A fundamental problem in building large scale Grid resource sharing system is the need for efficient and scalable techniques for discovery and provisioning of resources for delivering expected Quality of Service (QoS) to users’ applications. The current approaches to Grid resource sharing based on resource brokers are non-coordinated since these brokers make scheduling related decisions independent of the others in the system. Clearly, this worsens the load-sharing and utilisation problems of distributed Grid resources as sub-optimal schedules are likely to occur. Further, existing brokering systems rely on centralised information services for resource discovery. Centralised or hierarchical resource discovery systems are prone to single-point failure, lack scalability and fault-tolerance ability. In the centralised model, the network links leading to the server are very critical to the overall functionality of the system, as their failure might halt the entire distributed system operation.

Submitted by Cassio Henrique Volpatto Forte null (cassiohenriquevolpatto@hotmail.com) on 2018-03-23T14:11:24Z No. of bitstreams: 1 Dissertacao.pdf: 2024184 bytes, checksum: d6bed57662958df380a22b4445c0b980 (MD5) / Approved for entry into archive by Elza Mitiko Sato null (elzasato@ibilce.unesp.br) on 2018-03-23T18:21:38Z (GMT) No. of bitstreams: 1 forte_chv_me_sjrp.pdf: 2024184 bytes, checksum: d6bed57662958df380a22b4445c0b980 (MD5) / Made available in DSpace on 2018-03-23T18:21:38Z (GMT). No. of bitstreams: 1 forte_chv_me_sjrp.pdf: 2024184 bytes, checksum: d6bed57662958df380a22b4445c0b980 (MD5) Previous issue date: 2018-02-07 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A complexidade crescente das aplicações e o grande volume de dados utilizados por elas levam a um uso sempre crescente de sistemas distribuídos de alto desempenho. Nas últimas décadas o impacto do consumo de energia cresceu em relevância para o bom funcionamento desses sistemas, e seu tratamento é um grande desafio aos projetistas de hardware, desenvolvedores de aplicações e administradores. A dificuldade desse tratamento decorre do conflito entre consumo de energia e desempenho. Reduzir o consumo de energia das máquinas em um sistema distribuído causa prejuízos ao desempenho, enquanto fazer com que elas trabalhem mais rapidamente proporciona melhor desempenho mas causa aumento no consumo de energia. Nesse cenário, as políticas de escalonamento de tarefas podem levar em conta o consumo de energia, auxiliando no tratamento do problema. Este texto apresenta o desenvolvimento e avaliação de um novo algoritmo de escalonamento de tarefas independentes em grades computacionais federadas, o EHOSEP (Energy-aware Heterogeneous Owner-Share Enforcement Policy). O objetivo do novo algoritmo é tratar o consumo de energia, associando-o a um critério de justiça de propriedade. Esse critério de justiça decorre das chamadas grades federadas ou cooperativas, formadas por recursos computacionais de diferentes proprietários, procurando estimular seu compartilhamento pela garantia de uso justo. Os resultados obtidos com a simulação da aplicação do EHOSEP em diferentes modelos de grade mostram que é possível estimular o uso da grade atendendo-se limites de potência. / The increasing complexity of applications and the large volume of data used by them lead to an ever-increasing use of high-performance distributed systems. In recent decades the energy consumption is becoming more relevant to the proper functioning of these systems, and its management is a major challenge to hardware designers, application developers and administrators. The difficulty of this management arises from the conflict between power consumption and performance. Reducing energy consumption of machines in a distributed system reduces performance as well, while making machines work faster provides better performance at a cost of an increase in energy consumption. In this scenario, task scheduling policies may also consider energy consumption, helping to solve this problem. This document presents the development and evaluation of a new scheduling algorithm for independent tasks in federated computing grids, the EHOSEP (Energyaware Heterogeneous Owner-Share Enforcement Policy). The goal of the new algorithm is to address energy consumption by associating it with a ownership fairness criterion. This fairness criterion stems from the so-called federated or cooperative grids, formed by computational resources of different owners, aiming the resource sharing by the guarantee of fair usage. Results achieved with the simulation of EHOSEP applied to different grid models show that it is possible to stimulate the use of the grid even limiting energy consumption.