International Business Machines Corporation

Kay Schwendimann Anderson

Zhen Liu

Anton Viktorovich Riabov

Nagui Halim

Parijat Dube

Joseph Phillip Bigus

Eric P Bouillet

Grant W Wagner

Mark David Feblowitz

Dimitrios Pendarakis

Pankaj Rohatgi

Pau-Chen Cheng

Angela Marie Schuett

Genady Grabarnik

Paul Ashley Karger

Shai Halevi

Ronald Perez

Michael Steiner

Trent Ray Jaeger

Genady Ya Grabarnik

Frederick Douglis

Joel Leonard Wolf

Ramakrishnan Srikant

John Michael Tracey

David Alson George

John Davis Palmer

William H Tetzlaff

Ralf Rantzau

Elizabeth Suzanne Richards

Alexandre Valentinovich Evfimievski

David Tao

Trenton Ray Jaeger

Marc Lelarge

Angela Schuett Reninger

A system and method for workload generation include a processor for identifying a workload model by determining each of a hierarchy for workload generation, time scales for workload generation, and states and transitions at each of the time scales, and defining a parameter by determining each of fields for user specific attributes, application specific attributes, network specific attributes, content specific attributes, and a probability distribution function for each of the attributes; a user level template unit corresponding to a relatively slow time scale in signal communication with the processor; an application level template corresponding to a relatively faster time scale in signal communication with the processor; a stream level template corresponding to a relatively fastest time scale in signal communication with the processor; and a communications adapter in signal communication with the processor for defining a workload generating unit responsive to the template units.

Template-based approach for workload generation

A system and method for processing an information unit/packet (IU) in a stream processing system includes decomposing an IU into sub-information units persisted other than in the IU. An index or reference is generated in the IU for retrieving the persisted sub-information units during processing.

Method and system for secure lightweight stream processing

A method for security planning with hard security constraints includes: receiving security-related requirements of a network to be developed using system inputs and processing components; and generating the network according to the security-related requirements, wherein the network satisfies hard security constraints.

System and method for security planning with hard security constraints

A system, method, and computer program product for benchmarking a stream processing system are disclosed. The method comprises generating a plurality of correlated test streams. A semantically related data set is embedded within each of the test streams in the plurality of correlated test streams. The plurality of correlated test streams is provided to at least one stream processing system. A summary is generated for each of the semantically related embedded data sets. A common identifier, which is transparent to the system being tested, is embedded within each stream in the plurality of correlated test streams. The common identifier is extracted from the output data set generated by the stream processing system. At least one of the stored copies of the summaries and the common identifier are compared to an output data set including a set of zero or more correlation results generated by the stream processing system.

Benchmarking correlated stream processing systems

An automatic planning system is provided for stream processing workflow composition. End users provide requests to the automatic planning system. The requests are goal-based problems to be solved by the automatic planning system, which then generates plan graphs to form stream processing applications. A scheduler deploys and schedules the stream processing applications for execution within an operating environment. The operating environment then returns the results to the end users.

Stream processing workflow composition using automatic planning

System and methods are provided for managing and mitigating privacy risks in a system having a network of processing elements. According to one method, there is receive a request for at least one output product from the system. The request includes a set of privacy parameters. At least one set of workflow generating strategies are created that results in the output product having a privacy risk value below a predefined threshold. At least one of the workflow generating strategies is deployed for automatically producing the at least one output product.

Mitigating and managing privacy risks using planning

A method for security planning with soft security constraints, include: receiving security-related requirements of a workflow to be developed using system inputs and processing components; and generating at least one proposed workflow according to the security-related requirements, wherein the at least one proposed workflow satisfies soft constraints.

System and method for security planning with soft security constraints

An exemplary method is provided for managing and mitigating security risks through planning. A first security-related information of a requested product is received. A second security-related information of resources that are available for producing the requested product is received. A multi-stage process with security risks managed by the first security-related information and the second security-related information is performed to produce the requested product.

Method of managing and mitigating security risks through planning

A system and method for optimizing a storage system to support short data object lifetimes and highly utilized storage space are provided. With the system and method, data objects are clustered based on when they are anticipated to be deleted. When an application stores data, the application provides an indicator of the expected lifetime of the data, which may be a retention value, a relative priority of the data object, or the like. Data objects having similar expected lifetimes are clustered together in common data structures so that clusters of objects may be deleted efficiently in a single operation. Expected lifetimes may be changed by applications automatically. The system automatically determines how to handle these changes in expected lifetime using one or more of copying the data object, reclassifying the container in which the data object is held, and ignoring the change in expected lifetime for a time to investigate further changes in expected lifetime of other data objects.

Optimizing a storage system to support short data lifetimes

System and method for benchmarking correlated stream processing systems

Growing community of inventors

Washington, DC, United States of America

Kay Schwendimann Anderson