The Internet Topology: Illusion and Reality
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Date
2008-12-04
Authors
Advisors
Khaled Harfoush, Committee Chair
Arne A. Nilsson, Committee Member
Carla D. Savage, Committee Member
George N. Rouskas, Committee Member
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Abstract
Research studies targeted at unveiling the Internet topology are essential for understanding the performance of the Internet and its resilience to failures or distributed attacks, and for generating realistic topologies to simulate Internet protocols and applications. An accurate understanding of the complex Internet structure and behavior, while very rewarding, is very challenging and in fact is a source of controversy in the networking research community. Till now, there is a lack of understanding of the Internet complexity
In this thesis, we make the following contributions. First, we propose an efficient tool, AROMA, to unveil Layer-3 maps of the
Internet and use it to reveal ISP maps. AROMA reveals the same number of routers and links as existing tools such as Rocketfuel after sending less than 5.1% of the number of probes used by Rocketfuel, and reveals at least 100% more links and routers than Rocketuel while using the same number of probe packets.
Second, we study the limitations of existing layer-3 tools such as traceroute in unveiling the details of the Internet structure and identify that the power law connectivity observed in the
Internet topology is not an illusion as suggested by some researchers. It is mainly manifested due to the blindness of traceroute to layer-2 devices, and this manifestation will persist independent of the nature of the underlying physical topology.
Third, we provide a realistic Internet topology model, HINT, which captures the Internet structure and features. HINT is based on economical, performance and security constraints that are typically used to construct networks. Matching HINT topologies to known ISP topologies confirms its superiority to existing Internet topology
models.
Description
Keywords
Internet, cycle, power law, network topology
Citation
Degree
PhD
Discipline
Computer Science