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Figure 13 Average Message Transmission Delay DQMAN versus 802.
Figure 8 The message transmission delay changes with the selfishness of the network.
The average message transmission delay is illustrated in Figure 13 and reinforces the previous discussion.
Figure 4 The relationship between the message transmission delay and the number of nodes.
As a result, this algorithm has higher message delivery rate and lower message transmission delay.
And for several other algorithms, the message transmission delay will remain unchanged.
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The system is asynchronous, i.e., relative processor speeds and message transmission delays are unbounded.
The system is not synchronous, i.e., there are no known bounds on message transmission delays and the relative speeds of processes.
However, for that solution, we considered a synchronous model for the system, i.e., there exist known bounds on message transmission delays and processors' speed and, consequently, VCube provides a perfect process failure detection.
We study the question analytically in the model considered in [4] for PBFT, namely a partially synchronous system in which the end-to-end messages transmission delay δ is unknown.
The proposed analytical model computes message latency by determining the message transmission time, blocking delay at each router, multiplexing delay at each network channel, and waiting time in the source before entering the network.
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