Robert de Groote

Sharing enriched multimedia experiences across heterogeneous network infrastructures

Todays consumers have a wide variety of interactive media and services at their disposal, for instance, through IPTV networks, the Internet, and in-home and mobile networks. A major problem, however, is that media and services do not interoperate across networks because they use different user identities, metadata formats, and signaling protocols, for example. As a result, users cannot easily combine media and services from different network infrastructures and share them in an integrated manner with their family and friends. In addition to limiting peoples media experience, this also hinders the introduction of new services and business models as providers cannot easily develop and operate cross-network services. The goal of our work is to overcome this problem by means of an open and intelligent service platform that allows applications to easily combine media and services from different network infrastructures, and enables consumers to easily share them in an integrated way. The platform includes support for managing multi-user sessions across networks, context-aware recommendations, and cross-network identity management. While there has been prior work on platforms for converged media, our platform is unique in that it provides open, intelligent, and interoperable facilities for sharing media and services across network infrastructures. In addition, our work involves several specific innovations, for instance, pertaining to cross-network session management and synchronization. In this article we discuss the platform, its most important enabling services, and some of the applications we have built on top of it. We also briefly consider the new kinds of business models our platform makes possible.

Max-Plus Algebraic Throughput Analysis of Synchronous Dataflow Graphs

In this paper we present a novel approach to throughput analysis of synchronous dataflow (SDF) graphs. Our approach is based on describing the evolution of actor firing times as a linear time-invariant system in max-plus algebra. Experimental results indicate that our approach is faster than state-of-the-art approaches to throughput analysis of SDF graphs. The efficiency of our approach is due to an exploitation of the regular structure of the max-plus systems graphical representation, the properties of which we thoroughly prove.

Resource-Constrained Optimal Scheduling of Synchronous Dataflow Graphs via Timed Automata

Synchronous dataflow (SDF) graphs are a widely used formalism for modelling, analysing and realising streaming applications, both on a single processor and in a multiprocessing context. Efficient schedules are essential to obtain maximal throughput under the constraint of available resources. This paper presents an approach to schedule SDF graphs using a proven formalism of timed automata (TA). TA maintain a good balance between expressiveness and tractability, and are supported by powerful verification tools, e.g. UPPAAL. We describe a compositional translation of SDF graphs to TA, and perform analysis and verification in the UPPAAL state-of-the-art tool. This approach does not require the (exponential) transformation of SDF graphs to homogeneous SDF graphs and helps to find schedules with a trade-off between the number of processors required and the throughput. It also allows quantitative model checking and verification of (preservation of) user-defined properties such as the absence of deadlocks, safety, liveness and throughput analysis. This translation also forms the basis for future work to extend this analysis of SDF graphs with new features such as stochastics, energy consumption and costs.

Introducing and Exploiting Hierarchical Structural Information

This paper presents a programming model approach that explicitly addresses the programmability of scientific code by annotating imperative code with its algorithmic structural behavior. This information is used to create hierarchical structures, as opposed to the flat structure that most programming models work with, which allows sound code transformation at any level of the code, adjusting the granularity of parallelization simultaneously with other parameters to better exploit the available hardware resources.

Incremental Analysis of Cyclo-Static Synchronous Dataflow Graphs

In this article, we present a mathematical characterisation of admissible schedules of cyclo-static dataflow (<scp>csdf</scp>) graphs. We demonstrate how algebra ic manipulation of this characterization is related to unfolding <scp>csdf</scp> actors and how this manipulation allows <scp>csdf</scp> graphs to be transformed into <scp>mrsdf</scp> graphs that are <i>equivalent</i>, in the sense that they admit the same set of schedules. The presented transformation allows the rich set of existing analysis techniques for <scp>mrsdf</scp> graphs to be applied to <scp>csdf</scp> graphs and generalizes the well-known transformations from <scp>csdf</scp> and <scp>mrsdf</scp> into <scp>hsdf</scp>. Moreover, it gives rise to an incremental approach to the analysis of <scp>csdf</scp> graphs, where approximate analyses are combined with exact transformations. We show the applicability of this incremental approach by demonstrating its effectiveness on the problem of optimizing buffer sizes under a throughput constraint.

Single-rate approximations of cyclo-static synchronous dataflow graphs

Exact analysis of synchronous dataflow (sdf) graphs is often considered too costly, because of the expensive transformation of the graph into a single-rate equivalent. As an alternative, several authors have proposed approximate analyses. Existing approaches to approximation are based on the operational semantics of an sdf graph. We propose an approach to approximation that is based on functional semantics. This generalises earlier work done on multi-rate sdf graphs towards cyclo-static sdf (csdf) graphs. We take, as a starting point, a mathematical characterisation, and derive two transformations of a csdf graph into hsdf graphs. These hsdf graphs have the same size as the csdf graph, and are approximations: their respective temporal behaviours are optimistic and pessimistic with respect to the temporal behaviour of the csdf graph. Analysis results computed for these single-rate approximations give bounds on the analysis results of the csdf graph. As an illustration, we show how these single-rate approximations may be used to compute bounds on the buffer sizes required to reach a given throughput.

Multi-rate Equivalents of Cyclo-Static Synchronous Dataflow Graphs

In this paper, we present a transformation that takes a cyclo-static dataflow (CSDF) graph and produces an equivalent multi-rate synchronous dataflow (MRSDF) graph. This fills a gap in existing analysis techniques for synchronous dataflow graphs, transformations into equivalent homogeneous synchronous dataflow (HSDF) graphs exist, but these suffer from an exponential increase in the graphs size. The presented transformation allows the rich set of existing analysis techniques for MRSDF graphs to be applied to CSDF graphs. We show the applicability of this transformation by demonstrating its effectiveness on the problem of optimising buffer sizes under a throughput constraint.