Srikanta N Tirthapura

US Patent:

8392434, Mar 5, 2013

Filed:

Sep 16, 2011

Appl. No.:

13/234420

Inventors:

David P. Woodruff - Mountain View CA, US
Srikanta N. Tirthapura - Ames IA, US

Assignee:

International Business Machines Corporation - Armonk NY
Iowa State University - Ames IA

International Classification:

G06F 17/30

US Classification:

707748

Abstract:

Described herein are methods, systems, apparatuses and products for random sampling from distributed streams. An aspect provides a method for distributed sampling on a network with a plurality of sites and a coordinator, including: receiving at the coordinator a data element from a site of the plurality of sites, said data element having a weight randomly associated therewith deemed reportable by comparison at the site to a locally stored global value; comparing the weight of the data element received with a global value stored at the coordinator; and performing one of: updating the global value stored at the coordinator to the weight of the data element received; and communicating the global value stored at the coordinator back to the site of the plurality of sites. Other embodiments are disclosed.

US Patent:

8484269, Jul 9, 2013

Filed:

Jan 2, 2008

Appl. No.:

12/006333

Inventors:

Graham Cormode - Summit NJ, US
Philip Korn - New York NY, US
Srikanta Tirthapura - Ames IA, US

Assignee:

AT&T Intellectual Property I, L.P. - Atlanta GA

International Classification:

G06F 1/02

US Classification:

708270, 708274

Abstract:

Aggregates are calculated from a data stream in which data is sent in a sequence of tuples, in which each tuple comprises an item identifier and a timestamp indicating when the tuple was transmitted. The tuples may arrive at a data receiver out-of-order, that is, the sequence in which the tuples arrive are not necessarily in the same sequence as their corresponding timestamps. In calculating aggregates, more recent data may be given more weight by a decay function which is a function of the timestamp associated with the tuple and the current time. The statistical characteristics of the tuples are summarized by a set of linear data summaries. The set of linear data summaries are generated such that only a single linear data summary falls between a set of boundaries calculated from the decay function and a set of timestamps. Aggregates are calculated from the set of linear data summaries.

US Patent:

8533699, Sep 10, 2013

Filed:

Mar 31, 2011

Appl. No.:

13/077793

Inventors:

Mark S. Moir - Wllington, NZ
David Dice - Foxboro MA, US
Srikanta N. Tirthapura - Ames IA, US

Assignee:

Oracle International Corporation - Redwood City CA

International Classification:

G06F 9/45
G06F 9/46

US Classification:

717152, 717151, 718101, 718102

Abstract:

Systems and methods for optimizing code may use transactional memory to optimize one code section by forcing another code section to execute atomically. Application source code may be analyzed to identify instructions in one code section that only need to be executed if there exists the possibility that another code section (e. g. , a critical section) could be partially executed or that its results could be affected by interference. In response to identifying such instructions, alternate code may be generated that forces the critical section to be executed as an atomic transaction, e. g. , using best-effort hardware transactional memory. This alternate code may replace the original code or may be included in an alternate execution path that can be conditionally selected for execution at runtime. The alternate code may elide the identified instructions (which are rendered unnecessary by the transaction) by removing them, or by including them in the alternate execution path.

US Patent:

8645412, Feb 4, 2014

Filed:

Oct 21, 2011

Appl. No.:

13/278469

Inventors:

David P. Woodruff - Mountain View CA, US
Srikanta N. Tirthapura - Ames IA, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 17/30

US Classification:

707769

Abstract:

Described herein are approaches for computing correlated aggregates. An aspect provides for receiving a stream of data elements at a device, each data element having at least one numerical attribute; maintaining in memory plurality of tree structures comprising a plurality of separate nodes for summarizing numerical attributes of the data elements with respect to a predicate value of a correlated aggregation query, said maintaining comprising: creating the plurality of tree structures in which each node implements one of: a probabilistic counter and a sketch, wherein said probabilistic counter and said sketch each act to estimate aggregated data element numerical attributes to form a summary of said numerical attributes; and responsive to a correlated aggregation query specifying said predicate value, using said plurality of tree structures as a summary of said data element numerical attributes to compute a response to said correlated aggregate query.

US Patent:

20090172059, Jul 2, 2009

Filed:

Jan 2, 2008

Appl. No.:

12/006338

Inventors:

Graham Cormode - Summit NJ, US
Philip Korn - New York NY, US
Srikanta Tirthapura - Ames IA, US

International Classification:

G06F 17/00

US Classification:

708274

Abstract:

Aggregates are calculated from a data stream in which data is sent in a sequence of tuples, in which each tuple comprises an item identifier and a timestamp indicating when the tuple was transmitted. The tuples may arrive out-of-order, that is, the sequence in which the tuples arrive are not necessarily in the sequence of their corresponding timestamps. In calculating aggregates, more recent data may be given more weight by multiplying each tuple by a decay function which is a function of the timestamp associated with the tuple and the current time. The tuples are recorded in a quantile-digest data structure. Aggregates are calculated from the data stored in the quantile-digest data structure.

US Patent:

20130103713, Apr 25, 2013

Filed:

Aug 28, 2012

Appl. No.:

13/596514

Inventors:

David P. Woodruff - Mountain View CA, US
Srikanta N. Tirthapura - Ames IA, US

Assignee:

IOWA STATE UNIVERSITY RESEARCH FOUNDATION, INC. - Ames IA
INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

International Classification:

G06F 17/30

US Classification:

707769, 707E17014, 707E17044

Abstract:

Described herein are approaches for computing correlated aggregates. An aspect provides for receiving a stream of data elements at a device, each data element having at least one numerical attribute; maintaining in memory plurality of tree structures comprising a plurality of separate nodes for summarizing numerical attributes of the data elements with respect to a predicate value of a correlated aggregation query, said maintaining comprising: creating the plurality of tree structures in which each node implements one of: a probabilistic counter and a sketch, wherein said probabilistic counter and said sketch each act to estimate aggregated data element numerical attributes to form a summary of said numerical attributes; and responsive to a correlated aggregation query specifying said predicate value, using said plurality of tree structures as a summary of said data element numerical attributes to compute a response to said correlated aggregate query.

US Patent:

20130155892, Jun 20, 2013

Filed:

Jan 31, 2013

Appl. No.:

13/755621

Inventors:

Iowa State University Research Foundation, Inc. - Ames IA, US
Srikanta Tirthapura - Ames IA, US

Assignee:

IOWA STATE UNIVERSITY RESEARCH FOUNDATION, INC. - Ames IA
AT&T INTELLECTUAL PROPERTY I, L.P. - Atlanta GA

International Classification:

H04L 12/26

US Classification:

370252

Abstract:

Aggregates are calculated from a data stream in which data is sent in a sequence of tuples, in which each tuple comprises an item identifier and a timestamp indicating when the tuple was transmitted. The tuples may arrive out-of-order, that is, the sequence in which the tuples arrive are not necessarily in the sequence of their corresponding timestamps. In calculating aggregates, more recent data may be given more weight by multiplying each tuple by a decay function which is a function of the timestamp associated with the tuple and the current time. The tuples are recorded in a quantile-digest data structure. Aggregates are calculated from the data stored in the quantile-digest data structure.

US Patent:

20130212141, Aug 15, 2013

Filed:

Mar 26, 2013

Appl. No.:

13/850438

Inventors:

Iowa State University Research Foundation, Inc - , US
Srikanta Tirthapura - Ames IA, US

Assignee:

Iowa State University Research Foundation, Inc - Ames IA
AT&T Intellectual Property I, L.P. - Atlanta GA

International Classification:

G06F 17/10

US Classification:

708270

Abstract:

Aggregates are calculated from a data stream in which data is sent in a sequence of tuples, in which each tuple comprises an item identifier and a timestamp indicating when the tuple was transmitted. The tuples may arrive at a data receiver out-of-order, that is, the sequence in which the tuples arrive are not necessarily in the same sequence as their corresponding timestamps. In calculating aggregates, more recent data may be given more weight by a decay function which is a function of the timestamp associated with the tuple and the current time. The statistical characteristics of the tuples are summarized by a set of linear data summaries. The set of linear data summaries are generated such that only a single linear data summary falls between a set of boundaries calculated from the decay function and a set of timestamps. Aggregates are calculated from the set of linear data summaries