Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Mobile agents constitute a computing paradigm of a more general nature than the widely used client/server computing paradigm. A mobile agent is essentially a computer program that acts autonomously on behalf of a user and travels through a network of heterogeneous machines. However, the greater flexibility of the mobile agent paradigm compared to the client/server computing paradigm comes at additional costs. These costs include, among others, the additional complexity of developing and managing mobile agent-based applications. This additional complexity comprises such issues as reliability. Before mobile agent technology can appear at the core of tomorrow's business applications, reliability mechanisms for mobile agents must be established. In this context, fault tolerance and transaction support are mechanisms of considerable importance. Various approaches to fault tolerance and transaction support exist. They have different strengths and weaknesses, and address different environments. Because of this variety, it is often difficult for the application programmer to choose the approach best suited to an application. This thesis introduces a classification of current approaches to fault-tolerant and transactional mobile agent execution. The classification, which focuses on algorithmic aspects, aims at structuring the field of fault-tolerant and transactional mobile agent execution and facilitates an understanding of the properties and weaknesses of particular approaches. In a distributed system, any software or hardware component may be subject to failures. A single failing component (e.g., agent or machine) may prevent the agent from proceeding with its execution. Worse yet, the current state of the agent and even its code may be lost. We say that the agent execution is blocked. For the agent owner, i.e., the person or application that has configured the agent, the agent does not return. To achieve fault-tolerance, the agent owner can try to detect the failure of the agent, and upon such an event launch a new agent. However, this requires the ability to correctly detect the crash of the agent, i.e., to distinguish between a failed agent and an agent that is delayed by slow processors or slow communication links. Unfortunately, this cannot be achieved in systems such as the Internet. An agent owner who tries to detect the failure of the agent thus cannot prevent the case in which the agent is mistakenly assumed to have crashed. In this case, launching a new agent leads to multiple executions of the agent, i.e., to the violation of the desired exactly-once property of agent execution. Although this may be acceptable for certain applications (e.g., applications whose operations do not have side-effects), others clearly forbid it. In this context, launching a new agent is a form of replication. In general, replication prevents blocking, but may lead to multiple executions of the agent, i.e., to a violation of the exactly-once execution property. Thi