Abstract: A method, computer system, and a computer program product are provided for providing multi-cloud collaboration. In one embodiment, the technique comprises obtaining registration information for a plurality of participants. The participants are devices located on a plurality of computer networks. A measurement query request is received from a query requester. The query requester is one of the plurality of participants. Contributions measurements is also received from a subset of the plurality of participants and measurement data is then updated based on the contributions received from the subset of participants. Measurement data is the provided in response to said measurement query. The amount of data provided depends on a set of policies regarding measurement contributions made by the query requester.

Abstract: Embodiments may include novel techniques to communicate user preferences to the FaaS provider so as to provide full applicability of FaaS for business critical applications and to provide full realization of the FaaS model flexibility. For example, in an embodiment, a method may be implemented in a computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, and the method may comprise receiving a request for processing of a computing task and associated data indicating a context of an overall process flow for the computing task, wherein the request for processing is a function invocation for a FaaS computing system, evaluating the data indicating the context and scheduling computing resources for performing the computing task based on the data indicating the context, and performing the computing task using the scheduled computing resources.

Abstract: Embodiments may include novel techniques to communicate user preferences to the FaaS provider so as to provide full applicability of FaaS for business critical applications and to provide full realization of the FaaS model flexibility. For example, in an embodiment, a method may be implemented in a computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, and the method may comprise receiving a request for processing of a computing task and associated data indicating a context of an overall process flow for the computing task, wherein the request for processing is a function invocation for a FaaS computing system, evaluating the data indicating the context and scheduling computing resources for performing the computing task based on the data indicating the context, and performing the computing task using the scheduled computing resources.

Abstract: A heterogeneous resource reservation (HRR) manager configured to classify historical application requests from a past time interval for a first workload to generate labeled historical application requests. The HRR manager further configured to generate a forecast based on the labeled historical application requests and for predicting future application requests for the first workload for a future time interval and calculate a joint plan based on the forecast. The joint plan including a set of virtual resources, a set of billing contracts, and a set of load balancer weights. The HRR manager further configured to implement the joint plan for a distributed computing workload during the future time interval.

Abstract: This invention relates to generating benchmarks without the need for executing the application on a specific benchmarking platform or by testing the application against known inputs and outputs. Instead, the system, in an embodiment, allows for source code comparisons to known systems to predict performance. The benchmarking can be done for varying deployment platforms and various usage patterns. The source code comparison process allows for fast performance prediction by using a distance vector.

Abstract: A heterogeneous resource reservation (HRR) manager configured to classify historical application requests from a past time interval for a first workload to generate labeled historical application requests. The HRR manager further configured to generate a forecast based on the labeled historical application requests and for predicting future application requests for the first workload for a future time interval and calculate a joint plan based on the forecast. The joint plan including a set of virtual resources, a set of billing contracts, and a set of load balancer weights. The HRR manager further configured to implement the joint plan for a distributed computing workload during the future time interval.

Abstract: An example method includes receiving a nominal equivalent resource usage data, an infrastructure usage data, an effective production capacity, a demand elasticity curve, and workload scheduling constraints across a plurality of accounts. The method includes calculating an equivalent resource utilization based on the nominal equivalent resource usage data, the infrastructure usage data, and the effective production capacity. The method includes calculating a potential value increase for a service based on the workload scheduling constraints, the nominal equivalent resource usage data, the effective production capacity, and the demand elasticity curve. The method includes calculating a value increase scheme for the service based on the potential value increase and sending the value increase scheme to a user workload device.

Abstract: An example method includes receiving a nominal equivalent resource usage data, an infrastructure usage data, an effective production capacity, a demand elasticity curve, and workload scheduling constraints across a plurality of accounts. The method includes calculating an equivalent resource utilization based on the nominal equivalent resource usage data, the infrastructure usage data, and the effective production capacity. The method includes calculating a potential value increase for a service based on the workload scheduling constraints, the nominal equivalent resource usage data, the effective production capacity, and the demand elasticity curve. The method includes calculating a value increase scheme for the service based on the potential value increase and sending the value increase scheme to a user workload device.

Abstract: This invention relates to generating benchmarks without the need for executing the application on a specific benchmarking platform or by testing the application against known inputs and outputs. Instead, the system, in an embodiment, allows for source code comparisons to known systems to predict performance. The benchmarking can be done for varying deployment platforms and various usage patterns.

Abstract: Machines, systems and methods for managing quality of service in a virtualized computing environment, the method comprising: provisioning one or more active virtual machines (VMs) over one or more hosts in a virtualized computing network, wherein one or more resources are allocated to the active VMs before the active VMs service one or more requests; monitoring information associated with quality of service defined for servicing of the requests; and designating at least an active VM as a shadow VMs, in response to results of the monitoring, wherein at least one resource remains allocated to the shadow VM, while the shadow VM enters a dormant state and no longer services any requests.

Abstract: Embodiments of the present invention may provide the capability to identify a specific object being interacted with that may be cheaply and easily included in mass-produced objects. In an embodiment, a computer-implemented method for object identification may comprise receiving a signal produced by a physical interaction with an object to be identified, the signal produced by an identification structure coupled to the object during physical interaction with the object, processing the signal to form digital data identifying the object, and accessing a database using the digital data to retrieve additional information identifying or describing properties of the object identified.

Abstract: A method for providing dynamic resizing of at least one virtual machine in a cloud infrastructure includes steps of: obtaining a measure of resource usage for the virtual machine and/or application performance of an application running on the virtual machine; determining, as a function of prescribed rules relating to resource usage and the measure of resource usage and/or application performance, whether the virtual machine requires resizing; and resizing the virtual machine to dynamically change resource availability for the virtual machine so as to maintain resource usage and/or application performance within prescribed limits defined by the prescribed rules.

Abstract: Embodiments of the present invention may provide the capability to identify a specific object being interacted with that may be cheaply and easily included in mass-produced objects. In an embodiment, a computer-implemented method for object identification may comprise receiving a signal produced by a physical interaction with an object to be identified, the signal produced by an identification structure coupled to the object during physical interaction with the object, processing the signal to form digital data identifying the object, and accessing a database using the digital data to retrieve additional information identifying or describing properties of the object identified.

Abstract: Embodiments of the present invention may provide the capability to identify a specific object being interacted with that may be cheaply and easily included in mass-produced objects. In an embodiment, a computer-implemented method for object identification may comprise receiving a signal produced by a physical interaction with an object to be identified, the signal produced by an identification structure coupled to the object during physical interaction with the object, processing the signal to form digital data identifying the object, and accessing a database using the digital data to retrieve additional information identifying or describing properties of the object identified.

Abstract: Machines, systems and methods for allocating resources to in a virtualized computing environment, the method comprising detecting one or more host machines with resources allocated to one or more virtual machines (VMs) that are in an idle state; reducing resource entitlements for at least one of the VMs that is detected to be in the idle state to make more resources available for allocation to VMs that are not in the idle state; and increasing resource entitlements for at least one of the VMs with reduced entitlement, in response to determining that the VM with reduced entitlement is no longer in the idle state.

Abstract: Systems and methods for managing capacity over-commitment in a resource provisioning environment. The method comprising collecting historical data about capacity usage in a resource provisioning environment and failure statistics from an operational database, in addition to prior service commitments due to previously contracted service level agreements (SLAs) stored in a SLA repository; calculating equivalent capacity for the resource provisioning environment based on a defined residual benefit goal, and other business goals instrumented by way of a policy engine; and determining whether placing requested virtual resources on one or more hosts is feasible taking into account anti-collocation constraints that prohibit placement of two or more virtual resources on same host.

Abstract: Methods, apparatus and computer program products implement embodiments of the present invention that include loading a digital model to a digital manufacturing system having a manufacturing tolerance, and manufacturing, by the digital manufacturing system using the digital model, multiple objects. For each given object, one or more fingerprint measurements of the given object are collected from a fingerprint sensing device having a fingerprint resolution better than the manufacturing tolerance, and using the one or more fingerprint measurements, a unique digital fingerprint is created. The unique digital fingerprint can be stored to a provenance database. Subsequent to storing the unique digital fingerprints, one or more authentication measurements of an authentication object can be collected, and using the one or more authentication measurements, an authentication digital fingerprint can be created.

Abstract: Machines, systems and methods for allocating resources to in a virtualized computing environment, the method comprising detecting one or more host machines with resources allocated to one or more virtual machines (VMs) that are in an idle state; reducing resource entitlements for at least one of the VMs that is detected to be in the idle state to make more resources available for allocation to VMs that are not in the idle state; and increasing resource entitlements for at least one of the VMs with reduced entitlement, in response to determining that the VM with reduced entitlement is no longer in the idle state.

Abstract: A system and method for correlating events in data processing resources processing a workload. An event correlation service comprising an event correlation service software framework is provided on a processor unit. The event correlation service is configured, using the event correlation service software framework, for correlating the events from monitored data for the workload, wherein the workload is processed using the data processing resources provided by a provider of the data processing resources. The event correlation service receives monitored data for the workload as the workload is being processed. The monitored data is processed by the event correlation service to identify an occurrence of an event of interest for the workload as the workload is being processed. An output is provided in response to identifying the occurrence of the event of interest.

Abstract: Machines, systems and methods for deciding whether a plurality of virtual machines (VMs) may be hosted on a computing system with resources to support at least one of the VMs, the method comprising determining maximum permissible probability of infringement (maxPermInfrProb(v)) for a VM(v), wherein “v” is a value from 1 to n, such that n is the number of VMs in a set G, as stipulated by the VMs' SLA, wherein “v” is a value from 1 to n, such that n is the number of VMs in a set G; partitioning the set G into a plurality of groups Gi (G1, . . . Gi, . . . Gn), so that each group is homogenous with respect to maxPermInfrProb defined for members of the group Gi; and organizing the groups Gi based on the value of maxPermInfrProb for each Gi.