The paper proposes a surrogate model for liquid moulding of structural composites. A methodology is presented to simulate the dual-phase Darcy’s flow in a heterogeneous porous medium. The approach is an encoder–decoder that receives as input a matrix of permeabilities and produces two scalar fields that represent the pressure and front flow. This model is trained with synthetic data generated with a computer fluid dynamics simulator. In this context, the lack of robustness of models trained with the popular L2 and L1 losses is highlighted and several enhancements to these baseline approaches are introduced. First, the study provides a piece-wise power-logarithmic loss that improves training in the presence of the bimodal distribution of error residuals produced by the dual-phase flow predictions. A non-uniform sampling strategy for the selection of time training snapshots is also included, which contributes to improve the prediction accuracy. The estimation of the front flow field is further refined with a multi-task training strategy. The introduction of these improvements in the baseline models reduce the relative error of the pressure and front flow fields by more than 50%, performing these simulations in a record time of 50 ms. The surrogate model is further evaluated as a digital twin to predict – in a real experiment – the location and spatial extent of race-tracking channels and regions with dissimilar degrees of permeability.

Event-driven architectures are becoming more prevalent recently in multiple technological paradigms, especially in web applications, with message brokers being the cornerstone of these architectures. One of the most relevant implementations of these message brokers are content-based publish/subscribe systems. The performance of these systems is a critical factor for web engineering, since the web applications they support need to be reactive despite increases and fluctuations in workloads. However, an obstacle to the research of these systems is the lack of real and publicly available workloads, due to the privacy issue involved in disclosing the interests (subscriptions) of users and other commercial interests of the companies. In this paper we present a parameterizable automated system designed to syntactically translate workloads from different content-based publish/subscribe systems as a means to increase the availability of public workloads to solve the aforementioned problem. As a case study, we describe the evolution of a context-aware content-based publish/subscribe system (i.e. E-SilboPS) designed by the authors, which improves up to 5 times the performance of its previous version by reaching the maximum throughput limited by the physical resources of the hardware where it is deployed, as demonstrated by the conducted quantitative evaluation. Then, we validate the utility of the proposed automated workload generation system by using it to make the performance comparison between this new version E-SilboPS and one of the most cited publish/subscribe systems called PADRES, through a real trace of a massively multiplayer online game (MMOG) generated by the latter.

This paper describes the architecture of a proposed multiparty conferencing system for satellites. Different conferencing models are discussed and compared. A session initiation protocol (SIP)-based conference signaling model and an extension to protocol-independent multicast sparse mode that supports quality-of-service (QoS) in DiffServ networks are proposed, as particularly suitable for multiparty conferencing applications over satellite links. The paper also presents key issues and potential solutions of scalable QoS multicast services for multiparty conferences over satellite. End-to-end QoS parameters for voice and video are measured and analyzed on a prototype.

Abstract A common characteristic of process algebras is that they permit us the partial description of concurrent systems by including non-deterministic behaviours. These non-deterministic components are abstractions of the actual ones, and they can be detailed in successive refinements. This paper proposes an enrichment of the above abstraction. It defines a formal description technique which is able to characterize the non-determinism in a probabilistic way. The proposed technique, called LOTOS-P is an upward compatible extension of LOTOS. The compatibility includes also the possibility of specifying non-deterministic behaviours; that is, without probabilistic characterization. The contents of the paper are mainly related to the definition of probabilistic models based on process algebras, and the study of the observable behaviour of systems by using testing relations. The advantage of the proposed model with respect to previous works is twofold. First, the model is simpler, and second, the compatibility with LOTOS is achieved. The simplicity does not make the model useless because its expressive power permits us to express random behaviours in the same way they are being expressed with classical techniques of discrete systems modeling. The probabilistic evaluation of the properties of the system can be done by applying the defined calculus, but also by simulation . Simulation means that we are able to obtain the desired results with a given confidence level.