Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Symbolic model checking: 1020 states and beyond
Information and Computation - Special issue: Selections from 1990 IEEE symposium on logic in computer science
Accelerated reliability analysis for self-healing SONET networks
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Model-based adaptation for self-healing systems
WOSS '02 Proceedings of the first workshop on Self-healing systems
Reliability Analysis in Self-Repairing Embryonic Systems
EH '99 Proceedings of the 1st NASA/DOD workshop on Evolvable Hardware
Autonomic Computing and Reliability Improvement
ISORC '05 Proceedings of the Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing
Lifetime Analysis in Heterogeneous Sensor Networks
DSD '06 Proceedings of the 9th EUROMICRO Conference on Digital System Design
Design space exploration of reliable networked embedded systems
Journal of Systems Architecture: the EUROMICRO Journal
Interactive presentation: Reliability-aware system synthesis
Proceedings of the conference on Design, automation and test in Europe
Topology-aware replica placement in fault-tolerant embedded networks
ARCS'08 Proceedings of the 21st international conference on Architecture of computing systems
An operating system infrastructure for fault-tolerant reconfigurable networks
ARCS'06 Proceedings of the 19th international conference on Architecture of Computing Systems
Architectures & infrastructure
Service research challenges and solutions for the future internet
Symbolic system level reliability analysis
Proceedings of the International Conference on Computer-Aided Design
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In recent years, several network online algorithms have been studied that exhibit self-x properties such as self-healing or self-adaption. These properties are used to improve systems characteristics like, e.g., fault-tolerance, reliability, or load-balancing.In this paper, a symbolic reliability analysis of self-healing networked embedded systems that rely on self-reconfiguration and self-routing is presented. The proposed analysis technique respects resource constraints such as the maximum computational load or the maximum memory size, and calculates the achievable reliability of a given system. This analytical approach considers the topology of the system, the properties of the resources, and the executed applications. Moreover, it is independent of the used online algorithms that implement the self-healing properties, but determines the achievable upper bound for the systems reliability. Since this analysis is not tailored to a specific online algorithm, it allows a reasonable decision making on the used algorithm by enabling a rating of different self-healing strategies. Experimental results show the effectiveness of the introduced technique even for large networked embedded systems.