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.
Fifthly, in mobile agent technology, checkpointing can prevent the loss of an agent and prevent blocking. In this case single failure does not prevent the progress of a mobile agent execution. However, checkpointing does not satisfy the exactly-once property, leading to multiple executions of an agent @cite_17 .
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Mobile agents have attracted considerable interest in recent years. In the context of mobile agents, fault tolerance is crucial to enable the integration of mobile agent technology into today's business applications. To further develop mobile agent technology, reliability mechanisms such as fault tolerance and transaction support are required. For this purpose, we first identify two basic requirements for fault-tolerant mobile agent execution: (1) non-blocking (i.e., a single failure does not prevent progress of the mobile agent execution); and (2) exactly-once (i.e., multiple executions of the agent are prevented). To achieve fault tolerance for the agent system, especially for the agent transfer to a new host, we use distributed transaction processing. This paper proposes a novel approach to fault-tolerant mobile agent execution, which is based on modeling agent execution as a sequence of agreement problems. Each agreement problem is one instance of the well-understood consensus problem. Our solution does not require a perfect failure detection mechanism, while preventing blocking and ensuring that the agent is executed exactly once In mobile agent systems, program code together with some process state can autonomously migrate to new hosts. Despite its many practical benefits, mobile agent technology results in significant new security threats from malicious agents and hosts. In this paper, we propose a security architecture to achieve three goals: certification that a server has the authority to execute an agent on behalf of its sender; flexible selection of privileges, so that an agent arriving at a server may be given the privileges necessary to carry out the task for which it has come to the server; and state appraisal, to ensure that an agent has not become malicious as a consequence of alterations to its state. The architecture models the trust relations between the principals of mobile agent systems and includes authentication and authorization mechanisms. As the failure frequency is increasing with the components count in modern and future supercomputers, resilience is becoming critical for extreme scale systems. The association of failure prediction with proactive checkpointing seeks to reduce the effect of failures in the execution time of parallel applications. Unfortunately, proactive checkpointing does not systematically avoid restarting from scratch. To mitigate this issue, failure prediction and proactive checkpointing can be coupled with periodic checkpointing. However, blind use of these techniques does not always improves system efficiency, because everyone of them comes with a mix of overheads and benefits. In order to study and understand the combination of these techniques and their improvement in the system's efficiency, we developed: (i) a prototype combining state of the art failure prediction, fast proactive checkpointing and preventive checkpointing; (ii) a mathematical model that reflects the expected computing efficiency of the combination and computes the optimal checkpointing interval in this context; (iii) a discrete event simulator to evaluate the computing efficiency of the combination for system parameters corresponding to the current and projected large scale HPC systems. We evaluate our proposed technique on a large supercomputer (i.e. TSUBAME2) with production-level HPC applications and we show that failure prediction, proactive and preventive checkpointing can be coupled successfully, imposing only about 2 to 6 of overhead in comparison with preventive checkpointing only. Moreover, our model-based simulations show that the optimal solution improves the computing efficiency up to 30 in comparison with classic periodic checkpointing. We show that the prediction recall has a much higher impact on execution efficiency than the prediction precision. This result suggests that researchers on failure prediction algorithms should focus on improving the recall. We also show that the combination of these techniques can significantly improve (by a factor 2, for a particular configuration) the mean time between failures (MTBF) perceived by the application. Two mobile agents (robots) with distinct labels have to meet in an arbitrary, possibly infinite, unknown connected graph or in an unknown connected terrain in the plane. Agents are modeled as points, and the route of each of them only depends on its label and on the unknown environment. The actual walk of each agent also depends on an asynchronous adversary that may arbitrarily vary the speed of the agent, stop it, or even move it back and forth, as long as the walk of the agent in each segment of its route is continuous, does not leave it and covers all of it. Meeting in a graph means that both agents must be at the same time in some node or in some point inside an edge of the graph, while meeting in a terrain means that both agents must be at the same time in some point of the terrain. Does there exist a deterministic algorithm that allows any two agents to meet in any unknown environment in spite of this very powerful adversary? We give deterministic rendezvous algorithms for agents starting at arbitrary nodes of any anonymous connected graph (finite or infinite) and for agents starting at any interior points with rational coordinates in any closed region of the plane with path-connected interior. While our algorithms work in a very general setting - agents can, indeed, meet almost everywhere - we show that none of the above few limitations imposed on the environment can be removed. On the other hand, our algorithm also guarantees the following approximate rendezvous for agents starting at arbitrary interior points of a terrain as above: agents will eventually get at an arbitrarily small positive distance from each other.