Average Case Analysis of Dynamic Graph Algorithms

TitleAverage Case Analysis of Dynamic Graph Algorithms
Publication TypeTechnical Report
Year of Publication1995
AuthorsAlberts, D., & Henzinger M. Rauch
Other Numbers960
Abstract

We present a model for edge updates with restricted randomness in dynamic graph algorithms and a general technique for analyzing the expected running time of an update operation. This model is able to capture the average case in many applications, since (1) it allows restrictions on the set of edges which can be used for insertions and (2) the type (insertion or deletion) of each update operation is arbitrary, i.e., not random. We use our technique to analyze existing and new dynamic algorithms for the following problems: maximum cardinality matching, minimum spanning forest, connectivity, 2-edge connectivity, k-edge connectivity, k-vertex connectivity, and bipartiteness. Given a random graph G with m_0 edges and n vertices and a sequence of l update operations such that the graph contains m_i edges after operation i, the expected time for performing the updates for any l is O(l log n + n sum_{i=1}^{l} 1/sqrt m_i) in the case of minimum spanning forests, connectivity, 2-edge connectivity, and bipartiteness. The expected time per update operation is O(n) in the case of maximum matching. We also give improved bounds for k-edge and k-vertex connectivity. Additionally we give an insertions-only algorithm for maximum cardinality matching with worst-case O(n) amortized time per insertion.

URLhttp://www.icsi.berkeley.edu/ftp/global/pub/techreports/1995/tr-95-020.pdf
Bibliographic Notes

ICSI Technical Report TR-95-020

Abbreviated Authors

D. Alberts and M. R. Henzinger

ICSI Publication Type

Technical Report