Traffic Divergence Theory: An Analysis Formalism for Dynamic Networks
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911827479232512 |
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| author | Macktoobian, Matin Shu, Zhan Zhao, Qing |
| author_facet | Macktoobian, Matin Shu, Zhan Zhao, Qing |
| contents | Traffic dynamics is universally crucial in analyzing and designing almost any network. This article introduces a novel theoretical approach to analyzing network traffic dynamics. This theory's machinery is based on the notion of traffic divergence, which captures the flow (im)balance of network nodes and links. It features various analytical probes to investigate both spatial and temporal traffic dynamics. In particular, the maximal traffic distribution in a network can be characterized by spatial traffic divergence rate, which reveals the relative difference among node traffic divergence. To illustrate the usefulness, we apply the theory to two network-driven problems: throughput estimation of data center networks and power-optimized communication planning for robot networks, and show the merits of the proposed theory through simulations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_03066 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Traffic Divergence Theory: An Analysis Formalism for Dynamic Networks Macktoobian, Matin Shu, Zhan Zhao, Qing Multiagent Systems Networking and Internet Architecture Dynamical Systems Traffic dynamics is universally crucial in analyzing and designing almost any network. This article introduces a novel theoretical approach to analyzing network traffic dynamics. This theory's machinery is based on the notion of traffic divergence, which captures the flow (im)balance of network nodes and links. It features various analytical probes to investigate both spatial and temporal traffic dynamics. In particular, the maximal traffic distribution in a network can be characterized by spatial traffic divergence rate, which reveals the relative difference among node traffic divergence. To illustrate the usefulness, we apply the theory to two network-driven problems: throughput estimation of data center networks and power-optimized communication planning for robot networks, and show the merits of the proposed theory through simulations. |
| title | Traffic Divergence Theory: An Analysis Formalism for Dynamic Networks |
| topic | Multiagent Systems Networking and Internet Architecture Dynamical Systems |
| url | https://arxiv.org/abs/2404.03066 |