International Business Machines Corporation

Sameh Afif Fakhouri

Vijay Krishnarao Naik

John Arthur Pershing, Jr

William Francis Jerome

Vijay A Kumar

Krishna Kummamuru

Pradeep Varma

Ajay Raina

Liana Liyow Fong

Peter Richard Badovinatz

Tushar Deepak Chandra

Felipe Knop

Chun-Shi Chang

Dennis Duane Jurgensen

John Joseph Edward Turek

Srirama Mandyam Krishnakumar

Timothy L Race

Peter B Badovinatz

A decision support system called Mounties that is designed for managing applications and resources using rule-based constraints in scalable mission-critical clustering environments. Mounties consists of four active service components: (1) a repository of resource proxy objects for modeling and manipulating the cluster configuration; (2) an event notification mechanism for monitoring and controlling interdependent and distributed resources; (3) a rule evaluation and decision processing mechanism; and (4) a global optimization service for providing decision making capabilities. The focus of this paper is on the design of the first three services that together connect and coordinate the distributed resources with the decision making component.

Decision based system for managing distributed resources and modeling the global optimization problem

An embodiment of the invention provides a method of managing a cluster of networked resources and resource groups using rule-based constraints. This method includes the step of building a globally optimal cluster configuration of the resources in accordance with the rule-based constraints and a current state of the resources, including identifying for each of the resources and resource groups an availability and quality of service, which are determined by dependencies among the resources and resource groups, resource equivalency, constraints on the resources and network policies. The method comprises the further steps of bringing the cluster of resources on-line in a systematic manner, given the current state of each of the resources and resource groups; and with the cluster of networked resources on-line, determining dynamic dependencies of and configuration infomration about the cluster of resources (i) statically at defined times and (ii) dynamically during cluster operation.

Managing a cluster of networked resources and resource groups using rule - base constraints in a scalable clustering environment

A topology propagation facility is provided for maintaining a common network topology database at different nodes in a distributed computing environment. The facility generates no message traffic when the distributed computing environment is in steady state. This is accomplished by discontinuing sending of group connectivity messages during a time period of no topology change within the distributed environment. Sending of group connectivity messages is reinitiated from at least one group leader upon identification by the group leader of at least one topology change within the distributed computing environment. Group connectivity messages are forwarded from one group of nodes on a first network to another group of nodes on a second network using a node common to both groups of nodes. The networks of the distributed computing environment can comprise heterogenous networks such that the topology propagation facility presented facilitates interoperability of the networks.

Topology propagation in a distributed computing environment with no topology message traffic in steady state

The number of instances of an application running in a computing environment are controlled by monitoring the current load on the application, and altering the current number of instances of the application based on results of the monitoring. The load may be monitored by monitoring the current number of instances of the application running in the computing environment. Where a maximum, minimum and/or initial number on startup, of instances of the application are specified, the altering is done based on comparing the current number to one or more of the specified numbers of instances.

Controlling a number of instances of an application running in a computing environment

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New Rochelle, NY, United States of America

Sameh Afif Fakhouri