A method of managing a fill state of a buffer in an external device includes monitoring the latency of a network connection to an external device having a network buffer via a managing device. A state of fill of the network buffer is determined based on at least the monitored latency of the network connection, and the effective network speed is estimated based on the state of fill of the network buffer. One or more network traffic scheduling parameters are adjusted in response to the estimated effective network speed, such as a maximum currently usable network speed that is lower than a maximum possible speed of the network. The maximum currently usable network speed of the network connection is periodically increased if the monitored latency is in a normal state and the maximum currently usable network speed is lower than the maximum possible speed of the network.

Network capacity is provisioned in a computing environment comprising a computing service provider and an edge computing network. A cost function is applied to usage data for a number of user endpoints at the edge computing network, a number and type of workloads at the edge computing network, offload capability of the edge computing network, and resource capacities at the edge computing network. An estimated network capacity is determined, where the workloads are dynamic, and the cost function is usable to optimize the network capacity with respect to one or more criteria.

Network capacity is provisioned in a computing environment comprising a computing service provider and an edge computing network. A cost function is applied to usage data for a number of user endpoints at the edge computing network, a number and type of workloads at the edge computing network, offload capability of the edge computing network, and resource capacities at the edge computing network. An estimated network capacity is determined, where the workloads are dynamic, and the cost function is usable to optimize the network capacity with respect to one or more criteria.

Disclosed are a network control device and an operation method of the network control device for dynamically constructing an end-to-end virtual dedicated network slice based on a software-defined network (SDN) over the entire wired and wireless network section of a private network and a public network.

Disclosed are a network control device and an operation method of the network control device for dynamically constructing an end-to-end virtual dedicated network slice based on a software-defined network (SDN) over the entire wired and wireless network section of a private network and a public network.

A network control and rate optimization solution for multiuser multiple input multiple output (MU-MIMO) communications in wireless networks. This solution is decentralized and includes scheduling and routing of the MU-MIMO communication links that adapt to dynamic channel, interference, and traffic conditions. The ergodic sum rates of MIMO multiple access channel (MAC) and interference channel (IC) configurations are analyzed by considering the error, and overhead effects due to channel estimation (training) and quantization (feedback). By taking practical considerations such as channel estimation, quantization error and in-network interference into account, the rate gain is shown with an increasing number of antennas compared with single-input single-output (SISO) systems. A distributed channel access protocol to select and activate MU-MIMO configurations is presented with the maximum achievable sum rates using local information on channel, interference, and traffic conditions. The scheduling algorithm is extended to routing via a cross-layer solution based on a decentralized version of the backpressure algorithm. After accounting for the control message overhead, it is shown that the proposed MU-MIMO scheduling and routing solution improves the stable throughput over the minimum distance routing based on frequency of encounters and single user MIMO communications in a mobile ad hoc network (MANET) setting.

A network control and rate optimization solution for multiuser multiple input multiple output (MU-MIMO) communications in wireless networks. This solution is decentralized and includes scheduling and routing of the MU-MIMO communication links that adapt to dynamic channel, interference, and traffic conditions. The ergodic sum rates of MIMO multiple access channel (MAC) and interference channel (IC) configurations are analyzed by considering the error, and overhead effects due to channel estimation (training) and quantization (feedback). By taking practical considerations such as channel estimation, quantization error and in-network interference into account, the rate gain is shown with an increasing number of antennas compared with single-input single-output (SISO) systems. A distributed channel access protocol to select and activate MU-MIMO configurations is presented with the maximum achievable sum rates using local information on channel, interference, and traffic conditions. The scheduling algorithm is extended to routing via a cross-layer solution based on a decentralized version of the backpressure algorithm. After accounting for the control message overhead, it is shown that the proposed MU-MIMO scheduling and routing solution improves the stable throughput over the minimum distance routing based on frequency of encounters and single user MIMO communications in a mobile ad hoc network (MANET) setting.

A method (400) for providing support for elasticity within a domain of a multi-domain network. The method comprises receiving (401) information for a requested virtual link forming part of an end-to-end path across the multi-domain network; wherein the information of the virtual link comprises a service parameter and an elasticity parameter. The method further comprises selecting (402) a physical path (150) corresponding to the virtual link on which to send traffic. The physical path is selected based on a service parameter and an elasticity parameter of the physical path.

A technique for distributing transmission resources in a media data streaming system is disclosed. A user terminal of the media data streaming system comprises an interface configured to receive a stream of variable bitrate encoded media data via a communications network. The user terminal further comprises a memory storing program code and at least one processing device configured to execute the program code. The program code causes the processing device to determine bitrate variation information for the media data stream and to trigger transmission of the bitrate variation information towards a network component. The network component is configured to trigger dynamic distribution of the transmission resources of the communications network among multiple user terminals dependent on the bitrate variation information.

The present system relates to a server for providing data connectivity in a packet mode communication network. The server has a processor arranged to receive, via a first brokerage control unit, a charging rule request to allow one or more communication devices in the communication network to exchange with an application server data charged under operator specific billing. The server determines availability of the operator specific billing based on network parameters and the charging rule request, and updates the database of a Policy and Charging Rules Function (PCRF) entity in the communication network based on available operator specific billing and an identifier for the application server, for subsequent charging of data exchanged with the application server at said available operator specific billing.