Semantic-compensation-based recovery in multi-agent systems

IEEE 2nd Symposium on Multi-Agent Security and Survivability, 2005. Pub Date : 2005-09-12 DOI:10.1109/MASSUR.2005.1507051

A. Unruh, H. Harjadi, J. Bailey, K. Ramamohanarao

{"title":"Semantic-compensation-based recovery in multi-agent systems","authors":"A. Unruh, H. Harjadi, J. Bailey, K. Ramamohanarao","doi":"10.1109/MASSUR.2005.1507051","DOIUrl":null,"url":null,"abstract":"In agent systems, an agent's recovery from, execution problems is often complicated by constraints that are not present in a more traditional distributed, database systems environment. An analysis of agent-related crash recovery issues is presented, and requirements for achieving 'acceptable' agent crash recovery are discussed. Motivated by this analysis, a novel approach to managing agent recovery is presented. It utilises an event-and task-driven model for employing semantic compensation; task retries, and checkpointing. The compensation/retry model requires a situated model of action and failure, and provides the agent with an emergent unified, treatment of both crash recovery and run-time failure-handling. This approach helps the agent to recover acceptably from crashes and execution problems; improve system predictability; manage inter-task dependencies; and address the way in which exogenous events or crashes can trigger the need for a re-decomposition of a task. Agent architecture is then presented, which uses pair processing to leverage these recovery techniques and increase the agent's availability on crash restart.","PeriodicalId":391808,"journal":{"name":"IEEE 2nd Symposium on Multi-Agent Security and Survivability, 2005.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE 2nd Symposium on Multi-Agent Security and Survivability, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MASSUR.2005.1507051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 17

Abstract

In agent systems, an agent's recovery from, execution problems is often complicated by constraints that are not present in a more traditional distributed, database systems environment. An analysis of agent-related crash recovery issues is presented, and requirements for achieving 'acceptable' agent crash recovery are discussed. Motivated by this analysis, a novel approach to managing agent recovery is presented. It utilises an event-and task-driven model for employing semantic compensation; task retries, and checkpointing. The compensation/retry model requires a situated model of action and failure, and provides the agent with an emergent unified, treatment of both crash recovery and run-time failure-handling. This approach helps the agent to recover acceptably from crashes and execution problems; improve system predictability; manage inter-task dependencies; and address the way in which exogenous events or crashes can trigger the need for a re-decomposition of a task. Agent architecture is then presented, which uses pair processing to leverage these recovery techniques and increase the agent's availability on crash restart.

查看原文本刊更多论文

多智能体系统中基于语义补偿的恢复

在代理系统中，代理从执行问题中恢复通常会因约束而变得复杂，这些约束在更传统的分布式数据库系统环境中不存在。对与代理相关的崩溃恢复问题进行了分析，并讨论了实现“可接受的”代理崩溃恢复的要求。在此基础上，提出了一种新的agent恢复管理方法。它利用事件和任务驱动模型来实现语义补偿;任务重试和检查点。补偿/重试模型需要操作和故障的定位模型，并为代理提供紧急的统一处理崩溃恢复和运行时故障处理。这种方法有助于代理从崩溃和执行问题中恢复到可接受的状态;提高系统的可预测性;管理任务间的依赖关系;并解决外生事件或崩溃触发任务重新分解的方式。然后介绍了代理体系结构，它使用对处理来利用这些恢复技术，并增加代理在崩溃重启时的可用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE 2nd Symposium on Multi-Agent Security and Survivability, 2005.

自引率

0.00%

发文量