| Patent application number | Description | Published |
|---|
| 20090019222 | METHOD AND SYSTEM FOR PLACEMENT OF LOGICAL DATA STORES TO MINIMIZE REQUEST RESPONSE TIME - Logical data stores are placed on storages to minimize store request time. The stores are sorted. A store counter and a storage counter are each set to one. (A), (B), and (C) are repeated until the storage counter exceeds the number of storages within the array. (A) is setting a load for the storage specified by the storage counter to zero. (B) is performing (i), (ii), and (iii) while the load for the storage specified by the storage counter is less an average determined load over all the storages. (i) is allocating the store specified by the store counter to the storage specified by the storage counter; and, (ii) is incrementing the load for this storage by this storage's request arrival rate multiplied by an expected service time for the requests of this store. (iii) is incrementing the store counter by one. (C) is incrementing the storage counter by one. | 01-15-2009 |
| 20090150456 | METHODS, SYSTEMS, AND COMPUTER PROGRAM PRODUCTS FOR DISASTER RECOVERY PLANNING - Formulating an integrated disaster recovery (DR) plan based upon a plurality of DR requirements for an application by receiving a first set of inputs identifying one or more entity types for which the plan is to be formulated, such as an enterprise, one or more sites of the enterprise, the application, or a particular data type for the application. At least one data container representing a subset of data for an application is identified. A second set of inputs is received identifying at least one disaster type for which the plan is to be formulated. A third set of inputs is received identifying a DR requirement for the application as a category of DR Quality of Service (QoS) class to be applied to the disaster type. A composition model is generated specifying one or more respective DR QoS parameters as a function of a corresponding set of one or more QoS parameters representative of a replication technology solution. The replication technology solution encompasses a plurality of storage stack levels. A solution template library is generated for mapping the application to each of a plurality of candidate replication technology solutions. The template library is used to select a DR plan in the form of a replication technology solution for the application. | 06-11-2009 |
| 20090150712 | METHODS, SYSTEMS, AND COMPUTER PROGRAM PRODUCTS FOR DISASTER RECOVERY PLANNING - Formulating an integrated disaster recovery (DR) plan based upon a plurality of DR requirements for an application by receiving a first set of inputs identifying one or more entity types for which the plan is to be formulated, such as an enterprise, one or more sites of the enterprise, the application, or a particular data type for the application. At least one data container representing a subset of data for an application is identified. A second set of inputs is received identifying at least one disaster type for which the plan is to be formulated. A third set of inputs is received identifying a DR requirement for the application as a category of DR Quality of Service (QoS) class to be applied to the disaster type. A composition model is generated specifying one or more respective DR QoS parameters as a function of a corresponding set of one or more QoS parameters representative of a replication technology solution. The replication technology solution encompasses a plurality of storage stack levels. A solution template library is generated for mapping the application to each of a plurality of candidate replication technology solutions. The template library is used to select a DR plan in the form of a replication technology solution for the application. | 06-11-2009 |
| 20090182784 | RECOVERY POINT IDENTIFICATION IN CDP ENVIRONMENTS - The embodiments of the invention provide a method of identifying a recovery point in a continuous data protection (CDP) log. More specifically, the method begins by detecting corrupted data in the CDP log and identifying the nature of corruption. Next, the nature of corruption is mapped to applications to identify components that may have caused the corrupted data. The method then finds a time instance of uncorrupted data in the components. Specifically, this can include searching CDP log entries in an order independent of log event age. Alternatively, the process of finding the time instance can include creating a data image of a first copy of uncorrupted data and sequentially apply entries of the CDP log until the corrupted data is reached. | 07-16-2009 |
| 20090307166 | METHOD AND SYSTEM FOR AUTOMATED INTEGRATED SERVER-NETWORK-STORAGE DISASTER RECOVERY PLANNING - An automated disaster recovery (DR) planning system for a computing environment is provided. A discovery module discovers servers, networks, and storage devices in a computing environment. An expert knowledge base module captures best practices in planning, and capabilities, interoperability, limitation and boundary values for different DR technologies. A match-making module determines multiple DR plans as combinations of one or more replication technologies that can be used to satisfy DR requirements. And, an optimizer configured for assessing a feasible DR plan from said multiple DR plans, to deploy for DR planning of a primary computing environment. | 12-10-2009 |
| 20100005173 | Method, system and computer program product for server selection, application placement and consolidation - A plurality of application profiles are obtained, for a plurality of applications. Each of the profiles specifies a list of resources, and requirements for each of the resources, associated with a corresponding one of the applications. Specification of a plurality of constraints associated with the applications is facilitated, as is obtaining a plurality of cost models associated with at least two different kinds of servers on which the applications are to run. A recommended server configuration is generated for running the applications, by formulating and solving a bin packing problem. Each of the at least two different kinds of servers is treated as a bin of a different size, based on its capacity, and has an acquisition cost associated therewith. The size is substantially equal to a corresponding one of the resource requirement as given by a corresponding one of the application profiles. Each of the applications is treated as an item, with an associated size, to be packed into the bins. The bin packing problem develops the recommended server configuration based on reducing a total acquisition cost while satisfying the constraints and the sizes of the applications. | 01-07-2010 |
| 20100011102 | METHOD FOR PLACING COMPOSITE APPLICATIONS IN A FEDERATED ENVIRONMENT - Techniques for placing at least one composite application in a federated environment are provided. The techniques include analyzing a composite application to be deployed in a federated environment, obtaining one or more application artifacts, analyzing feasibility of placing one or more application components at one or more clusters in the federated environment without knowledge of resource availability at each of the one or more clusters, and generating a mapping of the one or more application components to the one or more clusters such that an application requirement is met, wherein the one or more application artifacts are distributed across a federated environment. | 01-14-2010 |
| 20100106538 | DETERMINING DISASTER RECOVERY SERVICE LEVEL AGREEMENTS FOR DATA COMPONENTS OF AN APPLICATION - Techniques for determining one or more disaster recovery (DR) service level agreements (SLAs) for each of one or more components of an application are provided. The techniques include identifying one or more components of an application, capturing one or more intra-application data dependencies between the one or more components, and mapping each of the one or more components to a DR profile to determine one or more DR SLAs for each of the one or more components of an application. | 04-29-2010 |
| 20100180275 | TECHNIQUES FOR PLACING APPLICATIONS IN HETEROGENEOUS VIRTUALIZED SYSTEMS WHILE MINIMIZING POWER AND MIGRATION COST - N applications are placed on M virtualized servers having power management capability. A time horizon is divided into a plurality of time windows, and, for each given one of the windows, a placement of the N applications is computed, taking into account power cost, migration cost, and performance benefit. The migration cost refers to cost to migrate from a first virtualized server to a second virtualized server for the given one of the windows. The N applications are placed onto the M virtualized servers, for each of the plurality of time windows, in accordance with the placement computed in the computing step for each of the windows. In an alternative aspect, power cost and performance benefit, but not migration cost, are taken into account; there are a plurality of virtual machines; and the computing step includes, for each of the windows, determining a target utilization for each of the servers based on a power model for each given one of the servers; picking a given one of the servers with a least power increase per unit increase in capacity, until capacity has been allocated to fit all the virtual machines; and employing a first fit decreasing bin packing technique to compute placement of the applications on the virtualized servers. | 07-15-2010 |
| 20100332882 | MINIMIZING STORAGE POWER CONSUMPTION - Techniques for minimizing storage power consumption are provided. The techniques include generating one or more physical storage volumes and one virtual storage volume for each physical storage volume, creating a mapping from virtual storage volumes to physical storage volumes, determining input/output (I/O) access behavior of one or more applications using statistical analysis, and re-mapping the virtual to physical volume mapping based on the determined I/O access behavior of the one or more applications to minimize storage power consumption while meeting a required performance. | 12-30-2010 |
| 20110010222 | POINT-IN-TIME BASED ENERGY SAVING RECOMMENDATIONS - Energy saving efforts should not compromise data center performance. An energy management application can determine usage patterns in historical energy usage data based on statistical analysis and energy models. Energy savings recommendations can be generated for future points-in-time based on the usage patterns. Business constraints can be applied to the energy savings recommendations to ensure that the energy savings recommendations meet performance requirements. | 01-13-2011 |
| 20110016339 | Dynamic Selection of Server States - Techniques for dynamically selecting a server state for one or more servers in a cluster of servers are provided. The techniques include tracking each active and sleep state of each server in a cluster of servers, and selecting a server state for one or more servers in the cluster of servers to meet one or more workload level requirements of the cluster of servers, wherein selecting a server state for one or more servers comprises scheduling a transition between one or more active and sleep states for the one or more servers, wherein scheduling the transition comprises using power consumption information for each state and transition time information for each transition. | 01-20-2011 |
| 20110161470 | Method, System and Computer Program Product for Server Selection, Application Placement and Consolidation Planning of Information Technology Systems - A plurality of application profiles are obtained, for a plurality of applications. Each of the profiles specifies a list of resources, and requirements for each of the resources, associated with a corresponding one of the applications. Specification of a plurality of constraints associated with the applications is facilitated, as is obtaining a plurality of cost models associated with at least two different kinds of servers on which the applications are to run. A recommended server configuration is generated for running the applications, by formulating and solving a bin packing problem. Each of the at least two different kinds of servers is treated as a bin of a different size, based on its capacity, and has an acquisition cost associated therewith. The size is substantially equal to a corresponding one of the resource requirement as given by a corresponding one of the application profiles. Each of the applications is treated as an item, with an associated size, to be packed into the bins. The bin packing problem develops the recommended server configuration based on reducing a total acquisition cost while satisfying the constraints and the sizes of the applications. | 06-30-2011 |
