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Malgorzata Steinder

Malgorzata Steinder, Hawthorne, NY US

Patent application numberDescriptionPublished
20110072138VIRTUAL MACHINE DEMAND ESTIMATION - A method for use in a system in which computational entities are distributed across physical computing resources to place the entities on the resources includes estimating actual resource demand for each entity on each resource based on application resource usage data collected from a data source external from the entity, computing a best allocation of the resources to the entities from the estimated actual resource demand for each entity and distributing the resources to the entities in accordance with the computed best allocation.03-24-2011

Malgorzata Steinder, Fort Lee, NJ US

Patent application numberDescriptionPublished
20080270199METHODS AND APPARATUS FOR MANAGEMENT OF HETEROGENEOUS WORKLOADS - Systems and methods for managing a system of heterogeneous workloads are provided. Work that enters the system is separated into a plurality of heterogeneous workloads. A plurality of high-level quality of service goals is gathered. At least one of the plurality of high-level quality of service goals corresponds to each of the plurality of heterogeneous workloads. A plurality of control functions are determined that are provided by virtualizations on one or more containers in which one or more of the plurality of heterogeneous workloads run. An expected utility of a plurality of settings of at least one of the plurality of control functions is determined in response to the plurality of high-level quality of service goals. At least one of the plurality of control functions is exercised in response to the expected utility to effect changes in the behavior of the system.10-30-2008
20100042721Dynamic application placement with allocation restrictions, vertical stacking and even load distribution - A solution to a variant of a class constrained multiple knapsack problem. Previous solutions require that memory demand of every application be identical and do not consider minimizing placement changes. Previous techniques do not consider optimizing placement to improve load balancing as is described subsequently. Thus, the present invention provides systems, methods and apparatus, encapsulated in software, to provide the dynamic placement of application instances on a heterogeneous cluster of server machines. It depends on the existence of a visible and controllable platform, systems management and other business services that signal events and accept commands. It provides dynamically placing applications on servers such as to maximize a total amount of satisfied application demands, minimize a number of placement changes from a current placement, and minimize imbalance of load distribution of said applications on said at least one server.02-18-2010
20100223379COORDINATING SERVICE PERFORMANCE AND APPLICATION PLACEMENT MANAGEMENT - Coordinating tasks of performance management and application placement management in a dynamic fashion by: estimating capacity needs for various service classes of service requests; computing desired capacities of at least one application for said service requests; deciding whether the desired capacities are satisfied by a current application placement; making no change to current application placement if the desired capacities are satisfied; determining a new application placement based on the desired capacities and a projected load if the desired capacities are not satisfied; computing corresponding capacity constraints for all pairs of service classes and servers; and computing an optimal allocation of capacities among the service classes so as to optimize a quality of service.09-02-2010
20110004735METHOD AND APPARATUS FOR TWO-PHASE STORAGE-AWARE PLACEMENT OF VIRTUAL MACHINES - Techniques for placement of a virtual machine in a computing system. A first request is sent from a pool management subsystem to a placement subsystem. The first request includes specification of available storage capacities of storage systems in a computer network. The placement subsystem automatically determines a target storage system based, at least in part, on the available storage capacities. An identification of the target storage system is received at the pool management subsystem. At least one disk image of the virtual machine is written to the target storage system. Then, a second request is sent to the placement subsystem. The placement subsystem automatically determines a target computer. The latter determination is based, at least in part, on connectivity between the target computer and the target storage system. The virtual machine is installed at the target computer. The techniques facilitate live migration of virtual machines placed thereby.01-06-2011

Patent applications by Malgorzata Steinder, Fort Lee, NJ US

Malgorzata Steinder, Leonia, NJ US

Patent application numberDescriptionPublished
20080216088Coordinating service performance and application placement management - Apparatus, systems and methods for service and/or business for coordinating tasks of performance management and application placement management in a dynamic fashion. An example process is dynamic in the face of fluctuations in the request load to the distributed computer system and the periodic adjustments to the placement of applications onto servers in said distributed computer system. There are two opposite functional flows in said process: a demand estimation function and a capacity adjustment function. The coordination system involves two subsystems: a demand estimator and a capacity adjuster, along with appropriate interfaces to of the performance manager and the application placement manager. This results in application placement process reacting quicker to demand fluctuations, performance guarantees are better met by rearranging the resources to be allocated to the various classes of service, and the management system works in an unsupervised mode, thus reducing manual administration costs and human errors.09-04-2008
20080282267Dynamic Application Instance Placement in Data Center Environments - Techniques are disclosed for determining placements of application instances on computing resources in a computing system such that the application instances can be executed thereon. By way of example, a method for determining an application instance placement in a set of machines under one or more resource constraints includes the following steps. An estimate is computed of a value of the first metric that can be achieved by a current application instance placement and a current application load distribution. A new application instance placement and a new application load distribution are determined, wherein the new application instance placement and the new load distribution optimize the first metric.11-13-2008
20090157855DECENTRALIZED APPLICATION PLACEMENT FOR WEB APPLICATION MIDDLEWARE - A decentralized process to ensure the dynamic placement of applications on servers under two types of simultaneous resource requirements, those that are dependent on the loads placed on the applications and those that are independent. The demand (load) for applications changes over time and the goal is to satisfy all the demand while changing the solution (assignment of applications to servers) as little as possible.06-18-2009
20090254660SYSTEMS AND METHODS FOR COORDINATED MANAGEMENT OF POWER USAGE AND RUNTIME PERFORMANCE IN PERFORMANCE-MANAGED COMPUTING ENVIRONMENTS - Systems and methods are provided for dynamically controlling application placement and server resource allocation in a distributed system wherein a performance manager and power manager collaborate during run-time execution of data processing tasks to coordinate management and control of workload placement and server usage and dynamically determine a tradeoff between performance level and power usage that meets power and performance objectives10-08-2009
20090254909Methods and Apparatus for Power-aware Workload Allocation in Performance-managed Computing Environments - An exemplary method of allocating a workload among a set of computing devices includes obtaining at least one efficiency model for each device. The method also includes, for each of a set of allocations of the workload among the devices, determining, for each device, the power consumption for the device to perform the workload allocated to the device by the allocation, the power consumption being determined based on the at least one efficiency model for each device; and determining a total power consumption of the devices. The method also includes selecting an allocation of the workload among the devices based at least in part on the total power consumption of the devices for each allocation. The method also includes implementing the selected allocation of the workload among the devices.10-08-2009

Patent applications by Malgorzata Steinder, Leonia, NJ US