Computing opportunities are lost due to cumbersome and data assets-agnostic processes for end-to-end deployment over the Cloud-to-Edge continuum. In this paper, we introduce MEDAL, an intelligent Cloud-to-Edge Data Fabric to support Data Operations (DataOps)across the continuum and to automate management and orchestration operations over a combined view of the data and the resource layer. MEDAL facilitates building and managing data workflows on top of existing flexible and composable data services, seamlessly exploiting and federating IaaS/PaaS/SaaS resources across different Cloud and Edge environments. We describe the MEDAL Platform as a usable tool for Data Scientists and Engineers, encompassing our concept and we illustrate its application though a connected cars use case

Programmable Edge-to-Cloud Virtualization for 5G Media Industry: The 5G-MEDIA Approach

To ensure high Quality of Experience (QoE) for end users, many media applications require significant quantities of computing and network resources, making their realization challenging in resource constrained environments. In this paper, we present the approach of the 5G-MEDIA project, providing an integrated programmable service platform for the development, design and operations of media applications in 5G networks, facilitating media service management across the service life cycle. The platform offers tools to service developers for efficient development, testing and continuous correction of services. One step further, it provides a service virtualization platform offering horizontal services, such as a Media Service Catalogue and accounting services, as well as optimization mechanisms to flexibly adapt service operations to dynamic conditions with efficient use of infrastructure resources. The paper outlines three use cases where the platform was tested and validated

Towards Serverless NFV for 5G Media Applications

The advent of virtualization and IaaS have revolutionized the telecom industry via SDN/NFV. A new wave of cloud-native PaaS promises to further improve SDN/NFV performance, portability, and cost-efficiency. In this poster, we highlight a work in progress being done in the 5G-MEDIA project [2], which pioneers the application of the serverless paradigm to NFV in the context of media intensive applications in 5G networks. Motivational use cases include tele-immersive gaming, mobile journalism and UHD content distribution. For example, consider a next-gen e-sport, in which bouts between gamers last only a few minutes. FaaS offers a clear cost-efficiency benefit for hosting such applications. An architecture is shown in Fig. 1. It includes i) an Application/Service Development Kit (SDK) to enable access to media applications development tools; ii) a Service Virtualization Platform (SVP) to run the ETSI MANO framework, the Media Service MAPE optimization component and the VIM and WIM plugins to enable NFVIs integration; iii) different NFVIs to execute media-specific VNFs. FaaS VIM is implemented for integration of FaaS with the rest of the MANO stack. It allows mixing FaaS and "regular" VNFs within the same media forwarding graph. For reference implementation, Apache OpenWhisk [1] and Kubernetes are used. The main challenge is extending the programming model to support groups of actions communicating over a network, while retaining the simplicity of FaaS

A service platform architecture enabling programmable edge-to-cloud virtualization for the 5G Media industry

Media applications are amongst the most demanding services in terms of resources, requiring huge network capacity for high bandwidth audio-visual and other mobile sensory streams. The 5G-MEDIA project aims at innovating media-related applications by investigating how these applications and the underlying 5G network should be coupled and interwork to the benefit of both. The 5G-MEDIA approach aims at delivering an integrated programmable service platform for the development, design and operations of media applications in 5G networks by providing mechanisms to flexibly adapt service operations to dynamic conditions and react upon events (e.g. to transparently accommodate auto-scaling of resources, VNF replacement, etc.). In this paper we present the 5G-MEDIA service platform architecture, which has been specifically designed to enable the development and operation of services for the nascent 5G media industry. Our approach delivers an integrated programmable service platform for the development, design and operations of media applications in 5G networks

Cloud computing and RESERVOIR project

The support for complex services delivery is becoming a key point in current internet technology. Current trends in internet applications are characterized by on demand delivery of ever growing amounts of content. The future internet of services will have to deliver content intensive applications to users with quality of service and security guarantees. This paper describes the RESERVOIR project and the challenge of a reliable and effective delivery of services as utilities in a commercial scenario. It starts by analyzing the needs of a future infrastructure provider and introducing the key concept of a service oriented architecture that combines virtualisation-aware grid with grid-aware virtualisation, while being driven by business service management. This article will then focus on the benefits and the innovations derived from the RESERVOIR approach. Eventually, a high level view of RESERVOIR general architecture is illustrated

MEDAL: An AI-Driven Data Fabric Concept for Elastic Cloud-to-Edge Intelligence

© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.Current Cloud solutions for Edge Computing are inefficient for data-centric applications, as they focus on the IaaS/PaaS level and they miss the data modeling and operations perspective. Consequently, Edge Computing opportunities are lost due to cumbersome and data assets-agnostic processes for end-to-end deployment over the Cloud-to-Edge continuum. In this paper, we introduce MEDAL—an intelligent Cloud-to-Edge Data Fabric to support Data Operations (DataOps) across the continuum and to automate management and orchestration operations over a combined view of the data and the resource layer. MEDAL facilitates building and managing data workflows on top of existing flexible and composable data services, seamlessly exploiting and federating IaaS/PaaS/SaaS resources across different Cloud and Edge environments. We describe the MEDAL Platform as a usable tool for Data Scientists and Engineers, encompassing our concept and we illustrate its application though a connected cars use case