Abstract
This paper extends the work presented in Maia et al. (Semi-partitioned scheduling of fork-join tasks using work-stealing, 2015) where we address the semi-partitioned scheduling of real-time fork-join tasks on multicore platforms. The proposed approach consists of two phases: an offline phase where we adopt a multi-frame task model to perform the task-to-core mapping so as to improve the schedulability and the performance of the system and an online phase where we use the work-stealing algorithm to exploit tasks' parallelism among cores with the aim of improving the system responsiveness. The objective of this work is twofold: (1) to provide an alternative scheduling technique that takes advantage of the semi-partitioned properties to accommodate fork-join tasks that cannot be scheduled in any pure partitioned environment and (2) to reduce the migration overheads which has been shown to be a traditional major source of non-determinism for global scheduling approaches. In this paper, we consider different allocation heuristics and we evaluate the behavior of two of them when they are integrated within our approach. The simulation results show an improvement up to 15% of the proposed heuristic over the state-of-the-art in terms of the average response time per task set.

Abstract

Abstract
The Network-on-Chip (NoC) architecture is an interconnect network with a good performance and scalability potential. Thus, it comes as no surprise that NoCs are among the most popular interconnect mediums in nowadays available many-core platforms. Over the years, the real-time community has been attempting to make NoCs amenable to the real-time analysis. One such approach advocates to employ virtual channels. Virtual channels are hardware resources that can be used as an infrastructure to facilitate flit-level preemptions between communication traffic flows. This gives the possibility to implement priority-preemptive arbitration policies in routers, which is a promising step towards deriving real-time guarantees for NoC traffic. So far, various aspects of priority-preemptive NoCs were studied, such as arbitration, priority assignment, routing, and workload mapping. Due to a potentially large solution space, the majority of available techniques are heuristic-centric, that is, either pure heuristics, or heuristic-based search strategies are used. Such approaches may lead to an inefficient use of hardware resources, and may cause a resource over-provisioning as well as unnecessarily high design-cost expenses. Motivated by this reality, we take a different approach, and propose an integer linear program to solve the problems of priority assignment and routing of NoC traffic. The proposed method finds optimal routes and priorities, but also allows to reduce the search space (and the computation time) by fixing either priorities or routes, and derive optimal values for remaining parameters. This framework is used to experimentally evaluate both the scalability of the proposed method, as well as the efficiency of existing priority assignment and routing techniques. © 2017 Springer Science+Business Media New York

Abstract
More and more cyber-physical systems and the internet of things push for a multitude of devices and systems, which need to work together to provide the services as required by the users. Nevertheless, the speed of development and the heterogeneity of devices introduces considerable challenges in the development of such systems. This paper describes a solution being implemented in the setting of a serious game scenario, connected to real homes energy consumption. The solution provides a publish-subscribe middleware which is able to seamlessly connect all the components of the system.

Abstract
Smart governance is one of the characteristics of smart cities, having its roots in e-government, in the principles of good governance, and in the assumptions of citizens' participation and involvement in public decision-making. This chapter aims to answer the question: “What smart governance practices are being implemented in smart cities” through an extensive literature review in the areas of e-government, good governance, smart cities and smart governance, and content analysis of the websites of seven smart cities: Amsterdam, Barcelona, Copenhagen, Lisbon, Manchester, Singapore, and Stockholm. The objective was to identify the presence of factors related with e-participation; e-services; and public administration functioning on the cities' websites. The chapter ends with directions for future research and the conclusion that all the smart cities analyzed presented some factors related with smart governance, but with different levels of development and application.

Abstract
With an advancement towards the paradigm of Internet of Things (IoT), in which every device will be interconnected and communicating with each other, the field of wireless sensor networks has helped to resolve an ever-growing demand in meeting deadlines and reducing power consumption. Among several standards that provide support for IoT, the recently published IEEE 802.15.4e protocol is specifically designed to meet the QoS requirements of industrial applications. IEEE 802.15.4e provides five Medium-Access Control (MAC) behaviors, including three that target time-critical applications: Deterministic and Synchronous Multichannel Extension (DSME); Time Slotted Channel Hopping (TSCH) and Low Latency Deterministic Network (LLDN). However, the standard and the literature do not provide any worst-case bound analysis of these behaviors, thus it is not possible to effectively predict their timing performance in an application and accurately devise a network in accordance to such constraints. This paper fills this gap by contributing network models for the three time-critical MAC behaviors using Network Calculus. These models allow deriving the worst-case performance of the MAC behaviors in terms of delay and buffering requirements. We then complement these results by carrying out a thorough performance analysis of these MAC behaviors by observing the impact of different parameters. © 2017 IEEE.