Improving quality of service in application clusters

Quality of service (QoS) requirements, which include availability, integrity, performance and responsiveness are increasingly needed by science and engineering applications. Rising computational demands and data mining present a new challenge in the IT world. As our needs for more processing, research and analysis increase, performance and reliability degrade exponentially. In this paper we present a software system that manages quality of service for Unix based distributed application clusters. Our approach is synthetic and involves intelligent agents that make use of static and dynamic ontologies to monitor, diagnose and correct faults at run time, over a private network. Finally, we provide experimental results from our pilot implementation in a production environment

Intelligent architecture for automatic resource allocation in computer clusters

As the need for more reporting and assessment of information increase exponentially, computer-based applications consume resources at an alarmingly rapid rate. Therefore, traditional techniques for managing resource allocation, topology and systems need urgent revision. In this paper, we present an intelligent architecture that introduces a new strategy for managing resource discovery, allocation and dynamic reconfiguration at run-time. Our building methodology involves the employment of new types of clustered systems based on large application groupings, each having a master cluster controller. Each controlling engine consists of self-healing intelligent entities that can compensate for a variety of software or hardware problems. We also present evaluation results of extensive experiments in a production environment, which demonstrate the advantages of our approach

Cluster infrastructure for biological and health related research

Researchers in the biological and health industries need powerful and stable systems for their work. These systems must be dependable, fault-tolerant, highly available and easy to use. To cope with these demands we propose the use of computational and data clusters in a fail-over configuration combined with the grid technology and job scheduling. Our infrastructure has been deployed successfully for running time-critical applications in commercial environments. We also present experimental results from this pilot implementation that demonstrate the viability of our approach

Agent-based service management in large datacentres and grids

Increased computational demands and data mining present the IT world with new challenges. Amongst others, the maturing grid technology aims to address them. To take full advantage of the grid capabilities and enhance its effectiveness in complex and dynamic computational environments, we must make service management more stable, less computationally expensive and more automatic. In this paper, we propose a synthetic approach to deal with service management in large Unix datacentres that involves the employment of intelligent agents and ontologies. These agents can automatically detect and correct faults at run-time and manage services

Autonomous agents-based security infrastructure

Organizations have evolved to the stage where critical data management and protection are intimately linked to revenues. Error margins become smaller as information importance becomes greater. Security compromises cause considerable credibility loss and frustration. In this paper, we address both proactively and retrospectively security related problems for Unix-based systems. We have designed and built a software infrastructure, which handles security issues by autonomous intelligent agents automatically and dynamically with none or minimal service interruptions. Our software has been implemented and used for more than a year as part of the production environment of a mobile phone operator and Internet provider. The evaluation results over this period have shown that autonomous intelligent agents handling security can reduce dramatically downtime caused by security related incidents