A self-configuring router includes a resource allocator that automatically assigns processors to queues, such that queue workload is distributed as evenly as possible among the processors, and the processors are as fully utilized as possible. Consequently, packets do not remain on queues longer than necessary, thereby decreasing latency of packets traversing the router, and available and expensive resources, namely the processors, are kept busy. The router automatically allocates its own resources (processors) to its own queues.

A provisioning system for a distributed computing environment includes a map reduce framework that includes a splitter process, a mapper process, and a reduce process. The splitter process receives a task associated with a distributed application to be deployed on the distributed computing environment, and selects which of the resources are to be provisioned for executing the distributed application. The mapper process converts at least one abstract address included in the task to an absolute address, and executes the task for provisioning the selected resources, while the reduce process consolidates results of the executed task.

Systems and methods for providing web service instances to support traffic demands for a particular web service in a large-scale distributed system are disclosed. An example method includes determining a peak historical service load for the web service. The service load capacity for each existing web service instance may then be determined. The example method may then calculate the remaining service load after subtracting the sum of the service load capacity of the existing web service instances from the peak historical service load for the web service. The number of web service instances necessary in the large-scale distributed system may be determined based on the remaining service load. The locations of the web service instances may be determined and changes may be applied to the large-scale system based on the number of web service instances necessary in the large-scale distributed system.

A method of allocating cloud computing resources in a cloud computing environment to a user is disclosed. The method comprises determining a prediction accuracy score for each user indicative of their user predictability, and allocating cloud computing resources to each user dependent on their user predictability.

A computer-implemented method includes generating a query. The query is directed to a database server. The database server allocating a predetermined quantity of computing resources to the query. The method includes identifying a speed threshold. The method includes determining a quantity of running resources. The quantity of running resources is effective for a running speed for the query to exceed the speed threshold. The method is responsive to the quantity of running resources being greater than the predetermined quantity of computing resources. The method includes including an option with the query. The option is for additional computing resources to be allocated to the query. The method is responsive to input selecting the option, by transmitting the query and the additional computing resources to the database server.

A cloud broker gateway interfaces with an enterprise network and one or more public cloud networks, including a first public cloud and a second public cloud. The cloud broker gateway receives a request for one or more computing resources from a tenant associated with the enterprise network, and directs the request to the first public cloud based on a brokerage policy for the tenant. The cloud broker gateway receives a response indicating the first public cloud cannot provide the one or more computing resources, and redirects the request to the second public cloud based on the brokerage policy for the tenant. The cloud broker gateway also establishes a hybrid cloud that provides access to the one or more computing resources between the second public cloud and the enterprise network.

The invention relates to a network node and a method therein for admission control in a wireless communication system. The method comprises receiving a request for a bearer setup from a requesting entity, where the request and/or bearer is associated with a priority level P. The method further comprises obtaining, e.g. receiving or retrieving, reports indicating a priority blocking level, BLi, per monitored system resource, i, needed for setting up a bearer. The method further comprises determining a general priority blocking level BLG, based on the reports. Further, the method comprises deciding whether to accept or reject the request for a bearer setup based on the priority level P and the general priority blocking level BLG.

Methods and systems disclosed herein relate to determining a projected change in bandwidth demand in a specified area during a specified future time period, repositioning one or more balloons in a high-altitude balloon network based on the projected change in bandwidth demand, and providing, using the one or more balloons, at least a portion of the bandwidth demanded in the specified area during the specified future time period.

A cloud service brokerage system includes an electronic cloud service catalog containing cloud service defining information for a plurality of cloud services and a cloud service store coupled to the electronic cloud service catalog. The cloud service store includes cloud service publications each representing cloud service functionality corresponding to one or more of the cloud services. The cloud service store includes a user interface structure enabling generation of cloud service orders each including one or more of the cloud service publications.

The invention introduces a method for an automatic scaling of data consumers, performed by a processing unit of a data-consumer server, which contains at least the following steps. State-update requests are received from data consumers, where each state-update request includes a busy state or an idle state and the busy state indicates that the data consumer reads data from a queue and processes the read data. A first quantity of data consumers, a second quantity of busy states and a third quantity of idle states are calculated. A fourth quantity of data consumers to be produced is estimated according to the first, second and third quantities. Data consumers of the fourth quantity are produced.