Beyond Storage: State as a Runtime Control Problem in Parallel and Distributed Systems
Distributed, Parallel, and Cluster ComputingDatabases
Summary
The authors looked at how shared state affects the behavior of different computer systems that handle ongoing data and learning. They found that previous work often studied pieces like access control or memory separately, so they organized the research into three connected areas involving how state is accessed, executed, and evolves over time. They created a framework to compare different approaches using ideas like state objects and evaluation boundaries. Their work highlights common problems and suggests treating state management as a runtime control challenge.
Authors
Shuhao Zhang, Haoran Peng, Chun Ho Ma, Yancan Mao, Yufeng Du, Shifeng Liu, Ruijie Qiu, Xiaofei Liao, Hai Jin
Abstract
Shared state increasingly shapes both performance and failure behavior in streaming, serving, retrieval, and continual-learning systems. Existing studies, however, often isolate access control, hardware-aware execution, memory management, and long-horizon updates. The review organizes this literature around three coupled dimensions: state access and scheduling, state-aware execution, and state evolution and reuse. Across these dimensions, the literature is synthesized through a common scaffold: state object, control surface, coupling path, evaluation boundary, and unresolved contract. This comparison identifies recurring anti-patterns and informs a contract-oriented blueprint and disturbance-aware evaluation agenda. Taken together, the evidence characterizes state management as a runtime control problem.