Meta-heuristics self-configuration for scheduling

Scheduling resolution requires the intervention of highly skilled human problemsolvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. This paper addresses the resolution of complex scheduling problems using cooperative negotiation. A Multi-Agent Autonomic and Meta-heuristics based framework with self-configuring capabilities is proposed.

Iterative refinement approach for QOS-Aware service configuration

In heterogeneous environments, diversity of resources among the devices may affect their ability to perform services with specific QoS constraints, and drive peers to group themselves in a coalition for cooperative service execution. The dynamic selection of peers should be influenced by user’s QoS requirements as well as local computation availability, tailoring provided service to user’s specific needs. However, complex dynamic real-time scenarios may prevent the possibility of computing optimal service configurations before execution. An iterative refinement approach with the ability to trade off deliberation time for the quality of the solution is proposed. We state the importance of quickly finding a good initial solution and propose heuristic evaluation functions that optimise the rate at which the quality of the current solution improves as the algorithms have more time to run.

Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments

The scarcity and diversity of resources among the devices of heterogeneous computing environments may affect their ability to perform services with specific Quality of Service constraints, particularly in dynamic distributed environments where the characteristics of the computational load cannot always be predicted in advance. Our work addresses this problem by allowing resource constrained devices to cooperate with more powerful neighbour nodes, opportunistically taking advantage of global distributed resources and processing power. Rather than assuming that the dynamic configuration of this cooperative service executes until it computes its optimal output, the paper proposes an anytime approach that has the ability to tradeoff deliberation time for the quality of the solution. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves at each iteration, with an overhead that can be considered negligible.

Environmental/Regatta Buoy: Telemetry and Configuration

A monitorização ambiental é essencial para a tomada de decisões tanto na ciência como na indústria. Em particular, uma vez que a água é essencial à vida e a superfície da Terra é composta principalmente por água, a monitorização do clima e dos parâmetros relacionados com a água em ecossistemas sensíveis, tais como oceanos, lagoas, rios e lagos, é de extrema importância. Um dos métodos mais comuns para monitorar a água é implantar bóias. O presente trabalho está integrado num projeto mais amplo, com o objetivo de projectar e desenvolver uma bóia autónoma para a investigação científica com dois modos de funcionamento: (i) monitorização ambiental ; e (ii) baliza ativa de regata. Assim, a bóia tem duas aplicações principais: a coleta e armazenamento de dados e a assistência a regatas de veleiros autónomos. O projeto arrancou há dois anos com um grupo de quatro estudantes internacionais. Eles projetaram e construíram a estrutura física, compraram e montaram o sistema de ancoragem da bóia e escolherem a maioria dos componentes electrónicos para o sistema geral de controlo e medição. Este ano, durante o primeiro semestre, dois estudantes belgas - Jeroen Vervenne e Hendrick Verschelde – trabalharam nos subsistemas de recolha e armazenamento de dados (unidade de controlo escrava) e de telemetria e configuração (unidade de controlo mestre) assim como definiram o protocolo de comunicação da aplicação. O trabalho desta tese continua o desenvolvimento do subsistema de telemetria e configuração. Este subsistema _e responsável pela configuração do modo de funcionamento e dos sensores assim como pela comunicação com a estacão de base (controlo ambiental), barcos (baliza ativa de regata) e com o subsistema de recolha e armazenamento de dados. O desenvolvimento do subsistema de recolha e armazenamento de dados, que coleta e armazena num cartão SD os dados dos sensores selecionados, prossegue com outro estudante belga - Mathias van Flieberge. O objetivo desta tese é, por um lado, implementar o subsistema de telemetria e de configuração na unidade de controle mestre e, por outro lado, refinar e implementar, conjuntamente com Mathias van Flieberge, o protocolo de nível de aplicação projetado. Em particular, a unidade de controlo mestre deve processar e atribuir prioridades às mensagens recebidas da estacão base, solicitar dados à unidade de controlo escrava e difundir mensagens com informação de posição e condições de vento e água no modo de regata. Enquanto que a comunicação entre a unidade de controlo mestre e a estacão base e a unidade de controlo mestre e os barcos é sem fios, a unidade de controlo mestre e a unidade de controlo escrava comunicam através de uma ligação série. A bóia tem atualmente duas limitações: (i) a carga máxima é de 40 kg; e (ii) apenas pode ser utilizada em rios ou próximo da costa dada à limitação de distância imposta pela técnica de comunicação sem fios escolhida.

TEA: Timing and Energy Aware compression architecture for Efficient Configuration in CGRAs

Coarse Grained Reconfigurable Architectures (CGRAs) are emerging as enabling platforms to meet the high performance demanded by modern applications (e.g. 4G, CDMA, etc.). Recently proposed CGRAs offer time-multiplexing and dynamic applications parallelism to enhance device utilization and reduce energy consumption at the cost of additional memory (up to 50% area of the overall platform). To reduce the memory overheads, novel CGRAs employ either statistical compression, intermediate compact representation, or multicasting. Each compaction technique has different properties (i.e. compression ratio, decompression time and decompression energy) and is best suited for a particular class of applications. However, existing research only deals with these methods separately. Moreover, they only analyze the compaction ratio and do not evaluate the associated energy overheads. To tackle these issues, we propose a polymorphic compression architecture that interleaves these techniques in a unique platform. The proposed architecture allows each application to take advantage of a separate compression/decompression hierarchy (consisting of various types and implementations of hardware/software decoders) tailored to its needs. Simulation results, using different applications (FFT, Matrix multiplication, and WLAN), reveal that the choice of compression hierarchy has a significant impact on compression ratio (up to 52%), decompression energy (up to 4 orders of magnitude), and configuration time (from 33 n to 1.5 s) for the tested applications. Synthesis results reveal that introducing adaptivity incurs negligible additional overheads (1%) compared to the overall platform area.

Scalable and Efficient Configuration of TimeDivision Multiplexed Resources

Consumer-electronics systems are becoming increasingly complex as the number of integrated applications is growing. Some of these applications have real-time requirements, while other non-real-time applications only require good average performance. For cost-efficient design, contemporary platforms feature an increasing number of cores that share resources, such as memories and interconnects. However, resource sharing causes contention that must be resolved by a resource arbiter, such as Time-Division Multiplexing. A key challenge is to configure this arbiter to satisfy the bandwidth and latency requirements of the real-time applications, while maximizing the slack capacity to improve performance of their non-real-time counterparts. As this configuration problem is NP-hard, a sophisticated automated configuration method is required to avoid negatively impacting design time. The main contributions of this article are: 1) An optimal approach that takes an existing integer linear programming (ILP) model addressing the problem and wraps it in a branch-and-price framework to improve scalability. 2) A faster heuristic algorithm that typically provides near-optimal solutions. 3) An experimental evaluation that quantitatively compares the branch-and-price approach to the previously formulated ILP model and the proposed heuristic. 4) A case study of an HD video and graphics processing system that demonstrates the practical applicability of the approach.