TY - GEN
T1 - Relating L-resilience and wait-freedom via hitting sets
AU - Gafni, Eli
AU - Kuznetsov, Petr
PY - 2011/1/26
Y1 - 2011/1/26
N2 - The condition of t-resilience stipulates that an n-process program is only obliged to make progress when at least n-t processes are correct. Put another way, the live sets, the collection of process sets such that progress is required if all the processes in one of these sets are correct, are all sets with at least n-t processes. We show that the ability of arbitrary collection of live sets to solve distributed tasks is tightly related to the minimum hitting set of , a minimum cardinality subset of processes that has a non-empty intersection with every live set. Thus, finding the computing power of is NP-complete. For the special case of colorless tasks that allow participating processes to adopt input or output values of each other, we use a simple simulation to show that a task can be solved -resiliently if and only if it can be solved (h-1)-resiliently, where h is the size of the minimum hitting set of . For general tasks, we characterize -resilient solvability of tasks with respect to a limited notion of weak solvability: in every execution where all processes in some set in are correct, outputs must be produced for every process in some (possibly different) participating set in . Given a task T, we construct another task such that T is solvable weakly -resiliently if and only if is solvable weakly wait-free.
AB - The condition of t-resilience stipulates that an n-process program is only obliged to make progress when at least n-t processes are correct. Put another way, the live sets, the collection of process sets such that progress is required if all the processes in one of these sets are correct, are all sets with at least n-t processes. We show that the ability of arbitrary collection of live sets to solve distributed tasks is tightly related to the minimum hitting set of , a minimum cardinality subset of processes that has a non-empty intersection with every live set. Thus, finding the computing power of is NP-complete. For the special case of colorless tasks that allow participating processes to adopt input or output values of each other, we use a simple simulation to show that a task can be solved -resiliently if and only if it can be solved (h-1)-resiliently, where h is the size of the minimum hitting set of . For general tasks, we characterize -resilient solvability of tasks with respect to a limited notion of weak solvability: in every execution where all processes in some set in are correct, outputs must be produced for every process in some (possibly different) participating set in . Given a task T, we construct another task such that T is solvable weakly -resiliently if and only if is solvable weakly wait-free.
U2 - 10.1007/978-3-642-17679-1_17
DO - 10.1007/978-3-642-17679-1_17
M3 - Conference contribution
AN - SCOPUS:78751653017
SN - 364217678X
SN - 9783642176784
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 191
EP - 202
BT - Distributed Computing and Networking - 12th International Conference, ICDCN 2011, Proceedings
T2 - 12th International Conference on Distributed Computing and Networking, ICDCN 2011
Y2 - 2 January 2011 through 5 January 2011
ER -