English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Paper

Fully Dynamic All-pairs Shortest Paths with Worst-case Update-time revisited

MPS-Authors
/persons/resource/persons199379

Krinninger,  Sebastian
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

1607.05132.pdf
(Preprint), 609KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Abraham, I., Chechik, S., & Krinninger, S. (2016). Fully Dynamic All-pairs Shortest Paths with Worst-case Update-time revisited. Retrieved from http://arxiv.org/abs/1607.05132.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002C-50F8-A
Abstract
We revisit the classic problem of dynamically maintaining shortest paths between all pairs of nodes of a directed weighted graph. The allowed updates are insertions and deletions of nodes and their incident edges. We give worst-case guarantees on the time needed to process a single update (in contrast to related results, the update time is not amortized over a sequence of updates). Our main result is a simple randomized algorithm that for any parameter $c>1$ has a worst-case update time of $O(cn^{2+2/3} \log^{4/3}{n})$ and answers distance queries correctly with probability $1-1/n^c$, against an adaptive online adversary if the graph contains no negative cycle. The best deterministic algorithm is by Thorup [STOC 2005] with a worst-case update time of $\tilde O(n^{2+3/4})$ and assumes non-negative weights. This is the first improvement for this problem for more than a decade. Conceptually, our algorithm shows that randomization along with a more direct approach can provide better bounds.