Replication and replacement in dynamic delivery networks

Abstract

Purpose: Content delivery in dynamic networks is a challenging task, because paths may change during delivery and content might get lost. Replication is a typical measure to increase robustness and performance. Method: In previous work we proposed a hormone-based algorithm that delivers content, and optimizes the distribution of replicas. Clients express demands by creating hormones that will be released to the network. The corresponding resources are attracted by this hormone and travel towards a higher hormone concentration. This leads to a placement of content close to their most frequent requesters. In addition to that the hormone-based delivery requires an appropriate replication and clean-up strategy to balance the replicas throughout the network without exceeding the nodes’ storage limits or the networks communication capacity. Results: We examine different combinations of replication and replacement strategies and evaluate them in realistic scenarios involving node failure and networks of different size and structure. Conclusion: Results show that it is necessary to match the replication mechanisms with the clean-up mechanism and that the local hormone information can be used to improve the clean-up decision.