On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
On inferring autonomous system relationships in the internet
IEEE/ACM Transactions on Networking (TON)
Modeling Autonomous-System Relationships
Proceedings of the 20th Workshop on Principles of Advanced and Distributed Simulation
Systematic topology analysis and generation using degree correlations
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
AS relationships: inference and validation
ACM SIGCOMM Computer Communication Review
Computing the types of the relationships between autonomous systems
IEEE/ACM Transactions on Networking (TON)
Orbis: rescaling degree correlations to generate annotated internet topologies
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Inferring AS relationships: dead end or lively beginning?
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
The impact of network topology on the performance of MAP selection algorithms
Computer Networks: The International Journal of Computer and Telecommunications Networking
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The contractual relationships between autonomous systems (AS) cannot be ignored in the research of large-scale communication protocols and architectures. It has been widely recognized that disregarding policy relationships leads to unrealistic routing paths in simulated communication networks and thus to inaccurate conclusions about the investigated problem. Current AS-level topology generators either completely overlook the relationships or make the annotation process inherent in topology generation. We propose a novel algorithm for annotating random graphs. Our approach differs from previous studies in focusing on the annotation process rather than on the topology generation, which enables reuse of the state-of-the-art topology generators. We identify five properties of viable annotations and formulate the problem as a type-of-relationship problem in random graphs (TRR) by analogy with the related problem of inferring AS relationships from measured routing data. We propose an annotation algorithm for solving the TRR problem by taking advantage of the stochastic properties found in the inferred annotations provided by the cooperative association for internet data analysis (CAIDA). The evaluation provides the evidence of high resemblance of our annotations to the measured ones.