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arXiv:2609.09934 · v2

Collision-Free Schedule Acquisition through Slotted ALOHA: Scaling Laws and Fluctuations

Plínio Santini Dester
cs.IT
首次提交 2026-09-09 17:26
版本更新 2026-10-27 20:27
雷达观测 2026-10-29 00:35
arXiv ↗PDF ↗

摘要

Goal-oriented sensing, estimation, and control benefit from prompt, regular access to task-relevant updates. Although 1-persistent age-threshold slotted ALOHA (1-pTSA) can self-organize into a periodic collision-free schedule, its acquisition transient can dominate finite-horizon performance. We propose role-protected counter-threshold slotted ALOHA (RP--CTSA), which separates reservation memory from the age of information (AoI). A scheduled singleton retains its phase after colliding with active contenders, whereas a collision involving multiple scheduled nodes releases them immediately; AoI resets only after a decoded update. The protocol requires individual acknowledgments and a binary RELEASE/HOLD indication, but no centralized phase assignment or identification of colliders. Let $n$ denote the number of nodes and $Γ_n$ the counter threshold. Under inverse-population access scaling, the acquisition dynamics admit an exact pure-death representation. When $Γ_n=n$, the acquisition time is $O(n^2)$; when $Γ_n\sim(1+θ)n$, with $θ>0$, it is $O(n\log n)$. Simulations confirm both regimes and show substantial finite-horizon AoI gains over 1-pTSA while preserving every collision-free schedule.

作者备注：Submitted to Wireless Networks

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v3 · 2026-10-28 11:22 · 最新观测版本

Collision-Free Schedule Acquisition through Slotted ALOHA: Scaling Laws and Fluctuations

Decentralized networks can learn collision-free periodic transmission schedules, but acquisition can consume much of a finite operating horizon. We characterize acquisition in a reservation protocol for a fixed population of $n$ nodes and a period of $Γ_n\ge n$ slots. Initially, each node attempts independently in each slot with probability proportional to $1/n$. A success reserves a slot that the node reuses every $Γ_n$ slots, retaining it after collisions. Nodes use only their own acknowledgments and small local memory. An exact finite-population Markov reduction, independent of the arrangement of reserved slots, characterizes the time until every node has a distinct reservation. As $n\to\infty$, mean acquisition takes $O(n^2)$ slots when $Γ_n=n$ and $O(n\log n)$ slots when $Γ_n\sim(1+θ)n$, for fixed $θ>0$. With a fixed number $Γ_n-n$ of spare slots, the standard deviation of acquisition time has the same asymptotic order as its mean. If that number diverges while $Γ_n/n$ remains bounded, the ratio of standard deviation to mean tends to zero. A diverging sublinear number of spare slots yields $o(n^2)$ mean acquisition while long-run utilization, the fraction $n/Γ_n$ of slots with successful transmissions, tends to one. Simulations validate these laws and compare acquisition and delivered packets per slot with existing access protocols.

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v2 · 2026-10-27 20:27

Collision-Free Schedule Acquisition through Slotted ALOHA: Scaling Laws and Fluctuations

Goal-oriented sensing, estimation, and control benefit from prompt, regular access to task-relevant updates. Although 1-persistent age-threshold slotted ALOHA (1-pTSA) can self-organize into a periodic collision-free schedule, its acquisition transient can dominate finite-horizon performance. We propose role-protected counter-threshold slotted ALOHA (RP--CTSA), which separates reservation memory from the age of information (AoI). A scheduled singleton retains its phase after colliding with active contenders, whereas a collision involving multiple scheduled nodes releases them immediately; AoI resets only after a decoded update. The protocol requires individual acknowledgments and a binary RELEASE/HOLD indication, but no centralized phase assignment or identification of colliders. Let $n$ denote the number of nodes and $Γ_n$ the counter threshold. Under inverse-population access scaling, the acquisition dynamics admit an exact pure-death representation. When $Γ_n=n$, the acquisition time is $O(n^2)$; when $Γ_n\sim(1+θ)n$, with $θ>0$, it is $O(n\log n)$. Simulations confirm both regimes and show substantial finite-horizon AoI gains over 1-pTSA while preserving every collision-free schedule.

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