Abstract: In one embodiment, a first label-distribution-protocol (LDP) session is established between a first interface of a first computing device and a second computing device, while a second LDP session is established between a second interface and the second computing device. The method may further comprise receiving a request from a third computing device to subscribe to a multicast group, storing an association between a first label, the multicast group, and the first interface, and sending, to the second computing device via the first LDP session, an indication that the first label is associated with the multicast group. Further, the method may include receiving a request from a fourth computing device to subscribe to the multicast group, storing an association between a second label, the multicast group and, the second interface, and sending, via the second LDP session, an indication that the second label is associated with the multicast group.

Abstract: In one embodiment, a first label-distribution-protocol (LDP) session is established between a first interface of a first computing device and a second computing device, while a second LDP session is established between a second interface and the second computing device. The method may further comprise receiving a request from a third computing device to subscribe to a multicast group, storing an association between a first label, the multicast group, and the first interface, and sending, to the second computing device via the first LDP session, an indication that the first label is associated with the multicast group. Further, the method may include receiving a request from a fourth computing device to subscribe to the multicast group, storing an association between a second label, the multicast group and, the second interface, and sending, via the second LDP session, an indication that the second label is associated with the multicast group.

Abstract: An algorithm for modeling and optimizing control of a complex and dynamic system is provided to facilitate an allocation of the resources on the network that is the most efficient. The algorithm serves to depict the complex network of available resources using market-based negotiation wherein resources are defined as available buyers and sellers in an efficient market. Selling agents are offering their available resources for sale in accordance with parameters that correspond to the actual limitations of that actual resource and the buyers are looking to make a purchase from one of the sellers that presents a resource with the greatest utility to them. In order to overcome inefficiencies that result from the potential of inefficient allocation, the present invention has further endeavored to introduce an efficiency-arbitrage agent that scans the overall body of transactions to identify and remedy inefficient market transactions.

Abstract: A method and system for implementing a weighted belief network that assists collaborative users in making decisions. A belief network structure is employed that further includes user controlled weighting and biasing factors to adjust the probabilities for the various nodes. The various participants have the opportunity to make adjustments to the weighting and credibility of the evidence and participants in the decision making process in order to arrive at what may be perceived as a more objective outcome. As the collaborative environment is established and the belief network is built, each user can apply various weighting and bias scenarios from their own perspective thereby allowing each discrete user to work out their various suspicions regarding the bias of other participants or the actual weight of a discrete piece of supporting evidence in the context of the entire belief network.

Abstract: A method and system for implementing a weighted belief network that assists collaborative users in making decisions. A belief network structure is employed that further includes user controlled weighting and biasing factors to adjust the probabilities for the various nodes. The various participants have the opportunity to make adjustments to the weighting and credibility of the evidence and participants in the decision making process in order to arrive at what may be perceived as a more objective outcome. As the collaborative environment is established and the belief network is built, each user can apply various weighting and bias scenarios from their own perspective thereby allowing each discrete user to work out their various suspicions regarding the bias of other participants or the actual weight of a discrete piece of supporting evidence in the context of the entire belief network.

Abstract: An algorithm for modeling and optimizing control of a complex and dynamic system is provided to facilitate an allocation of the resources on the network that is the most efficient. The algorithm serves to depict the complex network of available resources using market-based negotiation wherein resources are defined as available buyers and sellers in an efficient market. Selling agents are offering their available resources for sale in accordance with parameters that correspond to the actual limitations of that actual resource and the buyers are looking to make a purchase from one of the sellers that presents a resource with the greatest utility to them. In order to overcome inefficiencies that result from the potential of inefficient allocation, the present invention has further endeavored to introduce an efficiency-arbitrage agent that scans the overall body of transactions to identify and remedy inefficient market transactions.