Applying feedback control in adaptive replication mechanisms in fault tolerant multi-agent organizations

Effective fault-handling in emerging complex applications in large-scale MAS (Multi-agent Systems) requires the ability to dynamically adapt resource allocation and fault tolerance policies in response to changes in environment, user or application requirements, and available resources. This adaptation process incorporates an observation mechanism that transparently monitors the application's behaviors as well as the availability of resources, and adaptively reconfigures the system resources. This process is realized by a specific module which exploits the information resulting from monitoring. In this paper, we present an approach for adaptive replication. This approach uses an observation mechanism and a feedback control system within an adaptive replication infrastructure to support adaptive fault tolerance in multi-agent organizations. The main strategy used in our approach is to insert control theory methodology and analysis to adaptive replication. Thus, our approach provides a systematic and scientific method for implementing adaptive fault tolerance policies in MAS.

[1]  Oguz Dikenelli,et al.  Implementing a Multi-agent Organization that Changes Its Fault Tolerance Policy at Run-Time , 2005, ESAW.

[2]  Ralph Deters,et al.  Improving fault-tolerance by replicating agents , 2002, AAMAS '02.

[3]  Riza Cenk Erdur,et al.  SEAGENT: a platform for developing semantic web based multi agent systems , 2005, AAMAS '05.

[4]  Shivakant Mishra,et al.  Consul: a communication substrate for fault-tolerant distributed programs , 1993, Distributed Syst. Eng..

[5]  Pierre Sens,et al.  Dynamic and Adaptive Replication for Large-Scale Reliable Multi-agent Systems , 2002, SELMAS.

[6]  Pierre Sens,et al.  Toward fault-tolerant multi-agent systems , 2001 .

[7]  Sang Hyuk Son,et al.  Feedback Control Real-Time Scheduling: Framework, Modeling, and Algorithms* , 2001, Real-Time Systems.

[8]  Onn Shehory,et al.  A Planning Component for RETSINA Agents , 1999, ATAL.

[9]  Jean-Pierre Briot,et al.  From Active Objects to Autonomous Agents , 1998, IEEE Concurr..

[10]  D. McCue,et al.  Fault-Tolerance in the Advanced Automation System , 1991, OPSR.

[11]  Matti A. Hiltunen,et al.  Adaptive Distributed and Fault-Tolerant Systems , 2007 .

[12]  K. H. Kim,et al.  An approach for adaptive fault-tolerance in object-oriented open distributed systems , 1997, Proceedings Third International Workshop on Object-Oriented Real-Time Dependable Systems.

[13]  E. N. Elnozahy,et al.  Replicated distributed processes in Manetho , 1992, [1992] Digest of Papers. FTCS-22: The Twenty-Second International Symposium on Fault-Tolerant Computing.

[14]  Mikal Ziane,et al.  Monitoring and organizational-level adaptation of multi-agent systems , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[15]  Lorenzo Strigini,et al.  Adaptable Fault Tolerance for Real-Time Systems , 1994, Responsive Computer Systems.