In dynamic circuit switching (wavelength routing) networks, capacity is immediately hard-reserved upon the arrival of a setup message at a node, but it is used at least a round-trip time delay later.
Network planning sets the network structure, capacity, routing policies, and security framework.
But enough of the benefits from better monitoring, routing and improved capacity utilization have flowed to their paychecks to make them quite popular among drivers today.
The algorithms have grown from the initial stage of finding shortest paths with Dijkstra's algorithm to cover more complex routing tasks such as finding protected and unprotected routes and capacity limited routing.
The routing and capacity designs for the meshed logical topologies are optimized by using the discrete event flow optimization (DEFO) algorithm, while the routing and capacity designs for the sparse logical topologies are optimized by using the shortest path optimization and DEFO algorithms presented.
The capacity of routing protocols is constrained by the intra-flow interference introduced by adjacent nodes on the same path, and inter-flow interference generated by nodes from neighboring paths.
The problem includes locating suitable hub facilities having adequate multiplexing capacity, and routing the demand traffic from various clients (end offices) through their hubs, or alternatively, through a special point of presence node, in order to minimize total costs.
For the non-splittable case, they present a maximum bottleneck capacity path routing heuristic.
(2015), they assumed to have two types of trucks, which differ in terms transportation capacity and routing costs per unitary distance.
To address this issue in this paper, a distributed traffic-aware routing scheme with a capacity of adjusting the data transmission rate of nodes is proposed for multi-sink wireless sensor networks that effectively distribute traffic from the source to sink nodes.
