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Data replication is a very relevant technique for improving performance, availability and scalability. These are requirements of many applications such as multiplayer distributed games, cooperative software tools, etc. How- ever, consistency of the replicated shared state is hard to ensure. Current consistency models and middleware sys- tems lack the required adaptability and efficiency. Thus, developing such robust applications is still a daunting task. We propose a new consistency model, named Vector- Field Consistency (VFC), that unifies i) several forms of consistency enforcement and a multi-dimensional criteria (time, sequence and value) to limit replica divergence, with ii) techniques based on locality-awareness (w.r.t. players position). Based on the VFC model, we propose a generic meta- architecture that can be easily instantiated both to cen- tralized and (dynamically) partitioned architectures: i) a single central server in which the VFC algorithm runs, or b) a set of servers in which each one is responsible for a slice of the data being shared. The first approach is clearly more adapted to ad-hoc networks of resource-constrained devices while the second, being more scalable, is well adapted to large-scale networks. We developed and evaluated two pro- totypes of VFC (for ad-hoc and large-scale networks) with very good performance results.

Unifying divergence bounding and locality awareness in replicated systems with vector-field consistency