Deliverable D3.1. Initial Requirements

A second public deliverable “Initial Requirements” is available for download. This deliverable summarises the constraints, wishes, and requirements of each of the use cases towards the RECAP project and the test bed operators. Particularly, it identifies functional requirements and defines the technical and business frame of the use cases. The report gives an overview of each use cases and describes the business setting including the value chains. Furthermore, it clarifies the currently existing, technical pre-RECAP set-up and pain points that it faces. Based on the pain points, use cases describe user stories that tell how the existence of RECAP helps the use cases stakeholders. It also details the data sets use cases provide to RECAP. These descriptions include meta-information on the data including data rate, data size, and legal aspects. Each use case section closes with a description of validation scenarios for the user stories and a summary of the impact of RECAP on the business setting.

In detail, this document contains description of four use cases:

  • Use Case A: Infrastructure and Network Management. Tieto provides innovative solutions for industries such as automotive, eCommerce and eHealth enabled by 4G-and-beyond, and mobile technologies in conjunction with fog/cloud computing. Tieto's use case will demonstrate through RECAP how the simulation of infrastructure, network function and service function characteristics can be automated to ensure the desired QoS for the different network services.
  • Use Case B: Big Data Analytics Engine. provides a special type of business intelligence known as 'competitive intelligence' or economic intelligence, by mining on hundreds of different types of scientific and industrial data sources. uses a composite, distributed architecture deployed in the cloud. In order to keep reduced response times during request peaks, Linknovate currently over-provisions nodes in the cloud. It is expected that this aspect can be optimized via RECAP's 'Dynamic provisioning' together with improving geolocation issues of the nodes serving Linknovate's portal.
  • Use Case-C: Edge/Fog Computing for Smart Cities. SATEC's work in smart cities focuses on extracting value from the growing 'local' data sources, which then needs to be hauled through data networks, stored and processed (as opposed to 'monitor only' solutions). This data is then moved back to the city data infrastructures, where they can be forwarded to the interested entities and authorities. RECAP will help with current challenges by identifying when the data produced in a local context could be stored and processed as close as possible to that context (i.e., to support large-scale IoT systems). This use case will demonstrate the capabilities of RECAP for automating the reallocation of resources close to the Edge/Fog computing in order to reduce the latency for their customers, and demonstrate cost savings /ease of management of resources for data centre operators.
  • Use Case D: Network Function Virtualisation. BT presents two Network Functions Virtualisation (NFV) use cases: Use Case D.1. 'virtual Content Distribution Networks' (vCDN) and Use Case D.2. 'Cloud Connect Intelligence' (CCI). NFV replaces physical network appliances with software running on servers.
  • Use Case D.1: vCDN help save physical space and power/energy consumption, and aim to replace the multiple customized physical caches with a standard server and storage running multiple virtual applications per CDN operator. Through RECAP (applying Machine Learning) this use case proposes to automate planning & operations and improve veracity, thereby improving efficiency of vCDN systems.
  • Use Case D.2: CCI adds the intelligence e.g. security (firewalls), WAN acceleration or optimisation, and traffic analytics. Understanding resources and developing a performance map for VNFs is of great importance. Via RECAP, use case owner BT proposes to achieve a better understanding of resources (i.e., performance map of VNFs) and to leverage the modeling and prediction capabilities of the RECAP framework for the early detection and remediation of faults in service chains.

Based on the user stories we narrow down further functional and non-functional requirements towards RECAP. These affect the development and construction of the testbeds and use of software packets: for instance, RECAP testbeds need to support both virtual machines and containers in data centre and edge settings. In addition, requirements demand for automated application handling, auto-scaling, monitoring, error detection, and re-location of workload. Finally, with respect to optimisation, they request support for planning and optimisation metrics.


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