Buckets: smart objects for digital libraries
Communications of the ACM
A framework for distributed digital object services
International Journal on Digital Libraries
Self-arranging preservation networks
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
Unsupervised creation of small world networks for the preservation of digital objects
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Comparison of failures and attacks on random and scale-free networks
OPODIS'04 Proceedings of the 8th international conference on Principles of Distributed Systems
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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, Barabási and Albert power law, Watts --- Strogatz small world and our Unsupervise. 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 WOs filled with date could outlive the individuals and institutions that created the data in an environment where WOs are lost due to random failures or directed attacks.