27869 results about "Workload" patented technology

In embodiments of the present invention improved capabilities are described for a virtualization environment adapted for development and deployment of at least one software workload, the virtualization environment having a metamodel framework that allows the association of a policy to the software workload upon development of the workload that is applied upon deployment of the software workload. This allows a developer to define a security zone and to apply at least one type of security policy with respect to the security zone including the type of security zone policy in the metamodel framework such that the type of security zone policy can be associated with the software workload upon development of the software workload, and if the type of security zone policy is associated with the software workload, automatically applying the security policy to the software workload when the software workload is deployed within the security zone.

The bypass network is designed to provide fast access and high quality streaming media services anywhere anytime. There are five major components including Peering Gateway, Content Locator, Edge Server, Gateway and Client. The whole bypass network is divided into number of self-managed sub-networks, which are referred as local networks in this document. Each local network contains Edge Servers, gateways, and a Content Locator. The Edge Servers serve as cache storage and streaming servers for the local network. The gateways provide a connection point for the client computers. Each local network is managed by a Content Locator. The Content Locator handles all client requests by communicating with the Peering Gateway and actual web sites, and makes the content available on local Edge Servers. The Content Locator also balances the load on each Edge Server by monitoring the workload on them. One embodiment is designed for home users whose home machine does not move around frequently. A second embodiment is designed for business users who travel around very often where the laptops would self-configure as a client of the network.

Systems and methods for discovery and classification of denial of service attacks in a distributed computing system may employ local agents on nodes thereof to detect resource-related events. An information later agent may determine if events indicate attacks, perform clustering analysis to determine if they represent known or unknown attack patterns, classify the attacks, and initiate appropriate responses to prevent and / or mitigate the attack, including sending warnings and / or modifying resource pool(s). The information layer agent may consult a knowledge base comprising information associated with known attack patterns, including state-action mappings. An attack tree model and an overlay network (over which detection and / or response messages may be sent) may be constructed for the distributed system. They may be dynamically modified in response to changes in system configuration, state, and / or workload. Reinforcement learning may be applied to the tuning of attack detection and classification techniques and to the identification of appropriate responses.

According to one system of the invention, the system provides a cloud-computing service from a cloud-computing environment comprising a plurality of cloud-computing resources. The system may comprise: a management module configured to manage a cloud-computing resource of the plurality of cloud-computing resources as a cloud-computing service, wherein the cloud-computing service performs a computer workload; an adapter configured to connect to the cloud-computing resource to the system and translate a management instruction received from the management module into a proprietary cloud application program interface call for the cloud-computing resource; a cloud service bus configured to route the management instruction from the management module to the adapter; a consumption module configured to allow a user to subscribe the cloud-computing service; a planning module configured to plan the cloud-computing service; and a build module configured to build the cloud-computing service from the cloud-computing resource and publish the cloud-computing service to the consumption module.

A data management and archive method and apparatus, such as for implementation in an automated system to monitor and manage status, performance and configuration data for a plurality of networked storage components. Analysis and cross-correlation of data related to the plurality of storage components can be done individually, collectively and / or comparatively. A collection manager component of a workload analyzer is implemented to start and stop data collection in the context of a system comprising at least one storage component (or at least two networked storage components). The collection manager includes a command and control module that coordinates requests of data from at least one collection agent configured on at least one host connected to the storage component(s).

A computer system may be configured to dynamically select a memory virtualization and corresponding virtual-to-physical address translation technique during execution of an application and to dynamically employ the selected technique in place of a current technique without re-initializing the application. The computer system may be configured to determine that a current address translation technique incurs a high overhead for the application's current workload and may be configured to select a different technique dependent on various performance criteria and / or a user policy. Dynamically employing the selected technique may include reorganizing a memory, reorganizing a translation table, allocating a different block of memory to the application, changing a page or segment size, or moving to or from a page-based, segment-based, or function-based address translation technique. A selected translation technique may be dynamically employed for the application independent of a translation technique employed for a different application.

A computer system for conserving operating power includes a number of computer hardware processor cores that differ amongst themselves in at least in their respective operating power requirements and processing capabilities. A monitor gathers performance metric information from each of the computer hardware processor cores that is specific to a particular run of application software then executing. A workload transfer mechanism transfers the executing application software to a second computer hardware processor core in a search for reduced operating power. A transfer delay mechanism is connected to delay a subsequent transfer of the executing application software if the system operating power may be conserved by such delay.

An apparatus and method for automatically load balancing one or more workload groups to a set of available physical resources of a data storage system, and generating a layout planning recommendation of the set of available physical resources that supports the one or more workload groups based on the load balancing.

Present invention is a system of blood glucose monitoring and intensive insulin therapy in a ICU for strict maintenance of normoglycemia which reduces intensive care and hospital mortality and morbidity of critically ill adult patients. The findings of present study also reveal factors determining insulin doses needed to maintain normoglycemia as well as the impact of insulin dose versus blood glucose level on the observed outcome benefits have been established. The invention provides a control system that adapts the flow of the insulin infusion based on insulin requirement calculated by blood glucose levels and clinical parameters such as history of diabetes, Body Mass Index, blood glucose level on admission, reason of ICU admission, time in the ICU, type and severity of illness, caloric intake, obesity, drugs affecting insulin sensitivity). This automated insulin monitoring systems significantly reduces the workload and human resource management problems for intensive insulin therapy in patients in the ICU.

An electronic mail system with a methodology providing distributed message storage and processing is described. In particular, this methodology breaks up how the individual components of message data are stored. Message data itself is broken up into two parts: a metadata (mutable) portion, and an immutable portion. The metadata portion represents that part of the message data that may change over time. This includes message status flags (e.g., the IMAP “message deleted” flag) and the message's position within a particular message folder, among other information. The immutable portion, which comprises the bulk of electronic mail data (namely, the message itself), once stored is never edited. Immutable data is written f+1 times on as many unique servers, to tolerate f number of server failures using Lampson's stable storage algorithm. The metadata portion is stored 2f+1 times on as many unique servers to tolerate f number of server failures using quorum voting. Once the message has been stored once, instead of being copied, its location is passed around by reference. The system utilizes a two-tier architecture. One tier consists of servers which store message metadata and immutable data, the Data Servers, and servers that operating upon those data, the Access Servers. Message store integrity is maintained in the event of server failure and as the set of Data Servers changes. In the latter case, I / O and storage workloads are dynamically redistributed across Data Servers in an efficient way.

A system and method for automatic workload characterization are provided. Transactions performed in a computer system may be logged. The log of transactions comprises a timestamp for each transaction. Resource usage in the computer system may be logged. The log of resource usage comprises one or more periods of time during which each of a plurality of resources is used, and the log of resource usage comprises a plurality of system performance metrics which reflect resource consumption by one or more processes that performed the transactions. The timestamps in the log of transactions may be compared to the periods of time in the log of resource usage. It may be determined which transactions used which resources as a result of the comparing the timestamps in the log of transactions to the periods of time in the log of resource usage. One or more workloads may be determined using the determining which transactions used which resources. Heuristics may be used to group processes into workloads.

An intelligent storage controller operating in conjunction with a computer running an application that uses the data managed by the intelligent storage controller, and requires data transformation operations to be performed on the data. The intelligent storage controller is adapted to directly perform the data transformation operations on the data controlled by the controller, under the direction of the computer running the application, thereby offloading this processing entirely to the intelligent storage controller. The intelligent storage controller may also provide an application programming interface for the computer running the application to use in directing commands to the intelligent storage controller. To accommodate varying workloads on the intelligent storage controller, data transformation tasks may be load balanced between the intelligent storage controller, the computer running the application, and / or other hosts.

In embodiments of the present invention improved capabilities are described for a virtualization environment adapted for development and deployment of at least one software workload, the virtualization environment having a metamodel framework that allows the association of a policy to the software workload upon development of the workload that is applied upon deployment of the software workload.

The present invention provides a solution (e.g., rules, techniques, etc.) for enabling the dynamic provisioning (e.g., movement) of Cloud-based jobs and resources. Such provisioning may be within a Cloud infrastructure, from Cloud to Cloud, from non-Cloud to Cloud, and from Cloud to non-Cloud. Each movement scenario is assigned a specific technique based on rules, profiles, SLA and / or other such criteria and agreements. Such dynamic adjustments may be especially advantageous in order to balance real-time workload to avoid over-provisioning, to manage Cloud performance, to attain a more efficient or cost-effective execution environment, to off-load a Cloud or specific Cloud resources for maintenance / service, and the like.

A method for storage and manipulation of storage system metrics incorporates a self-describing format wherein each data file includes a header block that contains the description and order of the periodic data. The header block is followed by a data block in which the data items are presented in the order that they appear in the data description block for that category. Two types of data are managed, including Base Metrics and Derived Metrics. Base Metrics are metrics that appear in the data file sent by an agent. Derived Metrics are computed based on a set of functions that derive new metrics from the base metrics as well as from previously defined derived metrics. A subset of the data block or file describes the configuration of the storage system at the time that the data file was created. Thus the data file contains a header section that in addition to describing the metrics also describes the configuration. A performance view component a user interface that facilitates access to the archives, and data manipulation effecting enhanced performance analysis, workload characterization and capacity planning. The performance view component facilitates generation of factory and user defined views of monitored metrics / parameters. Metrics from a storage system can be correlated using the performance view features, and parameters across machines can be correlated as well. System configuration(s) can be viewed and changed via the performance view user interface.

An on-demand manager provides an improved distributed data processing system for facilitating dynamic allocation of computing resources among multiple domains based on a current workload and service level agreements. Based on a service level agreement, the on-demand manager monitors and predicts the load on the system. If the current or predicted load cannot be handled with the current system configuration, the on-demand manager determines additional resources needed to handle the workload. If the service level agreement violations cannot be handled by reconfiguring resources at a domain, the on-demand manager sends a resource request to other domains. These other domains analyze their own commitments and may accept the resource request, reject the request, or counter-propose with an offer of resources and a corresponding service level agreement. Once the requesting domain has acquired resources, workload load balancers are reconfigured to allocate some of the workload from the requesting site to the acquired remote resources.

Systems, methods, and apparatus for managing resources assigned to an application or service. A resource manager maintains a set of workload classes and classifies workloads using workload signatures. In specific embodiments, the resource manager minimizes or reduces resource management costs by identifying a relatively small set of workload classes during a learning phase, determining preferred resource allocations for each workload class, and then during a monitoring phase, classifying workloads and allocating resources based on the preferred resource allocation for the classified workload. In some embodiments, interference is accounted for by estimating and using an “interference index”.

A system and methods for the migration of complex computer applications and the workloads comprising them between physical, virtual, and cloud servers that span a hybrid cloud environment comprising private local and remote customer data centers and public cloud data centers, without modification to the applications, their operational environments, or user access procedures. A virtual network manager securely extends the subnets and VLANS within the customer's various data center across the distributed, hybrid environment using overlay networks implemented with virtual network appliances at nodes of the overlay network. A server migrater migrates individual workloads of servers used by the complex application from one pool of server resources to another. A migration manager application provides a control interface, and also maps and manages the resources of the complex application, the hybrid environment, and the virtual network spanning the hybrid cloud environment.

Method and calculations determine an individual's, or several individuals' simultaneous rates of oxygen consumption, maximum rates of oxygen consumption, heart rates, calorie expenditures, and METS (multiples of metabolic resting rate) in order to determine the amounts of work that is performed by the individual's body. A heart monitor measures the heart rate, and an accelerometer measures the acceleration of the body along one or more axes. An altimeter measures change in altitude, a glucose monitor measures glucose in tissue and blood, and thermometers, thermistors, or thermocouples measure body temperature. Data including body fat and blood pressure measurements are stored locally and transferred to a processor for calculation of the rate of physiological energy expenditure. Certain cardiovascular parameters are mathematically determined. Comparison of each axis response to the individual's moment can be used to identify the type of activity performed and the information may be used to accurately calculate total energy expenditure for each physical activity. Energy expenditure may be calculated by assigning a separate proportionality coefficient to each axis and tabulating the resulting filtered dynamic acceleration over time, or by comparison with previously predetermined expenditures for each activity type. A comparison of total energy expenditure from the current activity is compared with expenditure from a previous activity, or with a baseline expenditure rate to assess the level of current expenditure. A measure of the individual's cardio-vascular health may be obtained by monitoring the heart's responses to various types of activity and to total energy expended.

A method for scaling resources according to workload among virtual servers running on a mainframe computer is provided. The invention comprises monitoring the number of service requests received by a cluster of virtual servers and determining if the service requests exceed a specified service limit for the servers. If the number of service requests exceeds the specified service limit, a new virtual server is automatically deployed by a software solution. This additional virtual server performs identical services as the other virtual servers in the cluster. This process is repeated until there are a sufficient number of servers to handle the workload. Service requests are then allocated among the cluster of virtual servers, until the number of requests falls below a certain threshold, at which point the extra servers are automatically deactivated.

A method and system for determining work ticket priority is provided. The method includes enabling a work ticket for a work assignment associated with an entity. The work ticket is assigned an initial priority value. Relevant data from multiple sources is associated with the work ticket and an updated priority value is requested. In response, multiple priority scores for the work ticket with respect to additional work tickets are published to an enterprise service bus (ESB) and an aggregate score for work ticket is calculated from the multiple priority scores.

A system for workload placement among data centers includes a plurality of grid resource allocation managers (GRAMs), wherein the GRAMs are configured to obtain information from the data centers. The system also includes an information service configured to receive information from the plurality of GRAMs and a broker configured to receive an application request and to determine resource requirements from the application request, wherein the broker is configured to determine which of the data centers contains adequate resources to perform the requested application. The system further includes a co-allocator configured to receive information pertaining to the data centers having the adequate resources, wherein the co-allocator is further configured to select one of the data centers to perform the requested application based upon energy efficiency characteristics of the data centers.

In a method of allocating workload among servers based upon historical data, a requested workload profile is received and is compared with a plurality of historical workload profiles. A historical workload profile that is within a predefined range of the requested workload profile and that corresponds to a substantially minimized resource usage for power and cooling is selected. In addition, workload among the servers is allocated according to the selected historical workload profile to thereby substantially minimize resource usage for power and cooling.

A system and method for utilizing the locale-independence of virtual machine technology is employed to facilitate load imbalancing in support of power management. Arbitrary stateless or stateful workloads are migrated as virtual machines from a larger number of resources to a smaller number of resources so as to eliminate workload from some resources. These latter resources can then be placed into a lower-power state to reduce power consumption. When workload rises again, some or all of the lower-powered resources can be powered-on, and workload can be reapplied to them.

A system and method for allocating resources in a cloud environment includes providing an abstraction layer between a cloud environment and one or more data centers by generating a virtual hypervisor as an application programming interface. Responsive to a workload request by the one or more data centers, resources are partitioned and virtual machines are instantiated in the one or more data centers using the virtual hypervisor such that non-functional requirements of the workload are addressed at the abstraction level using the virtual hypervisor.

The present invention relates to a method for workforce scheduling in which workload and workload types vary during scheduling period. The method acquires agent and skill requirements for all periods and contact types; acquires the contact center information including agent skill groups, agent work groups, tour and shift scheduling rules, agent availability, objective criterion to be optimized and its parameters; develops a Mixed Integer Linear Programming (MILP) model for the scheduling environment; applied an optimization algorithm that uses the Branch and Bound algorithm with a Rounding Algorithm to improve performance; and locates a globally optimal or near optimal workforce schedule in total cost or paid time or agent satisfaction. Detailed schedules may be developed by assigning daily shifts to work patterns, and breaks scheduled to daily shifts.

A computer-implemented method is disclosed. The method includes collecting cache-efficiency-indicator values of an at least one cache fragment during operation of a database system over a period of time. Providing approximation-function-parameter values for the collected, cache-efficiency-indicator values, an approximation function representing a relation between a cache-efficiency-indicator and the size of a respective cache fragment. The method continues by providing a set of workload windows based on the approximation-function-parameter values. Next, providing a workload-window information for the set of workload windows, the workload-window information including at least one approximation-function-parameter value representing each determined workload window. The method further includes storing the workload-window information for a comparison based on current, cache-efficiency-indicator values and the workload-window information.

A method of analyzing data based on the physiological orientation of a driver is provided. Data is descriptive of a driver's gaze-direction is processing and criteria defining a location of driver interest is determined. Based on the determined criteria, gaze-direction instances are classified as either on-location or off-location. The classified instances can then be used for further analysis, generally relating to times of elevated driver workload and not driver drowsiness. The classified instances are transformed into one of two binary values (e.g., 1 and 0) representative of whether the respective classified instance is on or off location. The uses of a binary value makes processing and analysis of the data faster and more efficient. Furthermore, classification of at least some of the off-location gaze direction instances can be inferred from the failure to meet the determined criteria for being classified as an on-location driver gaze direction instance.

A method comprises receiving into a planning tool a representative workload for a consumer. The method further comprises receiving into the planning tool quality of service desires of the consumer which define permitted degraded performance. In certain embodiments, the permitted degraded performance is time-limited wherein demands of the representative workload may exceed a pre-defined utilization constraint for at least one resource servicing the demands for no more than a pre-defined amount of contiguous time. The planning tool determines an allocation of demand of the consumer for each of a plurality of different classes of service (COSs). In certain embodiments, a first COS provides guaranteed resource access for servicing demand allocated thereto, and a second COS provides non-guaranteed resource access for servicing demand allocated thereto. In certain embodiments, the allocation of demand to the different COSs may be determined for both a normal mode and a failure mode of operation.