Use of the serverless paradigm in cloud application development is growing rapidly, primarily driven by its promise to free developers from the responsibility of provisioning, operating, and scaling the underlying infrastructure. However, modern cloud-edge infrastructures are characterized by large numbers of disparate providers, constrained resource devices, platform heterogeneity, infrastructural dynamicity, and the need to orchestrate geographically distributed nodes and devices over public networks. This presents significant management complexity that must be addressed if serverless technologies are to be used in production systems. This position paper introduces COGNIT, a major new European initiative aiming to integrate AI technology into cloud-edge management systems to create a Cognitive Cloud reference framework and associated tools for serverless computing at the edge. COGNIT aims to: 1) support an innovative new serverless paradigm for edge application management and enhanced digital sovereignty for users and developers; 2) enable on-demand deployment of large-scale, highly distributed and self-adaptive serverless environments using existing cloud resources; 3) optimize data placement according to changes in energy efficiency heuristics and application demands and behavior; 4) enable secure and trusted execution of serverless runtimes. We identify and discuss seven research challenges related to the integration of serverless technologies with multi-provider Edge infrastructures and present our vision for how these challenges can be solved. We introduce a high-level view of our reference architecture for serverless cloud-edge continuum systems, and detail four motivating real-world use cases that will be used for validation, drawing from domains within Smart Cities, Agriculture and Environment, Energy, and Cybersecurity. 

Data centers are complex systems that require sophisticated operational management approaches to provide the availability of digital services against the backdrop of cost and energy efficiency. To achieve this, data center telemetry data is required since, as is commonly said it is not possible to manage what cannot be measured. This paper details how it is possible to construct the key data center infrastructure management (DCIM) elements of monitoring and measuring by a combination of available opensource software tools that permit both scalability and an environment where analytics can be employed on the data center operation, which can offer relevant insight into energy efficient operational practices.

Popular media events of today are likely to attract a big, live audience. Being part of a huge cricket audience, for example, knowing that the event is broadcast to perhaps millions of people, is a truly arousing experience. But the size of the audience and the complexity of events do not come without drawbacks. Spectators find it difficult to be at the right spot at the right time and to grasp the essentials of the on goings. We introduce a Media Event Platform, which combines various sources of event crucial information and lets the mobile user choose from a number of different channels; WAP-phones, web browsers, digital radio, and SMS. This paper adds to the existing body of research by offering a novel multi channel system design for boosting event experiences and provides an early example of how mobile technology influences converging media forms. Further, we report from a user evaluation conducted in order to find implications for design improvements, and describe possible commercial potential.