Implementing Policy Management through BDI

Abstract

The requirement for Grid middleware to be largely transparent to individualusers and at the same time act in accordance with their personalneeds is a difficult challenge. In e-science scenarios, users cannotbe repeatedly interrogated for each operational decision made whenenacting experiments on the Grid. It is thus important to specifyand enforce policies that enable the environment to be configuredto take user preferences into account automatically. In particular,we need to consider the context in which these policies are applied,because decisions are based not only on the rules of the policybut also on the current state of the system. Consideration of contextis explicitly addressed, in the agent perspective, when decidinghow to balance the achievement of goals and reaction to the environment.One commonly-applied abstraction that balances reaction to multipleevents with context-based reasoning in the way suggested by ourrequirements is the belief-desire-intention (BDI) architecture,which has proven successful in many applications. In this paper,we argue that BDI is an appropriate model for policy enforcement,and describe the application of BDI to policy enforcement in personalisingGrid service discovery. We show how this has been implemented inthe myGrid registry to provide bioinformaticians with control overthe services returned to them by the service discovery process.