In environments such as buildings in which access points are densely deployed, those access points influence each other. To provide a frequency channel allocation scheme in such densely populated environments information gathered by the access points are collected. In such a situation, relying on a list of neighboring access points, background noise, communication medium business, the beacon messages received from access points as well as their associated RSSI, may lead to a frequency channel allocation scheme that may not significantly reduce the interference between access points. The invention introduces an activity-based distance computed between at least two access points which represents a time overlap in a use of the communication medium.

A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose seed particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count. During this process, the seed particles grow to the desired size (with their constituent first entities then located at the NG vertices) to complete the agent-to-resource allocation process.

A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose seed particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count. During this process, the seed particles grow to the desired size (with their constituent first entities then located at the NG vertices) to complete the agent-to-resource allocation process.

In environments such as buildings in which access points are densely deployed, those access points influence each other. To provide a frequency channel allocation scheme in such densely populated environments information gathered by the access points are collected. In such a situation, relying on a list of neighboring access points, background noise, communication medium business, the beacon messages received from access points as well as their associated RSSI, may lead to a frequency channel allocation scheme that may not significantly reduce the interference between access points. The invention introduces an activity-based distance computed between at least two access points which represents a time overlap in a use of the communication medium.

A method and an apparatus for organization and detection of homogeneous and heterogeneous swarms of devices and application of swarm intelligence using swarm intelligence framework are provided. The Swarm Intelligence Framework provides a generic platform for realizing solutions involving Swarm Intelligence Technology via flexible container-based Algorithm Plug-in Architecture which is essential to utilize Swarm Intelligence Framework for various scenarios and use cases, including dynamically loading and using the Swarm Detection Algorithm.

A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose seed particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count. During this process, the seed particles grow to the desired size (with their constituent first entities then located at the NG vertices) to complete the agent-to-resource allocation process.

A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose seed particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count. During this process, the seed particles grow to the desired size (with their constituent first entities then located at the NG vertices) to complete the agent-to-resource allocation process.

In using a virtual extensible local area network (VXLAN) for stream processing, a management system allocates resources for a streaming application based on an operator graph of the streaming application. The management system assigns the resources to a group of VXLAN segments based on the operator graph of the streaming application. A first processing element of the streaming application multicasts data on the group of VXLAN segments. A second processing element on a given VXLAN segment of the group of VXLAN segments receives the data. If the second processing element is an intended recipient of the data, then the second processing element processes the data. If the second processing element is not the intended recipient of the data, then the second processing element ignores the data.

A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose seed particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count. During this process, the seed particles grow to the desired size (with their constituent first entities then located at the NG vertices) to complete the agent-to-resource allocation process.

A method to associate a set of first entities to a set of second entities, e.g., computing jobs to processors, agent teams to workspace resources within a physical location, or the like. The NG is seeded using a force directed graph (FDG), whose seed particles represents the agents and their relative interconnectedness. The FDG is first brought into an equilibrium state to define a solution space. A relative coordinate system of the FDG solution space is then translated to a number of vertices represented in the NG, and then an initial seeding of the seed particles in the NG (based on their relative positions in the FDG solution space) is carried out. A search is then performed. During the search, each seed vertex releases its embedded agents to adjacent vertices to enable the agents to search for and achieve a required count. During this process, the seed particles grow to the desired size (with their constituent first entities then located at the NG vertices) to complete the agent-to-resource allocation process.