International Business Machines Corporation

Liangzhao Zeng

Jenny S Li

Hui Lei

Yu Deng

Han Chen

Nicholas C Fuller

Rick A Hamilton, Ii

Christopher J Dawson

Kun Bai

Li Feng Zhang

Lisa Seacat DeLuca

Al Chakra

Minkyong Kim

Hung-Yang Chang

Zhe Zhang

Ming Li

Min Li

Hao Yang

Nicholas C M Fuller

Lawrence H Koved

Jian Tan

Shicong Meng

Xiaolan Zhang

Jun-Jang Jeng

Trent Ray Jaeger

Fei Wang

Maja Vukovic

Pawan Raghunath Chowdhary

Sriram K Rajagopal

Hani Talal Jamjoom

Jim Alain Laredo

Guo Tong Xie

Daniel Nikolaus Bauer

Shyh-Kwei Chen

Fan Ye

Gidon Gershinsky

Christoph Lingenfelder

Nicholas David Butler

Trieu Can Chieu

Konstantin Shagin

David Leslie Cohn

Joachim H Frank

Kristijan Dragicevic

Hung-yang Chang

Marc-Thomas H Schmidt

David Rushall

Anca Sailer

Thomas E Chefalas

Frank Andre Schaffa

Vijay Krishnarao Naik

Alla Segal

Chang-Shing Perng

Ignacio Silva-Lepe

Santhosh Babu Kumaran

Jen-Yao Chung

Tao Tao

Teruo Koyanagi

Hiroyasu Ohsaki

Theresa Y Tai

Leslie S Liu

Xinxin Zhu

Kyriakos Karenos

Chang Shu

Joachin H Frank

A model-driven and QoS-aware infrastructure facilitates the scalable composition of Web services in highly dynamic environments. An exception management framework supports two modes of exception management for business processes, providing a novel policy-driven approach to exception management implemented in the system infrastructure. Exception management is implemented in the system infrastructure, with exception handling policies supplied by individual business processes. Using the exception management framework, developers define exception policies in a declarative manner. Before a business process is executed, the service composition middleware integrates the exception policies with normal business logic to generate a complete process schema. This policy driven-approach can significantly reduce the development time of business processes through its separation of the development of the business logic and the exception handling policies.

Apparatus and method for policy-driven business process exception handling

An approach for conversion between database formats (e.g., from a relational database format to a hash table or a 'big table' database format) based on user data access patterns in a networked computing environment is provided. A first set of database tables having a first format is identified based on a set of access patterns stored in a computer storage device. A second set of database tables having a second database format corresponding to the first set of database tables may then be provided (e.g., accessed, augmented, and/or generated). A mapping between the first set of database tables and the second set of database tables may then be created. A column set may then be generated based on at least one condition of the set of queries. The column set may then be used as a key for the second set of database tables.

Database table format conversion based on user data access patterns in a networked computing environment

A mechanism for declarative service domain federation uses a declarative approach to both the visibility aspect and the management aspect of service domain federation. Instead of manually exporting services, that is, selecting individual services from source domains to be visible in the target domain, using the present system, a federation architect uses a federation console to specify federation intent. The federation intent may include federation rule, query-based service group, and quality-of-service (QoS) policy. Based on the declared federation intent, a planning engine resolves the individual services based on the group query, generates the service visibility configuration, and creates the necessary service proxies and/or mediation objects to satisfy the goal. At runtime, a service monitor collects the performance metrics of federated services and dynamically adjusts the mediation/proxy configurations to maintain the QoS objectives specified by the federation architect.

Declarative service domain federation

One or more processors receive information regarding a program module that includes a description of a function, license terms, and non-functional properties of the program module. The license terms, the description of function, and the non-functional properties of the program module are identified, based on an analysis of the information. An object of interest of each license term of the license terms is determined, such that the object of interest is directed to a condition influencing license term compliance. Rules corresponding to compliance of the one or more license terms of the program module are determined, and the analyzed information of the program module is stored in a meta-model format organized into categories including the description of function, the one or more license terms, and the non-functional properties of the program module, utilizing standardized syntax and semantics.

Automatic generation of license terms for service application marketplaces

Methods, systems, and articles of manufacture for dynamic resource allocation in MapReduce are provided herein. A method includes partitioning input data into one or more sized items of input data associated with a MapReduce job; determining a total number of mapper components, and a total number of reducer components for the MapReduce job based on said partitioning; dynamically determining an allocation of resources to each of the total number of mapper components and reducer components during run-time of the MapReduce job, wherein said dynamically determining the allocation of resources comprises monitoring one or more utilization parameters for each of the total number of mapper components and total number of reducer components during run-time of the MapReduce job; and dynamically determining a number of concurrently executing mapper components and reducer components from the total number of mapper components and the total number of reducer components for the MapReduce job.

Dynamic resource allocation in MapReduce

Methods, systems, and articles of manufacture for enabling dynamic task-level configuration in MapReduce are provided herein. A method includes generating a first set of configurations for a currently executing MapReduce job, wherein said set of configurations comprises job-level configurations and task-level configurations; dynamically modifying configurations associated with a mapper component and/or a reducer component associated with at least one ongoing map task and/or ongoing reduce task of the MapReduce job based on the generated first set of configurations; and deploying said first set of configurations to the mapper component and/or the reducer component associated with the MapReduce job.

Enabling dynamic job configuration in mapreduce

Embodiments of the present invention provide an approach to repair vulnerabilities (e.g., security vulnerabilities) in images (e.g., application images) in a networked computing environment (e.g., a cloud computing environment). Specifically, an image is checked for vulnerabilities using a database of known images and/or vulnerabilities. If a vulnerability is found, a flexible/elastic firewall is established around the image so as to isolate the vulnerability. Once the firewall has been put in place, the vulnerability can be repaired by a variety of means such as upgrading the image, quarantining the image, discarding the image, and/or generating a new image. Once the image has been repaired, the firewall can be removed.

Image vulnerability repair in a networked computing environment

Embodiments of the disclosure relate to controlling access to a mobile device with a paired device. Aspects include pairing the paired device with the mobile device and defining a security profile for the mobile device. Aspects also include receiving a user access request for a desired action via the mobile device and determining signal strength between the paired device and the mobile device. Aspects further include executing the desired action based on a determination that the signal strength is greater than a threshold in the security profile for the desired action.

Controlling mobile device access with a paired device

Embodiments include method, systems and computer program products for searching a social network for media content. Aspects include receiving a query for media content related to a topic from a user, identifying a plurality of content items associated with the topic and determining a quality score for each of the plurality of content items. Aspects also include providing a subset of the plurality of content items to the user, wherein the subset is selected based on the quality score and updating the quality score of one or more content items in the subset based on a behavior of the user in viewing the subset of the plurality of content items.

Search engine analytics and optimization for media content in social networks

A computer program product comprising a tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for implementing a data analysis method is provided. The data analysis method includes generating first data identifying traversed cellular areas and time spent by a mobile device in each, wherein the mobile device is disposable to be carried by a user from first to second locations and to thereby traverse the cellular areas, generating second data identifying the first and second locations as well as time spent by the mobile device in each and performing, by a processor for output to a wellness professional, a wellness analysis of a user based on medical data and the first and second data.

Data analysis system with movement patterns for medical wellness correlation

Methods, systems, and computer program products for dynamic tuning of memory in MapReduce systems are provided herein. A method includes analyzing (i) memory usage of a first sub-set of multiple tasks associated with a MapReduce job and (ii) an amount of data utilized across the first sub-set of the multiple tasks; determining a memory size to be allocated to the first sub-set of the multiple tasks based on said analyzing, wherein said memory size minimizes a cost function related to said memory usage and said amount of data utilized; performing a task-wise performance comparison among a second sub-set of the multiple tasks associated with the MapReduce job using the determined memory size to be allocated to the first sub-set of the multiple tasks to generate a set of memory allocation results; and dynamically applying the set of memory allocation results to one or more additional tasks associated with the MapReduce job.

Dynamic tuning of memory in MapReduce systems

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Liangzhao Zeng