Pratham Sood
Director
Joshua M. Capps
Founder, Architect

Deterministic Identity Continuity in 5G RAN

April 13, 2026

Introduction

Distributed systems do not fail cleanly.
They fork.

After a crash, restart, or network partition, systems often produce multiple concurrent instances of the same logical entity — each believing it is correct.

This leads to:

  • split-brain execution
  • duplicate transactions
  • inconsistent system state
  • no clear accountability

As autonomous systems expand into edge environments such as 5G RAN, this problem becomes critical.

This Phase 2 research validation introduced and tested a different approach:

Deterministic Identity Continuity

A system model designed to ensure that a single canonical identity persists across time, regardless of failure, migration, restart, or network disruption.

The Problem

In conventional distributed systems:

  • identity is loosely assigned
  • recovery is non-deterministic
  • duplicate instances are tolerated or resolved heuristically

There is no guarantee that only one valid executor of an identity exists after failure.

Instead, distributed systems typically rely on:

  • leader election
  • quorum consensus
  • eventual consistency

These mechanisms coordinate state.

They do not enforce identity singularity.

The Approach

This research explored a different primitive:

Identity can be:

  • deterministically derived
  • cryptographically verified
  • enforced at execution boundaries

This enables:

One Identity

→ One Valid Executor
→ Across Time

System Model

The system introduced a deterministic identity pipeline:

Identity Anchor

Verification

Execution

At runtime, agents operated across distributed edge nodes while maintaining:

  • a single canonical identity
  • deterministic continuity
  • continuity-safe execution behavior

Identity Model

Each agent was defined using two independent cryptographic anchors.

Canonical Identity (Execution Identity)

A deterministic fingerprint derived from canonical metadata:

SHA-256(canonical(agent_metadata))

This defines:

who the agent is.

Purpose Binding (Intent Integrity)

A cryptographic binding of mission or operational intent:

SHA3-256(mission)

This defines:

what the agent is authorized to do.

Authority (Temporal Validity)

Execution authority operated through a lease-based state model:

ACTIVE → SAFE_MODE → EXPIRED

Execution was permitted only when:

  • identity was valid
  • purpose integrity was valid
  • authority state remained active

Experimental Environment

Validation was conducted within a simulated 5G NR Radio Access Network environment using:

  • ns-3 (≥ 3.30)
  • CTTC-LENA NR module
  • multi-node edge topology
  • dynamic mobility models
  • controlled fault injection

The environment simulated:

  • distributed edge execution
  • mobility events
  • node failure
  • process restart
  • degraded network conditions
  • partition events

Test Scenarios

The system was evaluated under the following conditions:

  • baseline split-brain duplication
  • node crash and recovery
  • agent migration across nodes
  • process restart
  • network partition

Each scenario tested whether canonical identity continuity could persist across lifecycle disruption.

Results

Across all tested lifecycle events:

  • identity was successfully re-verified
  • no identity divergence occurred
  • execution continuity was preserved

Verification Metrics

  • Total verification events: 3
  • Successful verifications: 3
  • Failures: 0
  • Verification latency: ~2–9 ms

Network Conditions During Validation

Identity continuity remained stable under degraded network conditions including:

  • packet loss up to 45%
  • elevated simulated latency
  • distributed node instability

Key Finding

Identity continuity remained invariant even under severe network degradation.

This demonstrated an important architectural separation:

Identity verification is a control-plane property,
not a function of network performance.

Visual Validation

The system generated a full NetAnim simulation replay showing:

  • duplicate agent emergence
  • failure events
  • continuity restoration
  • canonical executor recovery

The replay visually demonstrated the transition from:

  • conflicting execution paths

to:

  • one validated canonical executor

Deterministic Verification Flow

During execution attempts, identity verification occurred deterministically before authority was granted.

Verification flow:

  1. Agent submits execution request
  2. Fingerprint is computed
  3. Purpose hash is validated
  4. Authority lease is checked
  5. Runtime execution is either:
    • ALLOWED
    • DENIED

This ensured only the canonical executor could continue execution.

What This Proves

This Phase 2 validation demonstrated that:

  • identity can remain invariant across failure
  • duplicate execution can be detected deterministically
  • execution authority can be enforced
  • continuity can persist independently of network instability

What This Does Not Claim

This work did not attempt to demonstrate:

  • network performance optimization
  • throughput improvements
  • latency acceleration
  • data-plane optimization

Those are:

data-plane concerns.

This validation focused specifically on:

deterministic identity continuity at the control plane.

Why This Matters

As systems evolve toward:

  • autonomous agents
  • distributed AI execution
  • edge-native compute
  • AI-RAN / 6G environments

the cost of identity ambiguity increases significantly.

Without deterministic identity:

  • there is no authoritative execution path
  • no traceable accountability
  • no deterministic continuity guarantee

Conclusion

Deterministic identity continuity establishes identity as:

a control boundary,

not merely metadata.

This shifts distributed systems from:

identity as a label

to:

identity as an enforced property of execution

Evolution of the Research

This Phase 2 validation established the foundational deterministic identity continuity model within simulated distributed 5G edge environments.

Subsequent ACELOGIC™ infrastructure development expanded these concepts into:

  • Kubernetes-native enforcement
  • admission-time identity verification
  • distributed control-plane governance
  • runtime authority enforcement
  • multi-cluster continuity enforcement

The current ACELOGIC™ infrastructure architecture builds upon the deterministic continuity principles validated in this Phase 2 research environment.

Final Statement

There is no system-level accountability without canonical identity.