Towards realistic core-failure-resilient scheduling and analysis

Presented at IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

Towards realistic core-failure-resilient scheduling and analysis

Presented at IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

Real-Time Support in the Proposal for Fine-Grained Parallelism in Ada

Presented at Work in Progress Session, IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 3, Dec, 2015. San Antonio, U.S.A..

Energy-aware Task Allocation onto Unrelated Heterogeneous Multicore Platform for Mixed Criticality Systems

Presented at Work in Progress Session, IEEE Real-Time Systems Symposium (RTSS 2015). 1 to 4, Dec, 2015. San Antonio, U.S.A..

Embedded Multi-Core systems for Mixed Criticality applications in dynamic and changeable real-time environments

EMC2 finds solutions for dynamic adaptability in open systems. It provides handling of mixed criticality multicore applications in r eal-time conditions, withscalability and utmost flexibility, full-scale deployment and management of integrated tool chains, through the entire lifecycle.

Dependable Embedded Wireless Infrastructure

DEWI will provide key solutions for wireless seamless connectivity and interoperability in the everyday physical environment of citizens, thereby significantly contributing to the emerging smart home and smart public space.

Message-oriented middleware for smart grids

In order to increase the efficiency in the use of energy resources, the electrical grid is slowly evolving into a smart(er) grid that allows users' production and storage of energy, automatic and remote control of appliances, energy exchange between users, and in general optimizations over how the energy is managed and consumed. One of the main innovations of the smart grid is its organization over an energy plane that involves the actual exchange of energy, and a data plane that regards the Information and Communication Technology (ICT) infrastructure used for the management of the grid's data. In the particular case of the data plane, the exchange of large quantities of data can be facilitated by a middleware based on a messaging bus. Existing messaging buses follow different data management paradigms (e.g.: request/response, publish/subscribe, data-oriented messaging) and thus satisfy smart grids' communication requirements at different extents. This work contributes to the state of the art by identifying, in existing standards and architectures, common requirements that impact in the messaging system of a data plane for the smart grid. The paper analyzes existing messaging bus paradigms that can be used as a basis for the ICT infrastructure of a smart grid and discusses how these can satisfy smart grids' requirements.

mRPL: Boosting mobility in the Internet of Things

The 6loWPAN (the light version of IPv6) and RPL (routing protocol for low-power and lossy links) protocols have become de facto standards for the Internet of Things (IoT). In this paper, we show that the two native algorithms that handle changes in network topology – the Trickle and Neighbor Discovery algorithms – behave in a reactive fashion and thus are not prepared for the dynamics inherent to nodes mobility. Many emerging and upcoming IoT application scenarios are expected to impose real-time and reliable mobile data collection, which are not compatible with the long message latency, high packet loss and high overhead exhibited by the native RPL/6loWPAN protocols. To solve this problem, we integrate a proactive hand-off mechanism (dubbed smart-HOP) within RPL, which is very simple, effective and backward compatible with the standard protocol. We show that this add-on halves the packet loss and reduces the hand-off delay dramatically to one tenth of a second, upon nodes’ mobility, with a sub-percent overhead. The smart-HOP algorithm has been implemented and integrated in the Contiki 6LoWPAN/RPL stack (source-code available on-line mrpl: smart-hop within rpl, 2014) and validated through extensive simulation and experimentation.

Feature Extraction in Densely Sensed Environments: Extensions to Multiple Broadcast Domains

The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with a low overhead. In this article, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.