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Our main idea in this paper is to maximize the message delivery probability with the consideration of the group feature in the opportunistic network under the constraints of bandwidth and buffer space.
A node computes its message delivery probability with respect to each of the base station. 5.
The work also highlights the effectiveness of node's attribute at estimating its message delivery probability.
Figure 14 Comparison of message delivery probability by varying the percentage of malicious nodes.
Periodically, each node computes its message delivery probability with respect to each of the destination.
Figure 24 Comparison of message delivery probability of acknowledgement system by varying the number of nodes.
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The experiments shows that ferry based model outperforms geographical based model with 29% improvement in messages delivery probability.
Additionally, when the number of mobile ferries are reduced by 34% compared to gateways that are distributed based on geographical area, the mobile ferries approach still outperform geographical area based approach when it comes to messages delivery probability.
Figure 4 Impact on message delivery when delivery probability is computed using the following.(A) Number of messages forwarded, (B) one hop away factor and (C) community attribute.
If the value of this attribute is close to 1, a node is capable of delivering a message and its delivery probability is also high.
This helps to suppress spreading of the messages with low delivery probability, which may result in more messages staying in the buffer and the congestion.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com