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When applied in a commercial deployment, DHT-based P2P protocols face a dilemma: although most real-world participants are so unstable that the maintenance overhead is prohibitively high, they must be effectively utilized due to the lack of stable participants. Thus, determining how to leverage unstable nodes to enhance system scalability and then maximize stability in high-churn scenarios becomes a substantial problem. This paper focuses on this topic, and our main findings are two folds: 1) we propose a homogeneous grouping scheme for scalability enhancement. Besides extending system storage capacity by admitting all nodes, it clusters homogeneous nodes together, deploys the inter- and intra-group connections distinctively, and tunes the number of groups, which aims to facilitate search efficiency; 2) we further look into how to maximize stability under this scheme, which is formulated as the problem Maximum Stability of Grouping. It not only proves to be NP-hard, but also infeasible; therefore, we propose an approximated grouping approach and reduce it to an optimization problem that proves to be feasible. Simulation results exhibit that our grouping strategy effectively captures the stability-scalability tradeoff. Based on our proposed measurement metrics, it doubles the storage capacity of so-called GiantOnly strategy by incurring slightly more churn and search latency, and is about four times as stable as Chord with equal capacity and mild improvement in search efficiency.