pathsRam

PathsRam is a term used to describe an in-memory cache and data structure designed to store precomputed or frequently requested paths in graph-based computations. It aims to speed up repeated path queries by reusing stored results instead of recomputing routes from scratch with a pathfinding algorithm such as Dijkstra or A*.

Data model: Each entry in PathsRam associates a path query with a path record. A query is typically defined by a source node and a destination node, plus optional constraints such as maximum cost, time windows, or allowed edge types. A path record stores the node sequence, edge sequence, total cost, and metadata such as generation timestamp and a validity flag.

Cache management and invalidation: PathsRam uses a finite capacity and an eviction policy, commonly least-recently-used (LRU) or time-to-live (TTL). Invalidation occurs when the underlying graph changes (edge insertions, deletions, or weight updates) or when a path record becomes stale due to better alternative routes. Some implementations support incremental invalidation to preserve consistency.

Generation flow: On a query, the system checks PathsRam. A cache hit yields the stored path; a miss triggers a path computation via the chosen algorithm, after which the result may be stored in PathsRam according to policy. For dynamic graphs, the cache is updated or purged as changes occur.

Applications: PathsRam is applicable in robotics navigation, geographic information systems, network routing optimization, and game AI, where many queries reuse similar routes and the graph remains relatively stable.

Limitations: The approach consumes memory, risks serving outdated routes, and may offer diminishing returns for highly dynamic graphs or highly diverse query patterns. See also pathfinding, caching, and experience graphs.