Local majorities, coalitions and monopolies in graphs: a review
Theoretical Computer Science
Distributed Soft Path Coloring
STACS '03 Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science
Local Algorithms: Self-stabilization on Speed
SSS '09 Proceedings of the 11th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Counting in the Presence of Memory Faults
ISAAC '09 Proceedings of the 20th International Symposium on Algorithms and Computation
ACM Transactions on Algorithms (TALG)
A formal model for fault-tolerance in distributed systems
SAFECOMP'05 Proceedings of the 24th international conference on Computer Safety, Reliability, and Security
Output stability versus time till output
DISC'07 Proceedings of the 21st international conference on Distributed Computing
Priority queues resilient to memory faults
WADS'07 Proceedings of the 10th international conference on Algorithms and Data Structures
Hi-index | 0.00 |
This paper lays a theoretical foundation for scaling fault tolerant tasks to large and diversified networks such as the Internet. In such networks, there are always parts of the network that fail. On the other hand, various subtasks interest only parts of the network, and it is desirable that those parts, if nonfaulty, do not suffer from faults in other parts. Our approach is to refine the previously suggested notion of fault local algorithms (that was best suited for global tasks) for which the complexity of recovering was proportional to the number of faults. We refine this notion by introducing the concept of tight fault locality to deal with problems whose complexity (in the absence of faults) is sublinear in the size of the network. For a problem whose time complexity on an n-node network is T(n) (where possibly T(n)= o(n)), a tightly fault local algorithm recovers a legal global state in O(T(x)) time when the (unknown) number of faults is x.This concept is illustrated by presenting a general transformation for maximal independent set (MIS) algorithms to make them tightly fault local. In particular, our transformation yields an O(log x) randomized mending algorithm and an $\exp(O(\sqrt{\log x}))$ deterministic mending algorithm for MIS. The methods used in the transformation may be of interest by themselves.