A method for generating an application-aware virtual topology (AAVT) routing table for a network device among network devices connected via a wide area network is provided. The method is executed by a network controller connected to the network and includes: receiving, from the network devices, path information of the network devices; generating, using the path information, an underlay graph specifying a path topology of the network device; generating, based on the path topology specified in the underlay graph, the AAVT routing table for the network device where the AAVT routing table includes a set of paths; and transmitting, in response to generating the AAVT routing table, the AAVT routing table to the network device to cause the network device to program the set of paths.

A method for generating an application-aware virtual topology (AAVT) routing table for a network device among network devices connected via a wide area network is provided. The method is executed by a network controller connected to the network and includes: receiving, from the network devices, path information of the network devices; generating, using the path information, an underlay graph specifying a path topology of the network device; generating, based on the path topology specified in the underlay graph, the AAVT routing table for the network device where the AAVT routing table includes a set of paths; and transmitting, in response to generating the AAVT routing table, the AAVT routing table to the network device to cause the network device to program the set of paths.

Systems and methods are disclosed for identifying a set of internal edges on a representation of a network that satisfy a set of demands on the network. The disclosed systems and methods perform a multi-step process of selecting the internal edges. In a first step, an initial set of internal edges can be selected using a clique graph (or in another suitable manner). In a second step, a second set of internal edges can be selected using stream graph(s) (or in another suitable manner). The second set of internal edges can be used when determining network paths that satisfy the demands. When the representation of the network has a cut of two, the disclosed systems and methods can identify a set of internal edges providing a degree of protection against link failure.

Systems and methods are disclosed for identifying a set of internal edges on a representation of a network that satisfy a set of demands on the network. The disclosed systems and methods perform a multi-step process of selecting the internal edges. In a first step, an initial set of internal edges can be selected using a clique graph (or in another suitable manner). In a second step, a second set of internal edges can be selected using stream graph(s) (or in another suitable manner). The second set of internal edges can be used when determining network paths that satisfy the demands. When the representation of the network has a cut of two, the disclosed systems and methods can identify a set of internal edges providing a degree of protection against link failure.

A visibility platform can be used to monitor traffic traversing private cloud infrastructures and/or public cloud infrastructures. In some instances, the traffic is provided to a set of network services that are accessible to the visibility platform. These network services can be provisioned in a serial or parallel fashion. Network service chaining can be used to ensure that traffic streams skip unnecessary network services and receive only those network services that are needed. For example, an email service chain can include virus, spam, and phishing detection, while a video streaming service chain can include traffic shaping policies to satisfy quality of service (QoS) guarantees. When the visibility platform is represented as a graph that makes use of action sets, network service chains can be readily created or destroyed on demand.

A visibility platform can be used to monitor traffic traversing private cloud infrastructures and/or public cloud infrastructures. In some instances, the traffic is provided to a set of network services that are accessible to the visibility platform. These network services can be provisioned in a serial or parallel fashion. Network service chaining can be used to ensure that traffic streams skip unnecessary network services and receive only those network services that are needed. For example, an email service chain can include virus, spam, and phishing detection, while a video streaming service chain can include traffic shaping policies to satisfy quality of service (QoS) guarantees. When the visibility platform is represented as a graph that makes use of action sets, network service chains can be readily created or destroyed on demand.

Techniques are disclosed for determining predictions from a graph of a network dataset. The graph of the network dataset may include nodes describing entities and edges describing connections or links between the entities. Predictions may be made using a dual-path convolution network that considers both node connectivity and node topology. Node topology includes assessment of similarities in topology roles between nodes in the graph, even nodes that reside in different parts of the graph. The node connectivity and node topology in the dual-path convolution may be aligned using a multi-head attention network. Outputs from previous layers of the multi-head attention network may be provided as inputs to subsequent layers of the dual-path convolution to mutually reinforce the convolutions determining node connectivity and node topology toward alignment.

Techniques are disclosed for determining predictions from a graph of a network dataset. The graph of the network dataset may include nodes describing entities and edges describing connections or links between the entities. Predictions may be made using a dual-path convolution network that considers both node connectivity and node topology. Node topology includes assessment of similarities in topology roles between nodes in the graph, even nodes that reside in different parts of the graph. The node connectivity and node topology in the dual-path convolution may be aligned using a multi-head attention network. Outputs from previous layers of the multi-head attention network may be provided as inputs to subsequent layers of the dual-path convolution to mutually reinforce the convolutions determining node connectivity and node topology toward alignment.

Packet routers route data packets based on existing topology files. The packet routers hash the existing topology files into content-addressed objects and exchange the content-addressed objects. One of the routers modifies its topology file into a new topology file, hashes the new topology file into a new content-addressed object, and transfers the new content-addressed object to the other packet routers. The packet routers exchange the content-addressed objects, and in response, exchange the topology files. The routers establish a consensus on the new topology file based on the existing topology files. The one packet router routes additional data packets based on the new topology file in response to the consensus. In some examples, the content-addressed objects comprise Inter-Planetary File System (IPFS) objects.

Packet routers route data packets based on existing topology files. The packet routers hash the existing topology files into content-addressed objects and exchange the content-addressed objects. One of the routers modifies its topology file into a new topology file, hashes the new topology file into a new content-addressed object, and transfers the new content-addressed object to the other packet routers. The packet routers exchange the content-addressed objects, and in response, exchange the topology files. The routers establish a consensus on the new topology file based on the existing topology files. The one packet router routes additional data packets based on the new topology file in response to the consensus. In some examples, the content-addressed objects comprise Inter-Planetary File System (IPFS) objects.