Emc IP Holding Company LLC

Emc Corporation

Motorola Corporation

Freescale Semiconductor,inc.

Open Text Corporation

Vitaly Stanislavovitch Kozlovsky

Dmitry Nikolayevich Tylik

Thirumale N Niranjan

Ivan Valentinovich Gumenyuk

Inga Petryaevskaya

Mikhail Alexandrovich Ilyin

Artem Alexandrovich Aliev

Yuri Zagrebin

Nikolay Vyatkin

Alexander Shadrin

Jyh-Han Lin

Sergey Alexandrovich Alexeev

Alexey Vladimirovich Shusharin

Alexey Fomin

Ivan Andreyev

Misha Zelikov

Mikhail Yurievitch Zakharov

Andrey Pakhomov

Vladimir D Ivanov

Howard Dewey Owens

David M Zeryck

Eugeny Alexeevich Novozhilov

Dave Zeryck

Alexander Belov

Aleksandr Yevgenyevitch Maklakov

Aleksandr Valentinovich Shadrin

Mikhail Aleksandrovich Ilyin

Alexey Vyatcheslavovitch Petrochenko

Ilya Shavlyuk

Viatcheslav Kirilline

Valdimir Ivanov

Denis Serov

Konstantin Tyapochkin

Vladimir Krupsky

A system for document capture comprising a communication interface, a processor coupled to the communications interface, and a computer readable medium coupled to the processor. The computer readable medium stores a set of computer executable instructions that include instructions executable by the processor to receive an input capture flow comprising a first sequence of steps representing configurable code components of a document capture system. A step in the first sequence of steps holds configuration information for a corresponding configurable code component. The instructions further include instructions executable to compile the input capture flow into a capture process that defines a processing order for the configurable code components and setup attribute values for the configurable code components. Compiling the input capture flow into the capture process comprises optimizing the capture flow into a second sequence of steps and compiling the second sequence of steps into the capture process.

Document processing system capture flow compiler

Automated Tiered Storage (ATS) has become widely accepted technique in IT industry. Since IO data has different data densities on storage systems, higher storage capacity and improved performance can be achieved by combining two or more storage device tiers having different performance and cost characteristics. These multiple different storage device tiers can be combined into one automated storage pool, which automatically chooses optimal data placement for achieving both the highest performance and the lowest cost. When the storage device tier information can be stored as metadata for each of the data chunks. When there is a system failure and data needs to recovered, the device tier information metadata can be used to restore data to the predetermined optimum storage device tier of the ATS system which shortens the post-recovery warm-up time.

Dynamic rule based model for long term retention

Methods and apparatus are provided for block similarity based block level deduplication of data. An exemplary method comprises obtaining a deduplicated dataset comprising a plurality of unique data chunks; determining a number of differences between two of the unique data chunks; evaluating whether the number of differences satisfies a predefined similarity criteria (e.g., that the number of bit differences cannot exceed a specified limit); and storing metadata for a first one of the two unique data chunks if the predefined similarity criteria is satisfied for the two unique data chunks, wherein the metadata comprises a pointer to a second one of the two unique data chunks and bit differences between the two unique data chunks. The bit differences comprise an executable code and/or a bit mask. The predefined similarity threshold is optionally a tunable parameter. The first one of the two unique data chunks can be restored by processing the metadata.

Block level deduplication with block similarity

Systems and methods for efficient deduplication and/or provisioning of LUNs are disclosed. A first unique data block pool for a first LUN of a plurality of deduplicated LUNs is accessed, the first unique data block pool comprising a first plurality of unique data blocks for representing data stored on the first LUN. A second unique data block pool for a second LUN of the plurality of LUNs is accessed, the second unique data block pool comprising a second plurality of unique data blocks for representing data stored on the second LUN. It is determined a correspondence metric for the first unique data block pool and the second unique data block pool exceeds a pre-determined threshold. The first LUN and the second LUN are joined to form a first combined LUN. The first unique data block pool and the second unique data block pool are joined.

Efficient deduplication of logical units

Example embodiments of the present invention relate to a method, an apparatus, and a computer program product for IT appliance control. The method comprises determining an action regarding a storage system, encoding the action regarding the storage system, and representing the action regarding the storage system as a graphical representation.

Method and apparatus for IT appliance control

There is disclosed techniques for use in providing an optimal configuration for a data storage system. In one example, a method comprises the following steps. A request is received from a user to assist in the configuration of the data storage system. The request is received remote from the data storage system and includes values of application workload parameters. Optimal configuration parameters are determined for the data storage system in response to receiving the request. The optimal configuration parameters are determined based on the application workload parameters and one of a model and application best practices. Additionally, the optimal configuration parameters are provided to a target system such that the target system is able to establish the optimal configuration for the data storage system.

Optimal data storage configuration

Improved techniques involve comparing access patterns in a storage system to expected access patterns under similar circumstances. An intrusion detection system, in response to a suspected malicious application workload, collects information about a current session on the storage processor, e.g., application workload s running, users logged in, and timestamp, as well as parameters such as storage allocation requests sampled at prespecified intervals over a period of time. In a database that stores such sampled parameter values by application workload, user, and time, the system extracts the sampled parameter values having the application workload, user, and time corresponding to the current session. The system then compares the extracted sampled parameter values with the current parameter values and computes a difference. Based on the difference, the system determines whether the storage system is accessed by a malicious application workload.

Dynamic malicious application detection in storage systems

Embodiments are described for systems and methods that optimize large-scale data transfers over a wide area network by providing a data transmission protocol stack comprising a TCP layer that exchanges data processed by a host, and an IP layer that transports datagrams encapsulating the data to routers in the WAN, and a UDP-based transmission layer within the data transmission protocol stack that interfaces with the TCP layer and transmits data and control packets between the host and receivers of the WAN using a unicast duplex protocol. The stack has a WAN optimization components layer that interacts with the UDP-based transmission layer and provides transport protocol optimization through the UDP-based transmission layer and certain data de-duplication, compression, link aggregation, and application awareness functions.

Big data transfer optimization

A method is used in retrieving data from data storage systems. A nonvolatile memory module connected to a data storage system is detected. The data storage system uses information stored in the nonvolatile memory module to initiate an action. Based on the information, the action is performed. The action includes retrieving data from the data storage system to the nonvolatile memory module.

Retrieveing data from data storage systems

A method, computer program product, and computing system for defining a storage pool for a storage system being designed that includes a plurality of storage tiers. Each storage tier has a different level of performance. A plurality of workloads are defined for the storage system, wherein each of the plurality of workloads includes: a target skew factor, a capacity requirement, and a IOPS requirement. A density function is generated for each of the plurality of workloads based, at least in part, upon the target skew factor for each of the plurality of workloads. A consolidated system loading report is generated based, at least in part, upon the target skew factor for each of the plurality of workloads.

Tiered-storage design

An improved technique involves providing application workload simulation capability via a centrally located synthetic data generation service to an external party. Along these lines, a client inputs a description of an application scenario into a web form which sends a request to a central server to generate a synthetic data simulation program. The central server extracts parameters values from the request corresponding to the application scenario and finds a model in a model database based on the parameter values. From the model, the central server derives a Java program that generates synthetic data for simulating the operation load of the application scenario described by the client, and sends the Java program to the client. The client is then able to generate synthetic data using the Java program on various configurations to determine which will successfully handle the synthetic data load continuously over a given period of time.

Public service for emulation of application load based on synthetic data generation derived from preexisting models

Improved efficiency in monitoring environmental conditions in the vicinity of an unattended computer system includes using the existing communication systems between the computer system and a network, to provide immediate information to users, emergency responders and anyone connected to the network. The system may also include an ability of the unattended computer system to receive a return message from the user ordering a physical action in response to the reported environmental condition, for example turning on a fire suppression system in response to a smoke alarm. The system may also include storage of environmental conditions and analysis of variations over time, as well as any interactions of various types of environmental conditions, such as giving more weight to a high temperature reading in conjunction with an elevated but not critical level of smoke.

Environmental alert for computer systems

Described are techniques for analyzing storage resources. I/O operations which are directed to a set of storage resources and received at a data storage system from a first application are monitored. First information characterizing the I/O operations from the first application is collected in accordance with said monitoring. Using the first information, a first execution profile for the first application characterizing I/O operations of the first application is determined. It is determined whether the first execution profile of the first application matches any of a set of predetermined execution profiles for known applications. Each of the predetermined execution profiles characterizes I/O operations of one of the known applications. First processing is performed in accordance with one or more criteria including whether the first execution profile matches any of the set of predetermined execution profiles.

Storage resource usage analysis for customized application options

The invention is a system and method for generating a file system model at a selected point in time without requiring sequential generation of file system models for each point in time prior to the selected point in time. Present data modeling require that data be generated using some initial point, then passed through time intervals in order to simulate the data at a later point in time. The invention does not require sequential data generation. Instead, any arbitrary point in time may be selected, and the data may be modeled at that selected timepoint. The invention stores a compact representation of file system data for each timepoint. Whenever a user wants to simulate data at some timepoint, the proper compact representation is selected and expanded to produce a simulation of the data at that timepoint.

System and method for file system simulation

An improved technique involves generating a predictive model for data storage system configuration management. A customer support center generates such a predictive model from detailed customer configuration and transaction history. For example, a population of customers submits transaction logs to the customer support center; such transaction logs provide details as to how the customers responded to various events. The population of customers may also submit data including various statistics such as load intensity, workload characteristics, data access patterns, data change patterns, and data fingerprints to the customer support center. The customer support center then performs an analysis on the data and, from the analysis, computes values of model parameters that define a predictive model. This predictive model is configured to take in a particular state of any data storage system and produce a configuration that optimizes performance of that data storage system.

Growing community of inventors

Saint-Petersburg, Russia

Vitaly Stanislavovitch Kozlovsky