A network management system (NMS) for a communications network has communications apparatus capable of being operated in different power consumption modes to provide different levels of performance, has a path computation apparatus configured to select paths for the traffic using the communications apparatus, based on information about traffic load in the network and on information about the power consumption modes of the communications apparatus of at least one of the nodes. A power mode controller is also provided for controlling the power consumption modes of the communications apparatus according to information about traffic load and according to information about the paths selected. By combining of path computation and the control of power consumption modes the overall power consumption of the network can be reduced. A slave power mode controller can be provided.

In some examples, a controller for a network includes a path computation module that determines, for a plurality of LSPs or other flows having a common source, shortest paths of the network from the common source to respective destinations of the plurality of LSPs based at least on a minimum bandwidth. The path computation module further determines, after determining the shortest paths, a shortest path for the LSP of the plurality of LSPs as the shortest path of the shortest paths of the network from the common source to a destination for the LSP. A path provisioning module of the controller, after the path computation module determines the shortest path for the LSP and in response to the path computation modules routing the LSP to the shortest path for the LSP on a network model of the network, installs the LSP to the network as routed to the shortest path.

A method for controlling messages between communicating entities (CE) having computing devices, each CE sending messages to other neighboring CE with a entity-dependent message rate (CEMR), and with an entity-dependent transmission power, the messages being transmitted via one or more channels having a maximum channel capacity, and the CEMR defining a rate interval between a minimum and maximum rate, includes determining the CEMR within the rate interval by: (a) using a utility function for each CE; b) assigning an initial price for each CE; (c) adjusting the CEMR of each CE accounting for received prices of other CE; (d) computing a new price for each CE based on difference between initial price and available channel load for respective CEs; and (e) checking a termination condition for the difference and if unfulfilled, use the new price as initial price and repeat (c)-(e) until a termination condition is fulfilled.

Provided is a Weighted DESYNC based cross-layered resource allocation method. The method includes, with respect to each of a plurality of nodes constituting a routing path, calculating a link quality value with the next node, receiving a link quality value from at least one neighbor node, and based on the link quality values in the calculating of the link quality value and the receiving of the link quality value, calculating a weight factor for synchronizing a transmission yield.

A system for determining an optimal schedule for transmitting data from a source node to a destination node in a telecommunications network. The source node is connected to a plurality of egress links. The system comprises a schedule generator for generating a plurality of candidate schedules. The schedule generator is configured to automatically generate a candidate schedule for each egress link of the source node by selecting a first window of time, determining a highest throughput route starting at the egress link during the first window of time based on predicted link utilisations, and if the throughput of the highest throughput route is not sufficient to transport all the data during the first window of time, selecting one or more subsequent windows of time and, for each subsequent window of time, determining a highest throughput route starting at the egress link during the subsequent window of time based on predicted link utilisations until a candilate schedule for transferring all the data has been defined. The system also comprises a schedule selector for automatically selecting a best candidate schedule from the plurality of candidate schedules based on the time taken to transfer all the data across the network.

A method is provided in one example and includes determining a bandwidth level associated with a link, which is provided between a first microwave transceiver and a second microwave transceiver. The link is part of a communication ring containing multiple Ethernet ring protection elements. The method also includes comparing the bandwidth level associated with the link to a threshold level. A fail-over can be triggered for a selected one of the plurality of Ethernet ring protection elements if the bandwidth is below the threshold level. In certain example embodiments, the first microwave transceiver and the second microwave transceiver can implement an adaptive modulation protocol on the link.

The disclosed computer-implemented method for forwarding network traffic using minimal Forwarding Information Bases (FIBS) may include (1) identifying a Routing Information Base (RIB) that includes a set of routes that define paths to destinations both inside and outside a network and then (2) creating a FIB that includes a subset of active routes whose size is below a size threshold by (A) importing, from the set of routes within the RIB, (I) internal routes that define paths to destinations inside the network, (II) high-traffic external routes that define paths to destinations outside the network, and (III) a default route that defines a path to a default node that facilitates resolution of traffic that does not match any of the internal or high-traffic external routes and (B) excluding, from the FIB, low-traffic external routes that define paths to destinations outside the network. Various other methods, systems, and apparatuses are also disclosed.

A computing method of using a processor to manage a virtualization of a network bonding connection includes organizing one or a plurality of network bonding engines, each of the network bonding engines configured to split input data from at least one input data source into a plurality of data streams communicated over a plurality of wireless IP connections of different performance characteristics, or to reassemble the input data from the plurality of data streams. The organizing of the one or a plurality of network bonding engines includes choosing one or more wireless IP connections from the plurality of wireless IP connections to form one or more bonding groups through which the split data is communicated, and assigning network functions to each of the one or more bonding groups.

A machine-learning optimization of a plurality of networks is provided. The machine-learning optimization includes interconnecting an online platform providing a machine learning module, a core network of computers deploying novel software, and a plurality of Internet network service providers. The platform collects, via the software, performance data of the Internet networks, which the machine learning module utilizes to enhance performance and reduce the latency therein networks by taking into account thousands of real-time and historic latency and bandwidth metrics. Thereby the software continually selects an optimal path through the plurality of Internet networks.

The invention relates in particular to the optimization of routing in a cluster comprising a plurality of nodes and static communication links connecting nodes of the plurality of nodes, said routing being based on load levels associated with the communication links. In order to establish a connection between at least two nodes of the cluster that have been identified (505), at least one route is determined (510) that connects the identified nodes according to the communication links, said route being determined according to the nodes identified, communication links and at least one load level associated with each communication link. A determined route is selected. Subsequently, a value of weight associated with the selected route is estimated (520) and a load level associated with each communication link of the selected route is incremented (525).