Abstract: Methods and systems for medicine disposition in hospitals are disclosed. A method includes: receiving, by a computing device, an electronic health record (EHR) of a patient; receiving, by the computing device, an order to dispense a medicine to the patient; receiving, by the computing device, information from a wearable device of the patient and updating the EHR of the patient based on the information from the wearable device of the patient; determining, by the computing device, that a health concern is not identified based on the information from the wearable device of the patient; and dispensing, by the computing device, the medicine to the patient in accordance with the order.

Abstract: Methods and systems for medicine disposition in hospitals are disclosed. A method includes: receiving, by a computing device, an electronic health record (EHR) of a patient; receiving, by the computing device, an order to dispense a medicine to the patient; receiving, by the computing device, information from a wearable device of the patient and updating the EHR of the patient based on the information from the wearable device of the patient; determining, by the computing device, that a health concern is not identified based on the information from the wearable device of the patient; and dispensing, by the computing device, the medicine to the patient in accordance with the order.

Abstract: A system for corporate travel is provided. One or more travel-related data for a given time period is determined. One or more expenditures based, at least, on the one or more travel-related data is determined. A graphical template based, at least, on an expenditure target is generated.

Abstract: Resource configuration to exploit elastic network capability is provided by establishing an elastic network bandwidth allocation level to provide for an application for transfer of data between the application and an elastic network, the application hosted at a data center, then dynamically configuring, for the application, elastic network bandwidth allocation from the network service provider in accordance with the established elastic network bandwidth allocation level, and allocating storage resources of the data center for the application and processing resources of the data center for the application, the allocating being based on the established elastic network bandwidth allocation level and providing storage resources and processing resources to operate at a level commensurate with the established elastic network bandwidth allocation level.

Abstract: Dynamic configuration of network features is provided by performing real-time traffic analysis on network traffic flowing between an elastic cloud computing network and an edge appliance, evaluating effects of modifying elastic network bandwidth allocation and applying network traffic optimizations in routing traffic flowing between the elastic cloud computing network and the edge appliance, and dynamically configuring, based on the real-time traffic analysis and on the evaluating, one or more of (i) elastic network bandwidth allocation from the network service provider or (ii) at least one of the network traffic optimizations for performance by the edge appliance in routing traffic flowing between the elastic cloud computing network and the edge appliance.

Abstract: Dynamic quality of service for storage I/O port allocation is provided by obtaining indications of anticipated demand on a plurality of storage ports of a storage device of a data center, the anticipated demand being at least in part for storage input/output supporting transfer of data to or from a network, and dynamically adjusting storage port allocations based on the indications of anticipated demand and on real-time evaluation of workloads being serviced by the plurality of storage ports.

Abstract: Event-based data transfer scheduling using elastic network optimization criteria is provided. Bandwidth optimization criteria corresponding to different types of data transfer event scenarios are maintained, and based on recognizing a data transfer event scenario, a bandwidth optimization criteria is selected based on a type of the data transfer event scenario. A schedule for transferring data from a source to a target across the elastic network is determined according to the selected bandwidth optimization criteria, and the elastic network is used in transferring the data to the target storage location, where the using includes dynamically configuring elastic network bandwidth allocation from an elastic network service provider and initiating transfer of the data to the target storage location according to the schedule.

Abstract: A method and associated systems for automatic redistribution of virtual machines. A cloud-optimization module selects parameters, such as bandwidth requirements, that characterize an efficiency of a virtual network. It assigns weightings to these parameters based on relative importance of each parameter to the proper operation of the network, where the weightings may be determined as functions of captured network-performance statistics. The module translates the network's topology into a graph in which each node represents a network entity, such as a virtual machine or an application, and each edge represents a connection between two such entities. The module then uses a growing neural gas algorithm to revise the graph and the weightings, and translates the revised graph to a more optimal topology that has redistributed the network entities to operate more efficiently, as measured by the weighted parameters.

Abstract: A method and associated systems for a resource-utilization monitor with self-adjusting sample size. A processor monitors availability of a resource-limited entity by analyzing a set of samples that each identify, at the time the sample was recorded, an unused amount of resource available to the entity. The processor computes a Chi-square statistic of the sample set. If the statistic reveals that the number of samples in the sample set is too small to produce valid results, the processor adjusts the sample size to specify a larger number of samples and repeats these steps. If the number of samples is large enough to produce statistically valid results, the processor analyzes the sample set to determine whether the current amount of remaining resource is undesirably low, is likely to become undesirably low during a short-term period of time, or is likely to become undesirably low during a longer-term period of time.

Abstract: Controlled transfer of data over an elastic network is provided and includes analyzing properties of a set of data for transfer from a source storage location to a target storage location across an elastic cloud computing network as part of a staged transfer of the set of data, assigning transfer queue weightings to data subsets of the set of data based on weighting parameters, the transfer queue weightings dictating order of transfer of the data subsets from the source storage location to the target storage location, and controlling transfer of the data subsets from the source storage location to the target storage location consistent with the transfer queue weightings assigned to the data subsets, the controlling transfer including controlling, based on costs to transfer the data subsets, bandwidth allocation of the elastic cloud computing network and a transfer schedule for the data subsets.

Abstract: Resource configuration to exploit elastic network capability is provided by establishing an elastic network bandwidth allocation level to provide for an application for transfer of data between the application and an elastic network, the application hosted at a data center, then dynamically configuring, for the application, elastic network bandwidth allocation from the network service provider in accordance with the established elastic network bandwidth allocation level, and allocating storage resources of the data center for the application and processing resources of the data center for the application, the allocating being based on the established elastic network bandwidth allocation level and providing storage resources and processing resources to operate at a level commensurate with the established elastic network bandwidth allocation level.

Abstract: Data transfer using flexible dynamic elastic network service provider relationships is provided. A relationship is dynamically established with an elastic network service provider of multiple available elastic network service providers to transfer a portion of the set of data to the target. Peering policies for each of the multiple elastic network service providers are checked, where a respective peering policy for each elastic network service provider includes respective bandwidth pricing information. Based on the bandwidth pricing information for each of the plurality of elastic network service providers, an elastic network service provider and a schedule are selected to use in transferring the portion to the target. The elastic network service provider is used in transferring the portion to the target, which includes dynamically configuring elastic network bandwidth allocation from the elastic network service provider and initiating transfer of the portion to the target according to the selected schedule.

Abstract: An approach is provided for managing an allocation of a bandwidth of a dedicated channel in a network being utilized by an application performing a replication of data from a first to a second storage resource. Checks of parameters specified by the application are determined. The parameters include, but are not limited to, average compression ratio, compression ratio trend, throughput, throughput trend, and round trip time. Respective high and low threshold values for the parameters are determined. At least one of the checks of the parameters is executed, which determines a violation of a threshold value for one of the parameters. If the violation of the high threshold value is determined, an increase in the bandwidth is triggered. If the violation of the low threshold value is determined, a decrease in the bandwidth is triggered.

Abstract: Resource configuration to exploit elastic network capability is provided by establishing an elastic network bandwidth allocation level to provide for an application for transfer of data between the application and an elastic network, the application hosted at a data center, then dynamically configuring, for the application, elastic network bandwidth allocation from the network service provider in accordance with the established elastic network bandwidth allocation level, and allocating storage resources of the data center for the application and processing resources of the data center for the application, the allocating being based on the established elastic network bandwidth allocation level and providing storage resources and processing resources to operate at a level commensurate with the established elastic network bandwidth allocation level.

Abstract: Dynamic configuration of network features is provided by performing real-time traffic analysis on network traffic flowing between an elastic cloud computing network and an edge appliance, evaluating effects of modifying elastic network bandwidth allocation and applying network traffic optimizations in routing traffic flowing between the elastic cloud computing network and the edge appliance, and dynamically configuring, based on the real-time traffic analysis and on the evaluating, one or more of (i) elastic network bandwidth allocation from the network service provider or (ii) at least one of the network traffic optimizations for performance by the edge appliance in routing traffic flowing between the elastic cloud computing network and the edge appliance.

Abstract: Resource configuration to exploit elastic network capability is provided by establishing an elastic network bandwidth allocation level to provide for an application for transfer of data between the application and an elastic network, the application hosted at a data center, then dynamically configuring, for the application, elastic network bandwidth allocation from the network service provider in accordance with the established elastic network bandwidth allocation level, and allocating storage resources of the data center for the application and processing resources of the data center for the application, the allocating being based on the established elastic network bandwidth allocation level and providing storage resources and processing resources to operate at a level commensurate with the established elastic network bandwidth allocation level.

Abstract: Event-based data transfer scheduling using elastic network optimization criteria is provided. Bandwidth optimization criteria corresponding to different types of data transfer event scenarios are maintained, and based on recognizing a data transfer event scenario, a bandwidth optimization criteria is selected based on a type of the data transfer event scenario. A schedule for transferring data from a source to a target across the elastic network is determined according to the selected bandwidth optimization criteria, and the elastic network is used in transferring the data to the target storage location, where the using includes dynamically configuring elastic network bandwidth allocation from an elastic network service provider and initiating transfer of the data to the target storage location according to the schedule.

Abstract: Controlled transfer of data over an elastic network is provided and includes analyzing properties of a set of data for transfer from a source storage location to a target storage location across an elastic cloud computing network as part of a staged transfer of the set of data, assigning transfer queue weightings to data subsets of the set of data based on weighting parameters, the transfer queue weightings dictating order of transfer of the data subsets from the source storage location to the target storage location, and controlling transfer of the data subsets from the source storage location to the target storage location consistent with the transfer queue weightings assigned to the data subsets, the controlling transfer including controlling, based on costs to transfer the data subsets, bandwidth allocation of the elastic cloud computing network and a transfer schedule for the data subsets.

Abstract: Data transfer using flexible dynamic elastic network service provider relationships is provided. A relationship is dynamically established with an elastic network service provider of multiple available elastic network service providers to transfer a portion of the set of data to the target. Peering policies for each of the multiple elastic network service providers are checked, where a respective peering policy for each elastic network service provider includes respective bandwidth pricing information. Based on the bandwidth pricing information for each of the plurality of elastic network service providers, an elastic network service provider and a schedule are selected to use in transferring the portion to the target. The elastic network service provider is used in transferring the portion to the target, which includes dynamically configuring elastic network bandwidth allocation from the elastic network service provider and initiating transfer of the portion to the target according to the selected schedule.

Abstract: Dynamic quality of service for storage I/O port allocation is provided by obtaining indications of anticipated demand on a plurality of storage ports of a storage device of a data center, the anticipated demand being at least in part for storage input/output supporting transfer of data to or from a network, and dynamically adjusting storage port allocations based on the indications of anticipated demand and on real-time evaluation of workloads being serviced by the plurality of storage ports.