Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userPhase Changes in the Evolution of the IPv4 and IPv6 AS-Level Internet Topologies
148
0
0.0
(
0
)
Added by
Guoqiang Zhang
Publication date
2010
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
In this paper we investigate the evolution of the IPv4 and IPv6 Internet topologies at the autonomous system (AS) level over a long period of time.We provide abundant empirical evidence that there is a phase transition in the growth trend of the two networks. For the IPv4 network, the phase change occurred in 2001. Before then the networks size grew exponentially, and thereafter it followed a linear growth. Changes are also observed around the same time for the maximum node degree, the average node degree and the average shortest path length. For the IPv6 network, the phase change occurred in late 2006. It is notable that the observed phase transitions in the two networks are different, for example the size of IPv6 network initially grew linearly and then shifted to an exponential growth. Our results show that following decades of rapid expansion up to the beginning of this century, the IPv4 network has now evolved into a mature, steady stage characterised by a relatively slow growth with a stable network structure; whereas the IPv6 network, after a slow startup process, has just taken off to a full speed growth. We also provide insight into the possible impact of IPv6-over-IPv4 tunneling deployment scheme on the evolution of the IPv6 network. The Internet topology generators so far are based on an inexplicit assumption that the evolution of Internet follows non-changing dynamic mechanisms. This assumption, however, is invalidated by our results.Our work reveals insights into the Internet evolution and provides inputs to future AS-Level Internet models.
rate research
Read More
Since January 2011, IPv4 address space has exhausted and IPv6 is taking up the place as successor. Coexistence of IPv4 and IPv6 bears problem of incompatibility, as IPv6 and IPv4 headers are different from each other, thus, cannot interoperate with each other directly. The IPv6 transitioning techniques are still not mature, causing hindrance in the deployment of IPv6 and development of next generation Internet. Until IPv6 completely takes over from IPv4, they will both coexist. For IPv4-IPv6 coexistence, three solutions are possible: a) making every device dual stack, b) translation, c) tunneling. Tunneling stands out as the best possible solution. Among the IPv6 tunneling techniques, this paper evaluates the impact of three recent IPv6 tunneling techniques: 6to4, Teredo, and ISATAP, in cloud virtualization environment. In virtual networks, these protocols were implemented on Microsoft Windows (MS Windows 7 and MS Windows Server 2008) and Linux operating system. Each protocol was implemented on the virtual network. UDP audio streaming, video streaming and ICMP-ping traffic was run. Multiple runs of traffic were routed over the setup for each protocol. The average of the data was taken to generate graphs and final results. The performance of these tunneling techniques has been evaluated on eight parameters, namely: throughput, end to end delay (E2ED), jitter, round trip time (RTT), tunneling overhead, tunnel setup delay, query delay, and auxiliary devices required. This evaluation shows the impact of IPv4-IPv6 coexistence in virtualization environment for cloud computing.
Recently we introduced the rich-club phenomenon as a quantitative metric to characterize the tier structure of the Autonomous Systems level Internet topology (AS graph) and we proposed the Interactive Growth (IG) model, which closely matches the degree distribution and hierarchical structure of the AS graph and compares favourble with other available Internet power-law topology generators. Our research was based on the widely used BGP AS graph obtained from the Oregon BGP routing tables. Researchers argue that Traceroute AS graph, extracted from the traceroute data collected by the CAIDAs active probing tool, Skitter, is more complete and reliable. To be prudent, in this paper we analyze and compare topological structures of Traceroute AS graph and BGP AS graph. Also we compare with two synthetic Internet topologies generated by the IG model and the well-known Barabasi-Albert (BA) model. Result shows that both AS graphs show the rich-club phenomenon and have similar tier structures, which are closely matched by the IG model, however the BA model does not show the rich-club phenomenon at all.
We present the first complete measurement of the Chinese Internet topology at the autonomous systems (AS) level based on traceroute data probed from servers of major ISPs in mainland China. We show that both the Chinese Internet AS graph and the global Internet AS graph can be accurately reproduced by the Positive-Feedback Preference (PFP) model with the same parameters. This result suggests that the Chinese Internet preserves well the topological characteristics of the global Internet. This is the first demonstration of the Internets topological fractality, or self-similarity, performed at the level of topology evolution modeling.
The internet structure is extremely complex. The Positive-Feedback Preference (PFP) model is a recently introduced internet topology generator. The model uses two generic algorithms to replicate the evolution dynamics observed on the internet historic data. The phenomenological model was originally designed to match only two topology properties of the internet, i.e. the rich-club connectivity and the exact form of degree distribution. Whereas numerical evaluation has shown that the PFP model accurately reproduces a large set of other nontrivial characteristics as well. This paper aims to investigate why and how this generative model captures so many diverse properties of the internet. Based on comprehensive simulation results, the paper presents a detailed analysis on the exact origin of each of the topology properties produced by the model. This work reveals how network evolution mechanisms control the obtained topology properties and it also provides insights on correlations between various structural characteristics of complex networks.
The Internet is composed of routing devices connected between them and organized into independent administrative entities: the Autonomous Systems. The existence of different types of Autonomous Systems (like large connectivity providers, Internet Service Providers or universities) together with geographical and economical constraints, turns the Internet into a complex modular and hierarchical network. This organization is reflected in many properties of the Internet topology, like its high degree of clustering and its robustness. In this work, we study the modular structure of the Internet router-level graph in order to assess to what extent the Autonomous Systems satisfy some of the known notions of community structure. We show that the modular structure of the Internet is much richer than what can be captured by the current community detection methods, which are severely affected by resolution limits and by the heterogeneity of the Autonomous Systems. Here we overcome this issue by using a multiresolution detection algorithm combined with a small sample of nodes. We also discuss recent work on community structure in the light of our results.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
