Timely Proactive Cache Updating in Poisson Networks
Zheng Chen · 2023
We study information freshness in a cache updating system with randomly located caches whose distribution follows a Poisson point process. A finite set of content items/files are maintained at a central server, updated randomly over time, and requested randomly by users in the network. To provide timely service for content requests, the central server proactively delivers new file versions to the distributed caches, subject to some constraint on the updating costs per unit area. When a user requests a file, it retrieves the most up-to-date version from the set of caches located within its searching range. Considering the randomness in content requests, the number of caches and cache updating decisions, we derive the distribution of user-perceived version age of files and propose a spatial information freshness metric. Our results illustrate the interplay between cache density and file updating probabilities in terms of their impact on information freshness in large random network.