A mobile agent and message ferry mechanism based routing for delay tolerant network
Delay Tolerant Network (DTN) is a class of networks characterized by long delays, frequent disconnections and partitioning of communication paths between network nodes. Due to the frequent disconnection and network partitioning, the overall performance of the network will be deteriorated sharply. Th...
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my.uum.etd.73782021-08-09T03:39:26Z https://etd.uum.edu.my/7378/ A mobile agent and message ferry mechanism based routing for delay tolerant network Ahmed, Kawakib Khadyair TK5101-6720 Telecommunication Delay Tolerant Network (DTN) is a class of networks characterized by long delays, frequent disconnections and partitioning of communication paths between network nodes. Due to the frequent disconnection and network partitioning, the overall performance of the network will be deteriorated sharply. The problem is how to make the network fairly connected to optimize data routing and enhance the performance of a network. The aim of this study is to improve the performance of DTN by minimizing end-to-end delivery time and increasing message delivery ratio. Therefore, this research tackles the problem of intermittent connectivity and network partitioning by introducing Agents and Ferry Mechanism based Routing (AFMR). The AFMR comprises of two stages by applying two schemes: mobile agents and ferry mechanism. The agents' scheme is proposed to deal with intermittent connectivity and network partitioning by collecting the basic information about network connection such as signal strength, nodes position in the network and distance to the destination nodes to minimize end-to-end delivery time. The second stage is to increase the message delivery ratio by moving the nodes towards the path with available network connectivity based on agents' feedback. The AFMR is evaluated through simulations and the results are compared with those of Epidemic, PRoPHET and Message Ferry (MF). The findings demonstrate that AFMR is superior to all three, with respect to the average end-to-end delivery time, message delivery ratio, network load and message drop ratio, which are regarded as extremely important metrics for the evaluation of DTN routing protocols. The AFMR achieves improved network performance in terms of end-to-end delivery time (56.3%); enhanced message delivery ratio (60.0%); mitigation of message drop (63.5%) and reduced network load (26.1 %). The contributions of this thesis are to enhance the performance of DTN by significantly overcoming the intermittent connectivity and network partitioning problems in the network. 2018 Thesis NonPeerReviewed text en https://etd.uum.edu.my/7378/1/Depositpermission_s94434.pdf text en https://etd.uum.edu.my/7378/2/s94434_01.pdf text en https://etd.uum.edu.my/7378/3/s94434_02.pdf Ahmed, Kawakib Khadyair (2018) A mobile agent and message ferry mechanism based routing for delay tolerant network. PhD. thesis, Universiti Utara Malaysia. |
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TK5101-6720 Telecommunication Ahmed, Kawakib Khadyair A mobile agent and message ferry mechanism based routing for delay tolerant network |
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Delay Tolerant Network (DTN) is a class of networks characterized by long delays, frequent disconnections and partitioning of communication paths between network nodes. Due to the frequent disconnection and network partitioning, the overall performance of the network will be deteriorated sharply. The problem is how to make the network fairly connected to optimize data routing and enhance the performance of a network. The aim of this study is to improve the performance of DTN by minimizing end-to-end delivery time and increasing message delivery ratio. Therefore, this research tackles the problem of intermittent connectivity and network partitioning by introducing Agents and Ferry Mechanism based Routing (AFMR). The AFMR comprises of two stages by applying two schemes: mobile agents and ferry mechanism. The agents' scheme is proposed to deal with intermittent connectivity and network partitioning by collecting the basic information about network connection such as signal strength, nodes position in the network and distance to the destination nodes to minimize end-to-end delivery time. The second stage is to increase the message delivery ratio by moving the nodes towards the path with available network connectivity based on agents' feedback. The AFMR is evaluated through simulations and the results are compared with those of Epidemic, PRoPHET and Message Ferry (MF). The findings demonstrate that AFMR is superior to all three, with respect to the average end-to-end delivery time, message delivery ratio, network load and message drop ratio, which are regarded as extremely important metrics for the evaluation of DTN routing protocols. The AFMR achieves improved network performance in terms of end-to-end delivery time (56.3%); enhanced message delivery ratio (60.0%); mitigation of message drop (63.5%) and reduced network load (26.1 %). The contributions of this thesis are to enhance the performance of DTN by significantly overcoming the intermittent connectivity and network partitioning problems in the network. |
format |
Thesis |
author |
Ahmed, Kawakib Khadyair |
author_facet |
Ahmed, Kawakib Khadyair |
author_sort |
Ahmed, Kawakib Khadyair |
title |
A mobile agent and message ferry mechanism based routing for delay tolerant network |
title_short |
A mobile agent and message ferry mechanism based routing for delay tolerant network |
title_full |
A mobile agent and message ferry mechanism based routing for delay tolerant network |
title_fullStr |
A mobile agent and message ferry mechanism based routing for delay tolerant network |
title_full_unstemmed |
A mobile agent and message ferry mechanism based routing for delay tolerant network |
title_sort |
mobile agent and message ferry mechanism based routing for delay tolerant network |
publishDate |
2018 |
url |
https://etd.uum.edu.my/7378/1/Depositpermission_s94434.pdf https://etd.uum.edu.my/7378/2/s94434_01.pdf https://etd.uum.edu.my/7378/3/s94434_02.pdf https://etd.uum.edu.my/7378/ |
_version_ |
1707768030127194112 |
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13.18916 |