PRNGsid

PRNGsid is a concept for a family of pseudorandom number generators that derives its output from a session identifier (SID). The aim is to provide deterministic, reproducible streams of numbers for the same SID while allowing different SIDs to produce distinct sequences. This approach is useful in systems that require session-level isolation or traceability, such as simulations, testing environments, or multi-tenant workflows.

The design generally features a compact internal state that is updated through a mixing core combining bitwise operations and arithmetic. The SID is transformed by an initialization routine to form the initial state, and additional internal counters or counters derived from the SID can be used to generate multiple independent streams from a single SID. The generator outputs a uniform sequence of numbers and can be adapted to produce integers, floating-point values, or other derived formats.

Seeding and usage are central to PRNGsid. A SID is processed by a mixing function to initialize the state, after which the generator produces a sequence that is deterministic for that SID. The same SID will yield identical output across runs given the same implementation, while changing the SID changes the entire stream. Some implementations may support reseeding or deriving multiple streams by varying internal counters or using per-stream offsets.

Security considerations are important. PRNGsid is typically not intended as a cryptographically secure generator, and it may be vulnerable if the internal state is exposed. For cryptographic applications, stronger, vetted CSPRNGs should be used, and PRNGsid should be shielded from entropy depletion and side-channel leakage. Proper use includes protecting the state, avoiding reuse of the same SID in risky contexts, and restricting exposure to untrusted code.

Applications include simulations, reproducible experiments, testing pipelines, and scenarios where session-based seeding provides convenient isolation. Implementations may exist in multiple programming languages, guided by the same high-level principles: deterministic, SID-based seeding, fast state updates, and straightforward interfaces for next, random, or uniform outputs.