RECAP - Reliable Capacity Provisioning and Enhanced Remediation for Distributed Cloud Applications

Project start: 
Sunday, 1 May, 2016
Project end: 
Monday, 31 December, 2018

The RECAP project develops a radically novel concept in the provision of cloud services, where services are elastically instantiated and provisioned close to the users that actually need them via self-configurable cloud computing systems.

Who is the service/solution designed for?: 

Operators of data centers and Tier 1 hyperscale cloud service providers.

How will your solution/service benefit the end-user? 

The principal objective of RECAP is to reverse the current common practice to provide cloud-based services by allocating data centre resources on a best-effort basis. While recent years have seen significant advances in system instrumentation as well as data centre energy efficiency and automation, computational resources and network capacity are often provisioned using best-effort models and coarse-grained quality-of-service (QoS) mechanisms, even in state-of-the-art data centres.

These limitations are seen as a major hindrance in the face of the coming evolution of the Internet of Things (IoT) and the networked society, which are projected to significantly increase the load on networks and data centres, as well as require a much higher degree of intelligent automation.

How can the solution/service help you become more efficient, more secure, faster or cost-effective?: 

RECAP aims to advance cloud and edge computing technology by making application placement, infrastructure management, and capacity provisioning autonomous, predictable and optimized. It incorporates a much more elastic model, which delivers services and allocates resources in a dynamic manner, tied to time-varying user requirements.

This will ensure that communication critical applications will always achieve their goals without unnecessary delays, no matter where they are located. This, in turn, will minimise operational costs and improve effectiveness and energy efficiency of data center resources.