As users interact with an increasing array of personal computing devices, maintaining consistency of data across those devices becomes significantly more difficult. Typical solutions assume either access to centralized servers, continual connectivity, or unbounded storage and CPU capacity. In practice, users own devices with widely varying processing and storage capabilities that use intermittent or sparsely-connected networks and incur (often asymmetric) transfer costs. We identify the conditions that enable the seamless management of a user's data across devices and present a multi-agent system built upon a decision-theoretic approach to constructing and executing multiple plans to achieve consistency in a peer-to-peer, partially observable, non-deterministic environment. We analyze the performance of these plans in comparison to a standard epidemic replication algorithm used in many database consistency applications.
David L. Roberts, Sooraj Bhat, Charles Lee Isbell