International Business Machines Corporation

Moshik Hershcovitch

Danny Harnik

Yaron Weinsberg

Paula Kim Ta-Shma

Yosef Shatsky

Ronen Itshak Kat

Asaf Porat-Stoler

A computer program product and a system comprising: a cluster of Secure Execution Platforms (SEPs) having connectivity to a data storage, each SEP of said cluster is configured to maintain, using a key, confidentiality of data while processing thereof; the key is shared among the SEPs of said cluster, the key is automatically generated by the cluster or portion thereof and is unavailable to any non-cluster entity; the data storage retains encrypted data that is encrypted using the key; a first SEP of the cluster is configured to encrypt client data using the key to obtain encrypted client data and store the encrypted client data in the data storage; and a second SEP of the cluster is configured to retrieve encrypted stored data from the data storage, decrypt the encrypted stored data using the key to obtain non-encrypted form of the encrypted stored data.

Cluster of secure execution platforms

A computer-implemented method, according to one embodiment, includes: determining which of a plurality of fingerprints correspond to a copy of user data stored in one or more logical volumes at a storage location, and which of the plurality of fingerprints correspond to a pointer that points to a copy of user data stored in the one or more logical volumes at the storage location. A number of unique fingerprints is determined, and a number of the copies of user data stored in the one or more logical volumes is determined. The number of the copies of user data and the number of unique fingerprints are used to calculate an actual deduplication efficiency value. The number of the copies of user data and the number of unique fingerprints are used to calculate a potential deduplication efficiency value. The actual deduplication efficiency value is compared to the potential deduplication efficiency value.

Online measurement of potential deduplication efficiency

A system to reduce the amount of storage and memory used to maintain derived datasets is disclosed. The system operates by using pointers to the underlying data in persistent, byte-addressable storage media. The system additionally reduces the creation time of the views when storage class memory (SCM) is the underlying storage. Furthermore, the invention relates to a form of compression that is tailored to the use cases of big data analytics. The processes of this disclosure use random access to significantly improve performance.

Growing community of inventors

Tel Aviv, Israel

Moshik Hershcovitch