Actifio, Inc.

Keith Goldberg

Christopher A Provenzano

Philip J Abercrombie

Described herein are systems and methods for garbage collection prediction. A temporal graph is received, the temporal graph including nodes, the nodes including hash references to objects. An accumulated difference count is updated when a node is added to the temporal graph, the accumulated difference count including a number of hash differences between a parent node and its children nodes in the temporal graph. A divested difference count is updated when a node is removed from the temporal graph, the divested difference count including a number of hash differences referenced by the removed node but not by either a parent node of the removed node or any child nodes of the removed node. The outcome of the garbage collection is predicted based on at least one of the accumulated difference count and the divested difference count.

Garbage collection predictions

Described herein are systems and methods for efficient data replication. A set of hashes for a source object to be replicated is sent from the source local deduplication store to the remote server. The remote server generates a set of object hashes representative of data in the source object that is already present on the remote server, and data indicative of source object hashes that are not present on the remote server. The remote server transmits the generated data to the source local deduplication store. The source local deduplication store identifies portions of the source object that are not already present on the remote server based on the received data. The source local deduplication store transmits the identified portions of the source object to the remote server to replicate the source object on the remote server.

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Waltham, MA, United States of America

Keith Goldberg