Macquarie University
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Delay tolerant based warning message broadcasting system for marine fisheries

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posted on 2022-03-28, 20:10 authored by Md Shahzamal
Wireless communication has been incredibly successful to make life easier. Despite such development, many citizens are still far behind having the benefits of modern communication systems, especially low-income people in developing regions. The marine fishing community of Bangladesh corresponds to such a scenario as it suffers a lot due to lack of a proper warning system that could broadcast warning messages to every fishing boat when there is extreme sea weather. This project's aim is to develop a warning message broadcasting system for the marine fishing boats. To make this system inexpensive and easily accessible by fishermen, the Wi-Fi enabled phones available to the fishermen will be exploited with other wireless communication devices. This report presents the challenges and opportunities to implement this system combining Delay Tolerant Networks (DTN) with Mobile Ad-hoc Networks (MANET). The study has focused to find a suitable broadcasting protocol that will ensure fast propagation of warning messages with high reliability in this wide network environment. We have propsed a lightweight broadcasting protocol and conducted an initial evaluation of the network based on this protocol. We have also developed a new mobility model to simulate fishing boats based networks.


Table of Contents

1. Introduction -- 2. Background and review -- 3. Network modelling -- 4. Mobility modelling for fishing boats -- 5. Broadcast techniques and simulation -- 6. Discussion and future works.


Theoretical thesis. Bibliography: leaves 54-59

Awarding Institution

Macquarie University

Degree Type

Thesis MRes


MRes, Macquarie University, Faculty of Science and Engineering, Department of Computing

Department, Centre or School

Department of Computing

Year of Award


Principal Supervisor

Bernard Mans


Copyright Md Shahzamal. Copyright disclaimer:






1 online resource (vii, 59 leaves) illustrations (some colour), colour maps

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