Microsoft Technology Licensing, LLC

Microsoft Corporation

Balan Sethu Raman

Beysim Sezgin

Arnold S Miller

Roman Schindlauer

Dave D Straube

Torsten Walther Grabs

Ahmed Hassan Mohamed

David Matthew Kruse

Jonathan David Goldstein

Pradyumna K Misra

Rajeev Bashyam Rajan

Aaron M Contorer

Michael R C Seaman

Shishir P Pardikar

Sameet Harishanker Agarwal

Sanjay Anand

Kangrong Yan

Tomer Verona

Paul J Leach

Chris J Guzak

Timothy P McKee

Badrish Chandramouli

David A Orbits

Robert E Corrington

Sudarshan Anand Chitre

Ciprian Gerea

Ping Wang

Joseph L Linn

David George De Vorchik

Yun Lin

Richard Bruce Ward

Praerit Garg

Mohammed Samji

Rohan Kumar

Colin Joseph Meek

Pradeep Madhavarapu

Nathaniel Harper Ballou

Srinivasmurthy P Acharya

Yuval Neeman

Ramkumar Krishnan

Sambavi Muthukrishnan

Mohamed Hassan Ali

Peter J Cook

Ram Ramasubramanian

Prasanna V Krishnan

Henricus Johannes Maria Meijer

James Robert Hamilton

Lev Novik

Kim Cameron

Surendra Verma

Alexander Douglas James

Jason Fergus Moore

Kirt A Debique

Pradeep Jnana Madhavarapu

Nigel Robin Ellis

Mihai Costea

Irena Hudis

Johannes Klein

Anil Kumar Nori

Michael W Thomas

Walter R Smith

Yunxin Wu

Robert H Gerber

Rodger N Kline

Eric R Flo

Songyun Duan

Bart J F De Smet

Anurag Gupta

Michael Eric Deem

J Patrick Thompson

Maxim Mazeev

Shaun A Kaasten

Anthony Frederick Voellm

Rajesh M Rao

John F Ludeman

Andrew G Bybee

Shrinivas Ashwin

Michael Warmington

Kevin Farlee

Samuel H Smith

David S Montague

Xin Jin

Jon Cargille

Jacob Lacouture

Shioupyn Shen

Murali M Krishna

Amit Shukla

Rafael De Jesús Fernández Moctezuma

Okechukwu C Echeruo

Salome Jacob

Mahadevan Venkatraman

Jeffrey M Saathoff

Joseph Trdinich

Sameet H Argawal

Roopali Kaujalgi

Galex Sunyul Yen

Asvin Ananthanarayan

Noa Zalic

Kendarnath A Dubhashi

Shishir Pardikar

The disclosed architecture leverages realtime continuous event processing (CEP) to address using a general input interface framework to import a dynamic set of event types (e.g., assets), and using a declarative, expressive query model to implement monitoring and management tasks on an asset level. This is in contrast to looking separately at single values from static databases and/or realtime streams as is common conventionally. The architecture uses the CEP data model to model assets as realtime event types. Thus, queries can be formulated per asset and not just per single stream. The architecture uses the query capabilities of CEP to formulate asset management and monitoring tasks as standing, declarative queries, and uses the input interface of a CEP platform to correlate data from different data sources with different dynamic properties.

Dynamic asset monitoring and management using a continuous event processing platform

The disclosed architecture utilizes realtime continuous event processing (CEP) to address the use of a general input interface framework to import a dynamic set of event types (e.g., assets), and a declarative, expressive query model to implement monitoring and management tasks on an asset level. In one implementation, a realtime event processing system is provided, comprising a synchronization component configured to synchronize realtime event data and static event data of assets, and a realtime merge component configured to merge the synchronized realtime event data and static event data into a realtime event stream using one or more operators. The merged synchronized realtime event data and static event data is queriable as a single event type using a query to return related asset items.

Evaluating an expression tree. A method includes, at a first domain, accessing an expression tree. The expression tree comprises a plurality of nested expressions. The plurality of nested expressions spans a plurality of domains. The expressions in the expression tree are expressed in a common format in spite of the different expressions of the expression tree being intended to be evaluated by different domains. At the first domain, the method includes evaluating one or more references to local variables included in the plurality of nested expressions. The method further includes determining that one or more expressions in the plurality of expressions are to be evaluated by a different domain. The method further includes expanding the one or more expressions in the plurality of expressions to be evaluated by different domains to allow the one or more expressions to be evaluated by the different domain.

Delegation of expression tree evaluation

Described are sequence numbers for client-server communication, to control a client's use of server resources. A server grants the client credits, and the client consumes a credit for sending each command to the server. Each credit corresponds to a sequence number, with the set of sequence numbers forming a valid command window. The server enforces that for each received command, the command includes a sequence number that is within the valid command window and that the sequence number has not been used with another command. The server may also maintain a maximum window size, such that clients with credits cannot send a command with a sequence number that beyond a maximum sequence number. When incorporated into a data communication protocol, quality of service, combating denial of service, detection of message loss, division of server resources, secure message signing, and other numerous benefits result.

Data communication coordination with sequence numbers

The present invention extends to methods, systems, and computer program products for altering event lifetimes. Embodiments of the invention include using operators in an event-processing framework (algebra) to shorten (or 'clip') the duration of events. An operator can receive a primary event stream, a clip event stream, and condition as parameters. The operator clips the lifetime of an event in the primary stream to the next event in the clip stream that fulfills the condition. Altering event lifetimes can be used to facilitate cleaning event stream state, converting point events to a continuous signal, and creating and annotating session events.

Altering event lifetimes

Aspects of the subject matter described herein relate to stream operators. In aspects, a stream event is received. Based on a timestamp associated with the stream event and the number of stream operators that have asked to be activated prior to or at the timestamp, zero or more stream objects are informed of one or more time events and torn down if no longer needed. In addition, a destination stream operator is instantiated, if needed, data (e.g., the timestamp and packet, if any) corresponding to the stream event is provided to a stream operator, output data, if any, is received from the stream operator, and the stream operator is torn down if it no longer needs state data between invocations.

Stream operator

A 'Real-Time-Ready Analyzer' combines a data stream management system (DSMS) with a map-reduce (M-R) framework to construct a streaming map-reduce framework that is suitable for real-time Behavioral Targeting (BT) (or other temporal queries). The Real-Time-Ready Analyzer allows users to write 'dual-intent' temporal analysis queries for BT. These queries are succinct and easy to express, scale well on large-scale offline data, and can also work over real-time data. Further, the Real-Time-Ready Analyzer uses the aforementioned streaming map-reduce framework to provide dual-intent algorithms for end-to-end BT phases. Experiments using real data from an advertisement system show that the Real-Time-Ready Analyzer is very efficient and incurs orders-of-magnitude lower development effort than conventional systems.

Real-time-ready behavioral targeting in a large-scale advertisement system

Methods, systems, and computer-readable media are disclosed for implementing adapters for event processing systems. A particular system includes an input adapter configured to store event objects received from a source at an input queue. The system also includes a query engine configured to remove event objects from the input queue, to perform a query with respect to the removed event objects to generate result objects, and to insert result objects into an output queue. The system also includes an output adapter configured to remove result objects from the output queue and to transmit the result objects to a sink.

Complex event processing (CEP) adapters for CEP systems for receiving objects from a source and outputing objects to a sink

An extensibility framework that allows a user to write user-defined modules that include user-defined operators (UDO) and user-defined aggregators (UDA) in a non-temporal fashion without the need to worry about temporal attributes of events (or event types). The temporal domain is managed on behalf of the user, and allows the user to write operators and aggregates in the temporal data streaming domain as well as to port existing libraries of non-temporal UDOs/UDAs to the temporal data streaming domain. Temporal attributes and event types are managed for non-temporal UDOs/UDAs by the extensibility framework on behalf of the UDO/UDA writer. Windows can be employed to bridge the gap between the non-temporal domains and temporal domains. Support for complex event processing (CEP) is provided in UDOs/UDAs for base classes related to a CEP operator, CEP aggregate, CEP time sensitive operator, and CEP time sensitive aggregate.

Extensibility model for stream-based operators and aggregates

Growing community of inventors

Redmond, WA, United States of America

Balan Sethu Raman