Information Freshness in Dynamic Gossip Networks
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866908337796284416 |
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| author | Srivastava, Arunabh Maranzatto, Thomas Jacob Ulukus, Sennur |
| author_facet | Srivastava, Arunabh Maranzatto, Thomas Jacob Ulukus, Sennur |
| contents | We consider a source that shares updates with a network of $n$ gossiping nodes. The network's topology switches between two arbitrary topologies, with switching governed by a two-state continuous time Markov chain (CTMC) process. Information freshness is well-understood for static networks. This work evaluates the impact of time-varying connections on information freshness. In order to quantify the freshness of information, we use the version age of information metric. If the two networks have static long-term average version ages of $f_1(n)$ and $f_2(n)$ with $f_1(n) \ll f_2(n)$, then the version age of the varying-topologies network is related to $f_1(n)$, $f_2(n)$, and the transition rates in the CTMC. If the transition rates in the CTMC are faster than $f_1(n)$, the average version age of the varying-topologies network is $f_1(n)$. Further, we observe that the behavior of a vanishingly small fraction of nodes can severely impact the long-term average version age of a network in a negative way. This motivates the definition of a typical set of nodes in the network. We evaluate the impact of fast and slow CTMC transition rates on the typical set of nodes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_18504 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Information Freshness in Dynamic Gossip Networks Srivastava, Arunabh Maranzatto, Thomas Jacob Ulukus, Sennur Information Theory Networking and Internet Architecture Social and Information Networks Signal Processing We consider a source that shares updates with a network of $n$ gossiping nodes. The network's topology switches between two arbitrary topologies, with switching governed by a two-state continuous time Markov chain (CTMC) process. Information freshness is well-understood for static networks. This work evaluates the impact of time-varying connections on information freshness. In order to quantify the freshness of information, we use the version age of information metric. If the two networks have static long-term average version ages of $f_1(n)$ and $f_2(n)$ with $f_1(n) \ll f_2(n)$, then the version age of the varying-topologies network is related to $f_1(n)$, $f_2(n)$, and the transition rates in the CTMC. If the transition rates in the CTMC are faster than $f_1(n)$, the average version age of the varying-topologies network is $f_1(n)$. Further, we observe that the behavior of a vanishingly small fraction of nodes can severely impact the long-term average version age of a network in a negative way. This motivates the definition of a typical set of nodes in the network. We evaluate the impact of fast and slow CTMC transition rates on the typical set of nodes. |
| title | Information Freshness in Dynamic Gossip Networks |
| topic | Information Theory Networking and Internet Architecture Social and Information Networks Signal Processing |
| url | https://arxiv.org/abs/2504.18504 |