Analysis of Graphs for Digital Preservation Suitability

TL;DR

This paper evaluates the robustness of various graph models, including small-world and USW graphs, for long-term digital object storage under attack, showing USW graphs' superior resilience.

Contribution

It introduces the USW graph model and compares its robustness against other graph types under attack and repair strategies.

Findings

Watts-Strogatz small-world graphs are more resilient than random and power law graphs.

USW graphs outperform small-world graphs in robustness and resilience.

Power law graphs are highly vulnerable, disintegrating with minimal edge removal.

Abstract

We investigate the use of autonomically created small-world graphs as a framework for the long term storage of digital objects on the Web in a potentially hostile environment. We attack the classic Erdos - Renyi random, Barab'asi and Albert power law, Watts - Strogatz small world and our Unsupervised Small-World (USW) graphs using different attacker strategies and report their respective robustness. Using different attacker profiles, we construct a game where the attacker is allowed to use a strategy of his choice to remove a percentage of each graph's elements. The graph is then allowed to repair some portion of its self. We report on the number of alternating attack and repair turns until either the graph is disconnected, or the game exceeds the number of permitted turns. Based on our analysis, an attack strategy that focuses on removing the vertices with the highest betweenness value is most advantageous to the attacker. Power law graphs can become disconnected with the removal of a single edge; random graphs with the removal of as few as 1% of their vertices, small-world graphs with the removal of 14% vertices, and USW with the removal of 17% vertices. Watts - Strogatz small-world graphs are more robust and resilient than random or power law graphs. USW graphs are more robust and resilient than small world graphs. A graph of USW connected web objects (WOs) filled with data could outlive the individuals and institutions that created the data in an environment where WOs are lost due to random failures or directed attacks.