| 1. |
- Dubrova, Elena
(författare)
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Self-Organization for Fault-Tolerance
- 2008
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Ingår i: SELF-ORGANIZING SYSTEMS, PROCEEDINGS. - 9783540921561 ; , s. 145-156
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Konferensbidrag (refereegranskat)abstract
- In the last decade, there has been a considerable increase of interest in fault-tolerant computing due to dependability problems related to process scaling, embedded systems, and ubiquitous Computing, In this paper, we present an approach to fault-tolerance inspired by gene regulatory networks of living cells. Living cells are capable of maintaining their functionality under a variety of genetic changes and external perturbations. They have natural self-healing, self-maintaining, self-replicating, and self-assembling mechanisms. The fault-tolerance of living cells is due to the ability of their gene regulatory network to self-organize and produce a stable attractors' landscape. We introduce a computational scheme which exploits the intrinsic stability of attractors to achieve fault.-tolerant computation. We also test fault-tolerance of the presented scheme on the example of a gene regulatory network model of Arabidopsis thaliana and show that it can tolerate 68% single-point mutations in the outputs of the defining tables of gene functions.
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| 2. |
- Shafaat, Tallat M., et al.
(författare)
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A Practical Approach to Network Size Estimation for Structured Overlays
- 2008
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Ingår i: SELF-ORGANIZING SYSTEMS, PROCEEDINGS. - Berlin : SPRINGER-VERLAG. - 9783540921561 ; , s. 71-83
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Konferensbidrag (refereegranskat)abstract
- Structured overlay networks have recently received much attention due to their self-* properties under dynamic and decentralized settings. The number of nodes in all overlay fluctuates all the time due to churn. Since knowledge of the size of the. overlay is a core requirement for many systems, estimating the size in a decentralized manner is a challenge taken up by recent research activities. Gossip-based Aggregation has been shown to give accurate estimates for the network size, but previous work done is highly sensitive to node failures. In this paper, we present a gossip-based aggregation-style network size estimation algorithm. We discuss shortcomings of existing aggregation-based size estimation algorithms, and give a solution that is highly robust to node failures and is adaptive to network delays. We examine our solution in various scenarios to demonstrate. its effectiveness.
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