Fault-Tolerant Techniques for Ambient Intelligent Distributed Systems

Ambient Intelligent Systems provide an unexplored hardware platform for executing distributed applications under strict energy constraints. These systems must respond quickly to changes in user behavior or environmental conditions and must provide high availability and fault-tolerance under given quality constraints. These systems will necessitate fault-tolerance to be built into applications. One way to provide such fault-tolerance is to employ the use of redundancy. Hundreds of computational devices will be available in deeply networked ambient intelligent systems, providing opportunities to exploit node redundancy to increase application lifetime or improve quality of results if it drops below a threshold. Pre-copying with remote execution is proposed as a novel, alternative technique of code migration to enhance system lifetime for ambient intelligent systems. Self-management of the system is considered in two different scenarios: applications that tolerate graceful quality degradation and applications with single-point failures. The proposed technique can be part of a design methodology for prolonging the lifetime of a wide range of applications under various types of faults, despite scarce energy resources

Wireless Sensor Network Pattern Based Fault Isolation in Industrial Applications

In business applications where wireless sensor networks (WSN) are applied, failures in essential parts of the system must be efficiently detected and automatically recovered to avoid major losses. In this thesis we investigate existing fault detection and isolation solutions and present a fault isolation method based on the identification of system patterns. This approach has the ability to learn the behaviour of the network when specific failures occur and to combine known patterns