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版本更新 · v2arXiv:2610.09713

Rendezvous under Variable Disorientation:The Algorithmic Power of Fixed Unit Distance

Koichi Wada, Toshimitsu Masuzawa, Yuichi Sudo

原文摘要

We study deterministic Rendezvous of two robots with lights under weak geometric and synchronization assumptions. Our focus is on Variable Disorientation (VD), where each robot may arbitrarily rotate, reflect, and rescale its local coordinate system at every \Look, and on VD+Fixed-Unit-Distance (FUD), where each robot's local unit distance remains fixed. We consider the one-sided visibility models FSTA and FCOM, and schedulers ranging from the energy-restricted RSYNCH and R-RSYNCH to fully asynchronous executions. Under VD, we prove color-independent impossibility results for FSTA under SSYNCH and for FCOM under ASYNCH, and establish sharp two-color boundaries under RSYNCH and R-RSYNCH. Under VD+FUD, we introduce periodic distance classes, which turn multipl icative changes of the physical distance into predictable cyclic phase shifts. This technique yields a two-color self-stabilizing non-$L$-Rendezvous algorithm for both FSTA and FCOM under RSYNCH and R-RSYNCH even with Non-Rigid movement. Under Rigid movement, periodic distance classes further yield an optimal three-color non-quasi-self-stabilizing algorithm for FSTA under SSYNCH, a four-color FSTA algorithm under $M$-atomic ASYNCH, and a four-color FCOM algorithm under CM-atomic ASYNCH. By guarding the latter phase mechanism with two additional colors and replacing its initial swap by passive initialization, we obtain a six-color FCOM algorithm under full ASYNCH, improving the previous twelve-color upper bound by a factor of two. These results show that a fixed local metric can serve as persistent cyclic memory, and clarify how metric stability, one-sided visibility, and scheduler atomicity jointly determine Rendezvous solvability and color complexity.

cs.DC

版本更新 · v2arXiv:2604.04619

Online Graph Exploration under T-Interval Connectivity

Yuichi Sudo, Naoki Kitamura, Masahiro Shibata, Junya Nakamura, Sébastien Tixeuil, Toshimitsu Masuzawa, Koichi Wada

原文摘要

We study deterministic exploration by a single agent in $T$-interval-connected graphs, a standard model of dynamic networks in which, for every time window of length $T$, the intersection of the graphs within the window is connected. The agent does not know the window size $T$, nor the number of nodes $n$ or edges $m$, and must visit all nodes of the graph. We consider two visibility models: in $KT_0$, the agent observes only its current node's identifier and port information; in $KT_1$, it additionally observes the identifiers of its currently available neighbors. We investigate two fundamental questions: the minimum window size that guarantees exploration, and the optimal exploration time under sufficiently large window size. For both models, we show that a window size $T = Ω(m)$ is necessary, and we present deterministic algorithms whose required window size is $O(ξ(n,m)\cdot m + n \log^2 n)$, where $ξ(n,m) = \frac{\ln n}{1 + \ln m - \ln n}$. This window-size bound is tight for a wide range of $m$, in particular when $m = n^{1+Θ(1)}$. Separately, for exploration time, we prove lower bounds of $Ω((m - n + 1)n)$ in the $KT_0$ model and $Ω(m)$ in the $KT_1$ model, even when the dynamic graph is $\infty$-interval-connected (i.e., even when all snapshots share a common spanning tree), and our algorithms match these time bounds up to a polylogarithmic factor. These bounds are also tight when parameterized solely by $n$: $Θ(n^3)$ for $KT_0$ and $Θ(n^2)$ for $KT_1$.

cs.DC