Optimizing topology learning in a multihop network
AssigneeMotorola, Inc.
InventorsShyamal Ramachandran, Keith J. Goldberg
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AssigneeMotorola, Inc.
InventorsShyamal Ramachandran, Keith J. Goldberg
Estimating the term…
In a multihop network having a first type of node, a second type of node and a third type of node, techniques are provided for optimizing topology learning in the multihop network which can reduce the amount of control traffic that occurs due to frequent topology changes. For example, each of the nodes can transmit a node identifier and status information to the first type of node. The status information associated with each node can include a node type and a mobility state of the node. The first type of node can store the node identifier and the status information from each of the nodes. The first type of node can reserve or allocate a channel resource to each of the second type of nodes having a mobile state. The channel resource is used by the second type of node for exchanging topology information with the first type of node.
In a multihop network comprising at least one first type of node and a plurality of nodes comprising at least one of a second type of node and a third type of node, a method comprising:
In a multihop network comprising at least one first type of node and a plurality of nodes comprising at least one of a second type of node and a third type of node, a method of operating the second type of node within the multihop network comprising:
In a multihop network comprising at least one first type of node and a plurality of nodes comprising at least one of a second type of node and a third type of node, a method of operating the first type of node within the multihop network comprising:
Dependencies are inferred from the claim text.