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Chen and Wu [17] do something similar, relying on simulation to evaluate both a single and a multipath routing protocol of their own design in terms of message compromising probability and routing overhead.
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Compromising probability comparison between the military and commercial networks is shown in Figure 9.
Figure 9 Dynamic compromising probability comparison between the military and commercial networks.
Numerous simulations are executed to draw reliable results concerning the impact of dynamic beliefs in the maliciousness of relays on throughput and compromising probability.
From Figure 9, we can see that the compromising probability of the military network is smaller than that of the commercial network.
In a message, the probability of a particular symbol (represented by "x") turning up is denoted by p(x).
We showed that there is an inherent trade-off between energy consumption and message delivery performance (defined as the message capture probability).
We proposed an optimal sleep/wake scheduling algorithm, which satisfies a given message capture probability threshold with minimum energy consumption.
Figure 23 Comparison of message delivery probability of message delivery-based reputation system by varying the number of nodes.
Message delivery probability is defined as the number of delivered messages to the destinations to the number of created messages by source nodes.
Unlike the probability of forwarding a message by a node, as used in [25], in this paper, we discuss the message delivery probability of node.
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