Exact(7)
In our work, we are using LP to maximize the user rates with capacity and fairness constraints with a selected path.
One of the major limitation of ODSBR is that it can only work with a source routing protocol, such as DSR, where the source knows all the intermediate nodes on a selected path.
This paper proposes a reinforcement learning based message transfer model for transferring news report messages through a selected path in a trusted provenance network with the objective of maximizing the reward values based on trust or importance based and network congestion or utility based cost measures.
This paper described a reinforcement learning based message transfer model for transferring news report messages through a selected path in a trusted provenance network with the objective of maximizing the reward values based on trust or importance based and network congestion or utility based cost measures.
A selected path, with other paths juxtaposed, is depicted in Figure 4.
A selected path presents the name of each node, its identification domain, and the order in the path.
Similar(53)
As a result, the new path c which is the combination between path b and path k could route to destination and is better than selected path a, but which is conflict with the assumption we have provided above. .
The loss threshold of ODSBR is considered to be log n faults, where n is the hop-count of the selected path, whereas a threshold value of 0.51 is considered for WARP.
Fig. 5 A collinear n nodes with partitioning selected path.
If the selected path fails, the source node receives a RERR; in this case, a path is selected from the highest available class.
On the other hand, as shown on line 3 of the algorithm, we randomly select a path (simply using graph exploration) of length (2delta ) at each iteration and filter out all vertices that could be evenly covered in (delta )-hops from the middle vertex of this selected path, until all vertices from G are covered.
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