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The nonexistence of an end-to-end path poses a challenge in adapting traditional routing algorithms to delay-tolerant networks (DTNs). Previous works have covered centralized routing approaches based on deterministic mobility, ferry-based routing with deterministic or semideterministic mobility, flooding-based approaches for networks with general mobility, and probability-based routing for semideterministic mobility models. Unfortunately, none of these methods can guarantee both scalability and delivery. In this paper, we extend the investigation of scalable deterministic routing in DTNs with repetitive mobility based on our previous works. Instead of routing with global contact knowledge, we propose a routing algorithm that routes on contact information compressed by three combined methods. We address the challenge of efficient information aggregation and compression in the time-space domain while maintaining critical information for efficient routing. Then, we extend it to handle a moderate level of uncertainty in contact prediction. Analytical studies and simulation results show that the performance of our proposed routing algorithm, DTN hierarchical routing (DHR), is comparable to that of the optimal time-space Dijkstra algorithm in terms of delay and hop count. At the same time, the per-node storage overhead is substantially reduced and becomes scalable.