1. A method comprising: processing one or more social graphs associated with one or more users to cause a prediction of one or more future states of the one or more social graphs, wherein processing the one or more social graphs comprises, determining respective information trajectories defining a finite set of possible, nearest future states of the respective one or more social graphs, extracting historical patterns based on the one or more social graphs, and selecting the one or more future states from the set of possible future states based at least in part on the most recent historical patterns; and clustering one or more data items distributed over a plurality of storage partitions in a cloud, associated with at least one information space and at least one computation space, based, at least in part, on the one or more social graphs, the one or more future states, or a combination thereof, wherein the at least one information space comprises data associated with a user of a social network and the at least one computation space comprises computation closures associated with computation resources of the cloud, based, at least in part, on processing and maintaining the one or more social graphs, wherein computation closures identify a respective computation procedure together with relations and communications among one or more processes including one or more of passing arguments, sharing process results, selecting results provided from computation of alternative inputs or flow of data.
1. A method comprising: processing one or more social graphs associated with one or more users to cause a prediction of one or more future states of the one or more social graphs, wherein processing the one or more social graphs comprises, determining respective information trajectories defining a finite set of possible, nearest future states of the respective one or more social graphs, extracting historical patterns based on the one or more social graphs, and selecting the one or more future states from the set of possible future states based at least in part on the most recent historical patterns; and clustering one or more data items distributed over a plurality of storage partitions in a cloud, associated with at least one information space and at least one computation space, based, at least in part, on the one or more social graphs, the one or more future states, or a combination thereof, wherein the at least one information space comprises data associated with a user of a social network and the at least one computation space comprises computation closures associated with computation resources of the cloud, based, at least in part, on processing and maintaining the one or more social graphs, wherein computation closures identify a respective computation procedure together with relations and communications among one or more processes including one or more of passing arguments, sharing process results, selecting results provided from computation of alternative inputs or flow of data. 8. A method of claim 1 further comprising: determining one or more information state trajectories based, at least in part, on an inference action, a conceptual clustering, an analogy creation, one or more working conditions, a fault prediction, one or more usage patterns, a workload estimation, or a combination, wherein the one or more data items are retrieved from the plurality of the partitions within a plurality of distributed storages based, at least in part, on the one or more social graphs, the one or more future states, or a combination thereof.