Международный журнал роевого интеллекта и эволюционных вычислений

Абстрактный

Optimising Data Access with an Adaptive Geo-Replication Strategy

Amadeo Ascó

The amount of data being processed in Data Centres (DCs) keeps growing at an enormous rate so that full replication may start being impractical. One way to increase data availability can be accomplished using replication between DCs so data may be accessed locally, if possible, which allows to recover in the presence of site failures and reduce access costs. This means that replicating the data only in some of the DCs is becoming more critical to reduce the costs of keeping the data consistent or eventually consistent and still maintaining a high availability (scalability) and low access costs. The data locations overall the DCs must be determined dynamically giving the changing patterns of read and write requests for the data to be replicated. Given that the problem of finding an optimal replication schema in a general network has been shown to be NP-complete for the static case, it is unlikely to be able to generate a general algorithm to find efficient solutions to the dynamic problem. An adaptive bio-inspired replication strategy is presented here, which is completely decentralised, adaptive, inspired on the Ant Colony algorithm, and event-driven. Also, the replication protocol is independent of the strategy implemented but it is guided by the strategy.