Abstract

Ad-hoc networks are highly dynamic and can be disconnected/partitioned during their operations, particularly in delay-tolerant networks (DTNs) where infrastructure support is not entirely available. Even after several decades of research on DTN routing, there is still a need for routing protocols that operate effectively in network environments where disconnections, delays, and resource scarcity are common. Traditionally, DTN routing protocols use an epidemic routing strategy, where multiple copies of packets get forwarded to increase network reachability. However, these flooding-based strategies are seldom suitable in resource-constrained network settings. Other prominent DTN routing designs use distance vectors (DVs) that summarize global network reachability information based solely on destination nodes. Therefore, DVs have a much lower cardinality than individual network connections/links and provide better scalability potential for routing state information than techniques using link-state information. DV-based protocols also rely less on periodic broadcasts reducing the overall bandwidth demand among nodes. However, traditional DV routing and several studies of its adaptation to mobile ad-hoc network settings assume a connected underlying network. Thus, they fail to address the fundamental problem of unicast or nearly unicast forwarding of packets over a partitioned network. This thesis aims to address this problem by designing a disconnection tolerant routing protocol, Binary State Distance Vector Routing (BSDVR), which introduces binary state information for DV entries to compute unicast paths even when the network has become partitioned. We compare BSDVR against the traditional DV routing (TDVR) in a controlled network setting. We also compare BSDVR against other well-known ad-hoc routing protocols using packet simulations. Our experiments confirm that BSDVR generates more control overhead during link failures that do not cause partitions. However, in partition-causing link failures, BSDVR's control overhead is less than TDVR's by an order of magnitude, leading to much better convergence times.

Notes

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Graduation Date

2021

Semester

Fall

Advisor

Yuksel, Murat

Degree

Master of Science (M.S.)

College

College of Engineering and Computer Science

Department

Computer Science

Degree Program

Computer Science

Identifier

CFE0009296; DP0026900

URL

https://purls.library.ucf.edu/go/DP0026900

Language

English

Release Date

June 2023

Length of Campus-only Access

1 year

Access Status

Masters Thesis (Open Access)

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