Self-testing/correcting with applications to numerical problems
Journal of Computer and System Sciences - Special issue: papers from the 22nd ACM symposium on the theory of computing, May 14–16, 1990
Fault tolerance in distributed systems
Fault tolerance in distributed systems
Software reliability via run-time result-checking
Journal of the ACM (JACM)
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SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Proceedings of the IFIP WG6.1 Seventh International Conference on Protocol Specification, Testing and Verification VII
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Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Software Fault Tolerance: A Tutorial
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A system model for dynamically reconfigurable software
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WMC'04 Proceedings of the 5th international conference on Membrane Computing
Crypto-fraglets: networking, biology and security
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A survey on bio-inspired networking
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Code regulation in open ended evolution
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Experiments on the automatic evolution of protocols using genetic programming
WAC'05 Proceedings of the Second international IFIP conference on Autonomic Communication
Towards self-optimizing protocol stack for autonomic communication: initial experience
WAC'05 Proceedings of the Second international IFIP conference on Autonomic Communication
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The goal of this research is to create robust execution circuits for communication software which can distribute over a network and which continues to provide its service despite parts of the implementation being knocked out. Like packets that can be lost (which can be recovered by the appropriate protocols) we envisage an environment where parts of a protocol's execution can be lost. The remaining implementation elements should continue to operate and be able to recover by themselves for restoring full services again. Based on a chemical execution model, we show a few initial examples of packet processing functions that are robust against the knock-out of any single instruction. These examples illustrate how the model can be applied to implement resilient communication protocols, to which we add regulatory signals that can be used to steer the protocols' code basis.