You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
The work reported in this paper is motivated towards validating an alternative approach for fault tolerance over traditional methods like checkpointing that constrain efficacious fault tolerance. Can agent intelligence be used to achieve fault tolerant parallel computing systems? If so, "What agent capabilities are required for fault tolerance?", "What parallel computational tasks can benefit from such agent capabilities?" and "How can agent capabilities be implemented for fault tolerance?" need to be addressed. Cognitive capabilities essential for achieving fault tolerance through agents are considered. Parallel reduction algorithms are identified as a class of algorithms that can benefit from cognitive agent capabilities. The Message Passing Interface is utilized for implementing an intelligent agent based approach. Preliminary results obtained from the experiments validate the feasibility of an agent based approach for achieving fault tolerance in parallel computing systems.

Cited Abstract(s):
[1]: A long-term trend in high performance computing is the increasing number of nodes in parallel computing platforms, which entails a higher failure probability. Hence, fault tolerance becomes a key property for parallel application running on parallel computing systems. The message passing interface (MPI) is currently the programming paradigm and communication library most commonly used on parallel computing platforms. MPI applications may be stopped at any time during their execution due to an unpredictable failure. In order to avoid complete restarts of an MPI application because of only one failure, a fault tolerant MPI implementation is essential. In this paper, we propose a fault tolerant approach in cluster computing system. Our approach is based on reassignment of tasks to the remaining system and message logging is used for message losses. This system consists of two main parts, failure diagnosis and failure recovery. Failure diagnosis is the detection of a failure and failure recovery is the action needed to take over the workload of a failed component. This fault tolerant approach is implemented as an extension of the message passing interface.
In [1] , an extension to MPI is proposed that consists of two steps to achieve fault tolerance. Firstly, failure diagnosis, detection of the location of a failed component. Secondly, failure recovery, a step towards reassigning tasks of a failed component to fully functional system nodes.