Self-organising management of Grid environments

This paper presents basic concepts, architectural principles and algorithms for efficient resource and security management in cluster computing environments and the Grid. The work presented in this paper is funded by BTExacT and the EPSRC project SO-GRM (GR/S21939)

Managing Uncertainty: A Case for Probabilistic Grid Scheduling

The Grid technology is evolving into a global, service-orientated architecture, a universal platform for delivering future high demand computational services. Strong adoption of the Grid and the utility computing concept is leading to an increasing number of Grid installations running a wide range of applications of different size and complexity. In this paper we address the problem of elivering deadline/economy based scheduling in a heterogeneous application environment using statistical properties of job historical executions and its associated meta-data. This approach is motivated by a study of six-month computational load generated by Grid applications in a multi-purpose Grid cluster serving a community of twenty e-Science projects. The observed job statistics, resource utilisation and user behaviour is discussed in the context of management approaches and models most suitable for supporting a probabilistic and autonomous scheduling architecture

TOWARDS AUTOMATING POLICY- BASED MANAGEMENT SYSTEMS

The goal of distributed systems management is to provide reliable, secure and efficient utilization of the network, processors and devices that comprise those systems. The management system makes use of management agents to collect events and data from managed objects while policies provide information on how to modify the behaviour of a managed system. Systems as well as policies governing the behaviour of the system and its constituents can change dynamically. The aim of this work is to provide the services and algorithms needed to automatically identify and deploy management entities and be able to respond automatically to both changes to the system itself as well as to changes in the way the system is to be managed, i.e., changes to the set of management policies or sets of management agents. One significant challenge in the use of policy-based management systems is finding efficient mechanisms to address and simplify the gap between expressing and specifying policies and an actual configuration of a management system that realizes and makes use of policies. Little work has been done to define how the monitoring operations are to be configured and updated according to the policies. This Thesis proposes a general architecture for a policy-based management system for distributed systems which allows for expressing and automating the deployment of a wide range of management policies. The proposed solution is based on the matching between the management operations that are carried out by the management agents and the policies. The matching process relies on the attributes that the agents can monitor and the extracted attributes from the components of the policies. One major contribution of this Thesis is to build the policy model and services on existing management services found in commercial management systems. The work of this Thesis also focuses in finding87 strategies for selecting and configuring agents to be used to keep the time of a policy deployment low. The Thesis introduces the Policy-Management Agent Integrated Console (PMagic) prototype. The PMagic prototype has been implemented to provide a practical validation of the policy based management system model proposed. The approach, architecture and prototype have demonstrated that it is possible to create a more autonomic management system, particularly one that can instantiate agents to react to changes in sets of policies