Abstract: A system may assist with checking policy impact in a software-defined infrastructure environment. The system's data analysis may enable it to discover and quantify the impact of policies on software-defined infrastructure objects in the same or different layers.

Abstract: A system may assist with checking policy impact in a software-defined infrastructure environment. The system's data analysis may enable it to discover and quantify the impact of policies on software-defined infrastructure objects in the same or different layers.

Abstract: A system may assist with checking policy impact in a software-defined infrastructure environment. The system's data analysis may enable it to discover and quantify the impact of policies on software-defined infrastructure objects in the same or different layers.

Abstract: A system may assist with checking policy impact in a software-defined infrastructure environment. The system's data analysis may enable it to discover and quantify the impact of policies on software-defined infrastructure objects in the same or different layers.

Abstract: A system may assist with checking policy impact in a software-defined infrastructure environment. It may perform continuous learning of impact using emulations under varying conditions and may take a statistical and machine learning based analysis approach on the data obtained from emulations. The system's data analysis may enable it to discover and quantify the impact of policies on software-defined infrastructure objects in the same or different layers.

Abstract: A system may assist with checking policy impact in a software-defined infrastructure environment. The system's data analysis may enable it to discover and quantify the impact of policies on software-defined infrastructure objects in the same or different layers.

Abstract: When traffic arrives from the network for an idle mobile device, the network executes device activation procedures to awaken the device, which can result in a significant amount of signaling to complete. Adaptive device activation mechanisms are provided that adapt to network conditions and potentially to machine-to-machine device application requests to realize scalable device activation without increasing the resources used for this purpose and without negatively impacting existing human-to-human or human-to-machine traffic.

Abstract: Methods, systems, and devices for automatically and dynamically managing and coordinating network resources used by services between users over a data network having a network infrastructure. A network resources coordinator can include a knowledge store, rules library, rules engine, and orchestrator. The knowledge store can have a plurality of layered abstraction stores having stored thereon facts representative of a present state of the network. The rules library can include production rules representative of knowledge of the network and of users. The orchestrator can receive service requests from users and use the rules engine in conjunction with the production rules of the rules library and facts of the knowledge store to: determine network resources required and available for requested services, dynamically make automated decisions with respect to the network and users, detect and react to changes in the network in an automated fashion, and enforce constraints of the network.

Abstract: When traffic arrives from the network for an idle mobile device, the network executes device activation procedures to awaken the device, which can result in a significant amount of signaling to complete. Adaptive device activation mechanisms are provided that adapt to network conditions and potentially to machine-to-machine device application requests to realize scalable device activation without increasing the resources used for this purpose and without negatively impacting existing human-to-human or human-to-machine traffic.

Abstract: Methods, systems, and devices for automatically and dynamically managing and coordinating network resources used by services between users over a data network having a network infrastructure. A network resources coordinator can include a knowledge store, rules library, rules engine, and orchestrator. The knowledge store can have a plurality of layered abstraction stores having stored thereon facts representative of a present state of the network. The rules library can include production rules representative of knowledge of the network and of users. The orchestrator can receive service requests from users and use the rules engine in conjunction with the production rules of the rules library and facts of the knowledge store to: determine network resources required and available for requested services, dynamically make automated decisions with respect to the network and users, detect and react to changes in the network in an automated fashion, and enforce constraints of the network.

Abstract: Traffic flow from a traffic source with a source IP address to a customer system with a destination IP address is filtered by comparing the source IP address to a customer blacklist. If the source IP address is on the customer blacklist, then traffic to the customer system is blocked; else, traffic to the customer system is allowed. The customer blacklist is generated from a network blacklist, comprising IP addresses of unwanted traffic sources, and a customer whitelist, comprising IP addresses of wanted traffic sources. The customer blacklist is generated by removing from the network blacklist any IP address also on the customer whitelist. The network blacklist is generated by acquiring raw blacklists from reputation systems. IP addresses on the raw blacklists are sorted by prefix groups, which are rank ordered by traffic frequency. Top prefix groups are selected for the network blacklist.

Abstract: Traffic flow from a traffic source with a source IP address to a customer system with a destination IP address is filtered by comparing the source IP address to a customer blacklist. If the source IP address is on the customer blacklist, then traffic to the customer system is blocked; else, traffic to the customer system is allowed. The customer blacklist is generated from a network blacklist, comprising IP addresses of unwanted traffic sources, and a customer whitelist, comprising IP addresses of wanted traffic sources. The customer blacklist is generated by removing from the network blacklist any IP address also on the customer whitelist. The network blacklist is generated by acquiring raw blacklists from reputation systems. IP addresses on the raw blacklists are sorted by prefix groups, which are rank ordered by traffic frequency. Top prefix groups are selected for the network blacklist.

Abstract: The invention provides apparatus and methods for a Virtual Private Network (VPN) in a network that offers a simple user interface for efficient utilization of network resources. The VPN is defined for a specified set of endpoints each of which is associated with a single “hose.” A hose provides access to the VPN through an access point which may be a node of the network, for example. The hose is a single interface to the VPN for communication to all other endpoints of the VPN. The VPN achieves network resource allocation efficiency by exploiting resource sharing possibilities via multiplexing routing paths between endpoints and dynamic resource allocation techniques that permit real time resource allocation resizing. When a VPN is established with a VPN service provider, the routing paths between the endpoints of the VPN is optimized for multiplexing opportunities so that resource allocations between nodes along routing paths within the IP network is reduced to a minimum.

Abstract: A switch (10) for controlling the switching of communication paths in communication equipment, such as telephone networks, is connected to a plurality of controllers (11, 12, 13) via a divider unit (14). The divider unit (14) divides some or all of the resources of the switch (10) into a plurality of switch resource sets, and those switch resource sets are then associated with respective ones of the controllers (11, 12, 13). This has the effect of enabling each switch resource set to act as an independent sub-switch, with each controller (11, 12, 13) then controlling a corresponding sub-switch. This division of the resources of the switch (10) allows different control architectures to be operated simultaneously. This permits different virtual networks to be constituted on the same physical network. Any one of the controllers (11, 12, 13) has access only to the switch resource set or sets allocated to that controller (11, 12, 13).