Graph sampling for Internet topologies using normalized Laplacian spectral features

Ji, Bo; Shi, Jianmai; Zhang, Wensheng; Xing, Lining

doi:10.1016/j.ins.2018.12.073

Cited by 15 publications

(7 citation statements)

References 29 publications

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“…This section presents the comparison of the realistic AS graphs that are provided by the UCLA dataset [1], including the results obtained by our SICPS generator and those by four other generators, namely, Inet-3.0 [10], ORBIS [14], S-BITE [21], and SInetL [29], which are introduced in Section II.B. Inet-3.0 is a classical Internet-topology generator that considers both the hierarchical structure and degree power-law properties.…”

Section: Resultsmentioning

confidence: 99%

“…Recently, we have designed a model SInetL to sample a given Internet graph using the static-node-classification feature [29]. The model extracts a subgraph using a sampling method of the six types of marked nodes.…”

Section: ) Sinetl Modelmentioning

confidence: 99%

“…In the existing literature [10,14,21,29], comparison of the models was mainly realized through comparison of the AS graphs that were simulated by generators because the purpose of the generators was to simulate AS graphs that contained properties of these models.…”

Section: ) Sinetl Modelmentioning

confidence: 99%

“…Recently, we have partitioned the Internet transit and stub AS nodes into seven categories by analyzing the physical mean of the normalized Laplacian spectral properties [24][25][26][27][28][29]. However, these works only provided a static node classification and have not yet structurally distinguished the core from the periphery.…”

Section: Introductionmentioning

confidence: 99%

“…SICPS, ORBIS, and Inet-3.0 all generate graphs by filling the free degrees; thus, the time complexity of the three generators is (‖ ‖), where ‖ ‖ is the total number of edges. In [29], the time complexity of SInetL was proven to be (‖ ‖ ). For each newly added peripheral node, S-BITE first randomly selects a node that already exists in the network and then connects the peripheral node to the selected node.…”

mentioning

confidence: 99%

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Structural Decomposition Model for the Evolution of AS-Level Internet Topologies

Zhang

2020

IEEE Access

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Modeling Internet graphs at the autonomous-system (AS) level is helpful for recognizing and predicting the development trend of evolving Internet topology from a macro perspective. In contrast to the global statistical models such as the power-law distribution of node degrees, the structural decomposition models can more effectively represent the local connection. In this paper, we propose a structure-based model. Starting with the classification of links among the AS nodes, the proposed model partitions the core and periphery of Internet graphs into 16 atomic-level solid and dotted components. Additionally, the model captures the stable evolving features of these components based on the UCLA dataset that continuously explore Internet graphs over a long historic period from 2001 to 2015. Finally, according to the structure-based model, we design a new Internet-topology generator. Compared with the recently proposed generators, the advantages of our generator are as follows: (1) it accurately captures the structure decomposition property studied in this work, (2) it performs best on three statistical properties of the distance, assortativity coefficient, and maximum degree, and (3) it exhibits the best comprehensive performance in terms of runtime and multiple graph properties.

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Section: Resultsmentioning

confidence: 99%

Section: ) Sinetl Modelmentioning

confidence: 99%

Section: ) Sinetl Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Structural Decomposition Model for the Evolution of AS-Level Internet Topologies

Zhang

2020

IEEE Access

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An improved foraging heuristic considering reduced fog latency

Wang

Luo

Xiong

2020

Int J Communication

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Summary Most often, in centralized distributed computing, users are getting impatient by experiencing the delays in loading the content of the web applications over the internet; it is usually caused by the poor latency management and is becoming a catastrophic situation in availing the services and applications of the centralized‐cloud computing; cloud being a distributed platform, its customers are facing the latencies issues at the various tiers of the cloud. Workloads distributions are occurring concurrently on various virtual cloud platforms. Latency‐oriented applications and services usually in cloud platform are running over various virtual machines and possess the high complexities while interacting and face the difficulties in the consolidations of the various applications containing heterogenetic workloads. In this paper, we study the fog computing and consider that it will be a feasible platform to get rid of the cloud high‐latency issues and to reduce the delay time and workflow across the network. The main purpose is to enhance the latency across the various nodes in a network. The factors like interference, availability, and interaction among various participating nodes with nearer VMware are of importance for reducing the latencies. Reduced latencies will enhance the quality of service parameters, resources, and services availability. Latency can be an important factor for the resource optimization issues in cloud computing. The comparisons with existing technologies greatly show that latency in fog is quite efficient than in the cloud paradigm.

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