Abstract: A facility controlling a communication device to create a disconnected ad hoc network and then to rejoin an internetwork is described. The communication device makes a direct or indirect wireless connection with a participant in a network in which the communication device was formerly a participant. In response to making the connection, the communication device: (1) communicates with a registration authority of the network to synchronize a provisional registration authority state established by the first communication device during a period after the communication device was formally a participant in the network and before the connection was made; and (2) communicates with a security authority of the network to synchronize a security authority state established by the communication device during the period.

Abstract: In a first participant in a network—such as an ad hoc wireless network—a facility performs peer regulation of the network. The facility monitors behavior of a second participant in the network that has appointed itself a routing participant for the network. Among the monitored behavior, the facility identifies behavior of the second participant that is inconsistent with its routing participant status. In response to this identifying, the facility sends a message to participants of the network including a third participant indicating that the second participant is no longer a routing participant.

Abstract: Embodiments described are directed to the evaluation of a dynamically changing communication network environment to ensure that individual participant thresholds and network-centric thresholds are maintained and satisfied. A plurality of conditions for multiple dimensions of data are set for each participant in the network and for the network as a whole. The participant and network conditions, along with the participant capabilities, are considered holistically across the entire network to determine if the network and the participants are meeting thresholds for the different dimensions of data. In various embodiments, the thresholds, either at an individual participant level or at the network level, may be augmented with priorities to ensure that higher priorities are satisfied.

Abstract: A facility for operating a first node in a mesh network having other nodes is described. The first node directly receives signals each encoding an identifier of one of the other nodes, at least a portion of the signals also encoding an indication that the node having the identifier has appointed itself a routing node. The facility determines a first value equal to the number of unique node identifiers encoded in signals received during a first period of time, and a second value equal to the number of unique node identifiers encoded by signals received during the first period of time that also encode the indication. The facility determines a routing score for the first node based at least upon the first value and the second value that reflects the first node's suitability as a routing node in the mesh network.

Abstract: Seamless connectivity utilizing multi-domain security by storing a global key on each participant computing devices. When a participant computing device tries to connect to a network, the network sends encryption keys for that network in response to that participant computing device providing the global key and not being blacklisted. The participant computing device can then connect to the network using that network's encryption key. A meta-message container is generated for the message based on a next participant in a route from the transmitting participant to the destination participant. One or more series of one or more line items are generated for the message, with each line item being tagged tag with network information. The line items are encrypted based on the network information. The meta-message container and the encrypted series of line items are then transmitted to the next participant.

Abstract: Embodiments described herein are directed to creating a cognitive heterogeneous ad hoc mesh network via generation and utilization of a participant table. Participant object transmit notification signals to inform other participants objects in line-of-sight of their position and movement. Mobile participants that receive these notification signals update a local version of the participant table. If the receiving mobile participant is responsible for forwarding participant table updates to the sending mobile participant, then the receiving mobile participant includes the received notification signal with the transmission of its next notification signal to propagate the participant table update to a stationary participant. The stationary participant can then transmit participant table updates to other mobile participants. If a stationary participant is not accessible or not functioning, the participants continue to propagate participant table changes when a responsible forwarding participant changes.

Abstract: Embodiments described herein are directed to establishment of a cognitive heterogeneous ad hoc mesh network. Participant objects transmit notification signals to inform other participant objects in line-of-sight of their position and movement. These notification signals are used by each participant to establish an ad hoc mesh network between the recipient and the sender. The participants can also utilize echoes of the notification signals to detect and estimate the position and movement of participant or non-participant objects. Participant objects can share this positional information with one another to refine the estimated position and movement of non-participant objects or to correct errors in participant-reported positioning information. The position of each other participant and non-participant object is updated based on an individualized update rate that dynamically changes based on the distance and velocity of closure between the participant and the other participant or non-participant object.

Abstract: Seamless connectivity utilizing multi-domain security by storing a global key on each participant computing devices. When a participant computing device tries to connect to a network, the network sends encryption keys for that network in response to that participant computing device providing the global key and not being blacklisted. The participant computing device can then connect to the network using that network's encryption key. A meta-message container is generated for the message based on a next participant in a route from the transmitting participant to the destination participant. One or more series of one or more line items are generated for the message, with each line item being tagged tag with network information. The line items are encrypted based on the network information. The meta-message container and the encrypted series of line items are then transmitted to the next participant.

Abstract: Embodiments described herein are directed to tracking objects using a cognitive heterogeneous ad hoc mesh network. A first participant receives a notification signal from a second participant. The first participant determines first positioning information from the notification signal and second positioning information from characteristics of the received signal. If the difference between the first and second positioning information is below a first threshold, then the second participant is within line-of-sight of the first participant. If the difference is above the first threshold and below a second threshold, then the second participant may have a malfunctioning sensor. But if the difference is above the second threshold, then the second participant is not within line-of-sight of the first participant and the received signal was reflected off another object. The positioning information can then be refined or transmitted to other participants.

Abstract: Embodiments described herein are directed to employing an aggregation of participant sensor coverage areas to determine if there are missing coverage areas or unwanted overlapping coverage areas. If there are missing coverage areas, then at least one participant is instructed to modify its sensor coverage area to at least partially cover the missing coverage area. Conversely, if at least one participant has a sensor that is providing unwanted overlap of other sensor coverage areas, then that participant may be instructed to stop using that sensor, utilize that sensor for other data transmission purposes, or modify the coverage area to be non- or less-overlapping.

Abstract: Embodiments described herein are directed to creating a cognitive heterogeneous ad hoc mesh network via generation and utilization of a participant table. Participant object transmit notification signals to inform other participants objects in line-of-sight of their position and movement. Mobile participants that receive these notification signals update a local version of the participant table. If the receiving mobile participant is responsible for forwarding participant table updates to the sending mobile participant, then the receiving mobile participant includes the received notification signal with the transmission of its next notification signal to propagate the participant table update to a stationary participant. The stationary participant can then transmit participant table updates to other mobile participants. If a stationary participant is not accessible or not functioning, the participants continue to propagate participant table changes when a responsible forwarding participant changes.

Abstract: Embodiments described herein are directed to a tracking objects using a cognitive heterogeneous ad hoc mesh network. Participant objects transmit notification signals to inform other participant objects in line-of-sight of their position and movement. The participants also utilize echoes of the notification signals to detect and estimate the position and movement of non-participant objects. Participant objects can then share this positional information with one another to refine the estimated position and movement of non-participant objects. The position of each other participant and non-participant object is updated based on an individualized update rate that dynamically changes based on the distance and velocity of closure between the participant and the other participant or non-participant object.

Abstract: Embodiments described herein are directed to a tracking objects using a cognitive heterogeneous ad hoc mesh network. Participant objects transmit notification signals to inform other participant objects in line-of-sight of their position and movement. The participants also utilize echoes of the notification signals to detect and estimate the position and movement of non-participant objects. Participant objects can then share this positional information with one another to refine the estimated position and movement of non-participant objects. The position of each other participant and non-participant object is updated based on an individualized update rate that dynamically changes based on the distance and velocity of closure between the participant and the other participant or non-participant object.

Abstract: Embodiments described herein are directed to a tracking objects using a cognitive heterogeneous ad hoc mesh network. Participant objects transmit notification signals to inform other participant objects in line-of-sight of their position and movement. The participants also utilize echoes of the notification signals to detect and estimate the position and movement of non-participant objects. Participant objects can then share this positional information with one another to refine the estimated position and movement of non-participant objects. The position of each other participant and non-participant object is updated based on an individualized update rate that dynamically changes based on the distance and velocity of closure between the participant and the other participant or non-participant object.

Abstract: Embodiments described herein are directed to a tracking objects using a cognitive heterogeneous ad hoc mesh network. Participant objects transmit notification signals to inform other participant objects in line-of-sight of their position and movement. The participants also utilize echoes of the notification signals to detect and estimate the position and movement of non-participant objects. Participant objects can then share this positional information with one another to refine the estimated position and movement of non-participant objects. The position of each other participant and non-participant object is updated based on an individualized update rate that dynamically changes based on the distance and velocity of closure between the participant and the other participant or non-participant object.

Abstract: Embodiments described herein are directed to employing an aggregation of participant sensor coverage areas to determine if there are missing coverage areas or unwanted overlapping coverage areas. If there are missing coverage areas, then at least one participant is instructed to modify its sensor coverage area to at least partially cover the missing coverage area. Conversely, if at least one participant has a sensor that is providing unwanted overlap of other sensor coverage areas, then that participant may be instructed to stop using that sensor, utilize that sensor for other data transmission purposes, or modify the coverage area to be non- or less-overlapping.

Abstract: Embodiments described herein are directed to a tracking objects using a cognitive heterogeneous ad hoc mesh network. Participant objects transmit notification signals to inform other participant objects in line-of-sight of their position and movement. The participants also utilize echoes of the notification signals to detect and estimate the position and movement of non-participant objects. Participant objects can then share this positional information with one another to refine the estimated position and movement of non-participant objects. The position of each other participant and non-participant object is updated based on an individualized update rate that dynamically changes based on the distance and velocity of closure between the participant and the other participant or non-participant object.

Abstract: Embodiments described herein are directed to a tracking objects using a cognitive heterogeneous ad hoc mesh network. Participant objects transmit notification signals to inform other participant objects in line-of-sight of their position and movement. The participants also utilize echoes of the notification signals to detect and estimate the position and movement of non-participant objects. Participant objects can then share this positional information with one another to refine the estimated position and movement of non-participant objects. The position of each other participant and non-participant object is updated based on an individualized update rate that dynamically changes based on the distance and velocity of closure between the participant and the other participant or non-participant object.

Abstract: Embodiments described herein are directed to creating a cognitive heterogeneous ad hoc mesh network via generation and utilization of a participant table. Participant object transmit notification signals to inform other participants objects in line-of-sight of their position and movement. Mobile participants that receive these notification signals update a local version of the participant table. If the receiving mobile participant is responsible for forwarding participant table updates to the sending mobile participant, then the receiving mobile participant includes the received notification signal with the transmission of its next notification signal to propagate the participant table update to a stationary participant. The stationary participant can then transmit participant table updates to other mobile participants. If a stationary participant is not accessible or not functioning, the participants continue to propagate participant table changes when a responsible forwarding participant changes.

Abstract: Embodiments described herein are directed to a tracking objects using a cognitive heterogeneous ad hoc mesh network. Participant objects transmit notification signals to inform other participant objects in line-of-sight of their position and movement. The participants also utilize echoes of the notification signals to detect and estimate the position and movement of non-participant objects. Participant objects can then share this positional information with one another to refine the estimated position and movement of non-participant objects. The position of each other participant and non-participant object is updated based on an individualized update rate that dynamically changes based on the distance and velocity of closure between the participant and the other participant or non-participant object.