Location, Proximity, Affinity – The Key Factors in FaaS

The Function-as-a-Service paradigm emerged not only as a pricing technique, but also as a programming model promising to simplify developing to the cloud. Interestingly, while placing functions across hosts under the service platform is believed to be flexible, currently the available platforms pay little attention to co-locate connected functions, or data with the respective processing function in order to improve performance. Even though the local function invocation and data access might be an order of magnitude faster than their remote intra-cloud counterparts. In this paper, we therefore propose a Function-asa- Service platform design that reaps the performance benefits of co-location. We build the platform on WebAssembly, a secure and flexible tool for efficient local function invocations, and on a distributed in-memory database, which allows arbitrary data placement. On top we advocate smart placement strategies for function executions and data, decoupled from the functions. Hence we envision good horizontal scaling of functions while keeping the experienced processing latency to that of a single machine case

On the Tradeoff between Effectiveness and Scalability of Measurement-based Admission Control

One of the key problems to be solved in Mesurement-Based Admission Control is to efficiently utilise the information provided by the sources and measured by the network. There is a direct relationship between the amount of information available and the resulting effectiveness of the admission algorithm. In this paper we analyse the tradeoff between complexity and effectiveness using a practial class of AC methods in the context of Differentiated Services Internet