Adaptive & learning-aware orchestration of content delivery services

Many media services undergo a varying workload, showing periodic usage patterns or unexpected traffic surges. As cloud and NFV services are increasingly softwarized, they enable a fully dynamic deployment and scaling behaviour. At the same time, there is an increasing need for fast and efficient mechanisms to allocate sufficient resources with the same elasticity, only when they are needed. This requires adequate performance models of the involved services, as well as awareness of those models in the involved orchestration machinery. In this paper we present how a scalable content delivery service can be deployed in a resource- and time-efficient manner, using adaptive machine learning models for performance profiling. We include orchestration mechanisms which are able to act upon the profiled knowledge in a dynamic manner. Using an offline profiled performance model of the service, we are able to optimize the online service orchestration, requiring fewer scaling iterations

Service specific management and orchestration for a content delivery network

Any non-trivial network service requires service specific orchestration to meet its carrier-grade requirements regarding resiliency, availability, etc. How the network service components are mapped on the substrate, how VNFs get reconfigured after a monitored event or how they scale, only network service/function developers know how to execute such workflows to guarantee an optimal QoS. It is therefore of paramount importance that NFV Service Platforms allow developer specified input when performing such life cycle events, instead of defining generic workflows. Within the scope of the SONATA and SGTANGO projects, a mechanism was designed that allows developers to create and execute Service and Function Specific Managers. These managers are processes, created by the developer, that define service or function specific orchestration behaviour. The SONATA Service Platform executes these managers to overwrite generic Service Platform behaviour, creating developer customised life cycle workflows. We will demonstrate the development, testing and operational execution of these managers by using a Content Delivery Network which requires specific placement and scaling behaviour

Intracellular Nanoparticle Coating Stability Determines Nanoparticle Diagnostics Efficacy and Cell Functionality

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Scalable monitoring for multiple virtualized infrastructures for 5G services

This paper presents a high level architecture and functionality details of the monitoring framework that has been implemented and integrated within the SONATA project, in order to support the management of 5G services under the Software Defined Networking / Network Function Virtualization (SDN/NFV) paradigm. The innovative framework, extending the functionality of Prometheus.io, is unique in its support for multiple Points of Presence (PoP), its extensibility using Websockets, and its availability as opensource

A model to select the right infrastructure abstraction for Service Function Chaining

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