A Failure Handling Framework for Distributed Data Mining Services on the Grid

Abstract

Fault tolerance is an important issue in Grid computing, where many and heterogenous machines are used. In this paper we present a flexible failure handling framework which extends a service-oriented architecture for Distributed Data Mining previously proposed, addressing the requirements for fault tolerance in the Grid. The framework allows users to achieve failure recovery whenever a crash can occur on a Grid node involved in the computation. The implemented framework has been evaluated on a real Grid setting to assess its effectiveness and performance.