PhD Thesis Defense - Ricardo GaribayA framework for the development of parallel and distributed real-time embedded systems
Faculdade de Engenharia da Universidade do Porto, Porto, Portugal
Real-time embedded systems are part of our everyday life. These systems range from the traditional areas of military and mission critical to domestic and entertainment applications. The aim of real-time systems is to execute applications in a way that those applications met their temporal constraints. Most of the results for real-time systems are based on the sequential real-time execution model, where intra-task parallelism is forbidden. In the last decade real-time researchers have started to focus their attention on the case of multi-threaded parallel real-time task models.
In these models, concurrent real-time activities are allowed to become parallel and to be processed in more than one processor at the same time.
Despite the fact that parallel computations in multi-processors can offer an increased processing capacity, the multi-threaded parallel real-time task models have not considered the cases in which a distributed execution also exists. Such execution pattern can be used to provide even more capabilities and processing power. Furthermore, in some applications the use of parallel distributed computations is the only possibility in which the applications can comply with their time constraints. An example of such type of applications are modern automotive applications, which need to execute computational intensive applications (e.g., infotainment or driver assistance applications). Consequently, design frameworks that allow the workload to be distributed in peak situations by both parallel and distributed processors are required. Such scenarios require the integration of distributed computations with parallel real-time models. In a distributed system, the transmission delay of messages cannot be considered negligible as in the case of multi-processors systems, therefore, their impact on the schedulability of the system has to be considered.
The fork-join Parallel/Distributed real-time model (P/D task) proposed in this thesis is designed to consider such execution pattern. The P/D task model is derived from observing the execution of parallel and distributed programs (e.g. OpenMP, MPI). The thesis proposes a scheduling algorithm for P/D tasks, the parallel/Distributed Deadline Monotonic Scheduling (P/D-DMS). The thesis also proposes two heuristics for task partitioning and priority assignment for the linear transactional model and the P/D tasks model, the Distributed using Optimal Priority Assignment (DOPA) heuristic and the Parallel-DOPA (P-DOPA) heuristic, respectively.
A holistic analysis technique for P/D tasks is also proposed. The holistic approach allows to consider the systems as a whole, and an improved analysis is proposed based on that holistic view of the system. The allocation of P/D tasks is later extended by considering distributed multi-core nodes. The extension is based on the constraint programming approach.
The analysis and proposals presented in this thesis are validated through simulations and an experimental evaluation.
President: Doutor José Alfredo Ribeiro da Silva Matos, Professor Catedrático da FEUP
Doutor José Javier Gutiérrez, Professor Associado, Departamento de Electrónica e Computadores, Universidad de Cantabria
Doutor Paulo Bacelar Reis Pedreiras, Professor Auxiliar do Departamento de Eletrónica, Telecomunicações e Informática da Universidade de Aveiro
Supervisor: Doutor Luís Miguel Moreira Lino Ferreira, Professor Adjunto do Departamento de Engenharia Informática do Instituto Superior de Engenharia do Porto, Instituto Politécnico do Porto
Doutor Luís Miguel Pinho de Almeida, Professor Associado do Departamento de Engenharia Eletrotécnica e de Computadores da Faculdade de Engenharia da Universidade do Porto
Doutor Mário Jorge Rodrigues de Sousa, Professor Auxiliar do Departamento de Engenharia Eletrotécnica e de Computadores da Faculdade de Engenharia da Universidade do Porto
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Faculdade de Engenharia da Universidade do Porto
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