Nowadays, we are witnessing the diffusion of Stream Processing Systems (SPSs) able to analyze data streams in near realtime. Traditional SPSs likeStormandFlinktarget distributed clusters and adopt thecontinuous streaming model, where inputs are processed as soon as they are available while outputs are continuously emitted. Recently, there has been a great focus on SPSs for scale-up machines. Some of them (e.g.,BriskStream) still use the continuous model to achieve low latency. Others optimize throughput with batching approaches that are, however, often inadequate to minimize latency for live-streaming applications. Our contribution is to show a novel software engineering approach to design the runtime system of SPSs targeting multicores, with the aim of providing a uniform solution able to optimize throughput and latency. The approach has a formal nature based on the assembly of components calledbuilding blocks, whose composition allows optimizations to be easily expressed in a compositional manner. We use this methodology to build a new SPS calledWindFlow. Our evaluation showcases the benefits ofWindFlow: it provides lower latency than SPSs for continuous streaming, and can be configured to optimize throughput, to perform similarly and even better than batch-based scale-up SPSs.

Parallel programmers mandate high-level parallel programming tools allowing to reduce the effort of the efficient parallelization of their applications. Parallel programming leveraging parallel patterns has recently received renovated attention thanks to their clear functional and parallel semantics. In this work, we propose a synergy between the well-known Actors-based programming model and the pattern-based parallelization methodology. We present our preliminary results in that direction, discussing and assessing the implementation of the Map parallel pattern by using an Actor-based software accelerator abstraction that seamlessly integrates within the C++ Actor Framework (CAF). The results obtained on the Intel Xeon Phi KNL platform demonstrate good performance figures achieved with negligible programming efforts.

Summary How to flexibly manage complex applications across heterogeneous cloud platforms is one of the main concerns in today's IT enterprise. The OASIS standard TOSCA (Topology and Orchestration Specification for Cloud Applications) and the Docker ecosystem are two emerging solutions trying to address this problem from different perspectives. In this paper, we propose a solution that tries to synergically combine the pros of both TOSCA and of Docker. More precisely, we propose a TOSCA‐based representation for specifying the software components and the Docker containers forming an application. We also present TosKer, an engine for orchestrating the management of multicomponent applications based on the proposed TOSCA representation and on Docker. Finally, we illustrate how TosKer was fruitfully exploited in a concrete case study based on a third‐party application.