Abstract: A system and method for managing a plurality of agents in a plurality networked computing hosts. In various embodiments, a repository is provided with references to installation code for installing the agents. Boot stubs are executable on the hosts. The boot stubs retrieve references to the installation code and load the installation code on the hosts. A directory contains topology data that indicate the hosts on which boot stubs and agents are installed, and an initiator retrieves the topology data and initiate execution of the boot stubs.

Abstract: Techniques are provided for automatically deploying software packages. Management agents represent these packages, a logical tree represents the deployed structure, and a node of the tree represents a management agent. A node that does not have any child node is referred to as a leaf node. A recursive process associated with at least one repository generates the structure. The repositories include information for configuring the nodes and thus control the deployment process. During deployment, a non-leaf node, referred to as an initiator node, uses information received from a corresponding repository to generate its child nodes. A child node, if being an initiator node, recursively generates its child nodes until the recursive process stops as there is no additional child node to be generated. Further, node identifiers are automatically established and assigned to respective nodes.

Abstract: Method and apparatus for optimizing allocation of computer resources between server and service models. A server model is established in response to user input data. The server model includes one or more server nodes, and each server node has an associated set of capacity attributes. In addition, a service model is established that includes one or more service nodes. Each service node has an associated set of demand attributes. In response to a user selection, one of a plurality of optimization methods and one of a plurality of optimization policies, as embodied in objective functions, are selected for mapping the server nodes and service nodes. An optimized mapping is then generated of the server nodes in the server model to the service nodes in the service model using the selected optimization method, along with the demand and capacity attributes.

Abstract: Method and apparatus for representing capacities and demands in a layered computing environment using normalized values for identifying optimal allocations of computing resources. A plurality of server models are established, with each server model including one or more server nodes and each server node having an associated set of capacity attributes. Similarly, a plurality of service models are established, each service model including one or more service nodes and each service node having an associated set of demand attributes. The server models are defined with a layered relationship as are the service models. A node that is part of a model in one layer corresponds to a model in the next-lower layer. The invention normalizes the demand and capacity attributes of the server nodes and service nodes in the different model layer in order to generate optimized mappings of service nodes to server nodes.

Abstract: Method and framework for identifying optimal allocations of computing resources in a complex, distributed data processing environment. A plurality of server models are established, with each server model including one or more server nodes and each server node having an associated set of capacity attributes. Similarly, a plurality of service models are established, each service model including one or more service nodes and each service node having an associated set of demand attributes. The server models are defined with a layered relationship as are the service models. A node that is part of a model in one layer corresponds to a model in the next-lower layer. The invention generates optimized mappings of service nodes that are described in user-selected service models to server nodes that are described in user-selected server models, as a function of the associated sets of demand and capacity attributes.

Abstract: Techniques are provided for automatically deploying software packages. Management agents represent these packages, a logical tree represents the deployed structure, and a node of the tree represents a management agent. A node that does not have any child node is referred to as a leaf node. A recursive process associated with at least one repository generates the structure. The repositories include information for configuring the nodes and thus control the deployment process. During deployment, a non-leaf node, referred to as an initiator node, uses information received from a corresponding repository to generate its child nodes. A child node, if being an initiator node, recursively generates its child nodes until the recursive process stops as there is no additional child node to be generated. Further, node identifiers are automatically established and assigned to respective nodes.

Abstract: Method and apparatus for optimizing allocation of computer resources between server and service models. A server model is established in response to user input data. The server model includes one or more server nodes, and each server node has an associated set of capacity attributes. In addition, a service model is established that includes one or more service nodes. Each service node has an associated set of demand attributes. In response to a user selection, one of a plurality of optimization methods and one of a plurality of optimization policies, as embodied in objective functions, are selected for mapping the server nodes and service nodes. An optimized mapping is then generated of the server nodes in the server model to the service nodes in the service model using the selected optimization method, along with the demand and capacity attributes.

Abstract: Method and apparatus for representing capacities and demands in a layered computing environment using normalized values for identifying optimal allocations of computing resources. A plurality of server models are established, with each server model including one or more server nodes and each server node having an associated set of capacity attributes. Similarly, a plurality of service models are established, each service model including one or more service nodes and each service node having an associated set of demand attributes. The server models are defined with a layered relationship as are the service models. A node that is part of a model in one layer corresponds to a model in the next-lower layer. The invention normalizes the demand and capacity attributes of the server nodes and service nodes in the different model layer in order to generate optimized mappings of service nodes to server nodes.

Abstract: Method and framework for identifying optimal allocations of computing resources in a complex, distributed data processing environment. A plurality of server models are established, with each server model including one or more server nodes and each server node having an associated set of capacity attributes. Similarly, a plurality of service models are established, each service model including one or more service nodes and each service node having an associated set of demand attributes. The server models are defined with a layered relationship as are the service models. A node that is part of a model in one layer corresponds to a model in the next-lower layer. The invention generates optimized mappings of service nodes that are described in user-selected service models to server nodes that are described in user-selected server models, as a function of the associated sets of demand and capacity attributes.