🤖 AI Summary
This study addresses the challenge of dynamically coordinating heterogeneous traffic demands by a single agent in multi-engine analysis platforms. We propose an engine-agnostic traffic orchestration architecture based on a Composite Finite State Machine (CFSM). By modeling the multi-engine state space via Cartesian product and pre-mapping forwarding configurations, the method enables runtime table-lookup scheduling. Furthermore, temporal expiration is introduced as a first-class FSM transition to support declarative traffic decay, while a per-state hierarchical output mechanism is designed to accommodate varying service levels. The proposed architecture scales seamlessly to an arbitrary number of engines without structural refactoring, significantly enhancing both the efficiency and flexibility of traffic orchestration.
📝 Abstract
Modern application-security platforms route live traffic from a single proxy into several independent analysis engines -- behavioral anomaly detection, authentication analysis, resource discovery, access-control inspection, among others. Each engine's appetite for traffic changes on its own schedule, yet the proxy can honor only one forwarding instruction per resource. We present a traffic-orchestration method that models the combined needs of all engines as a single composite finite state machine (FSM) whose state space is the Cartesian product of per-engine states. Every reachable composite state pre-maps to one forwarding configuration, so runtime reduces to a lookup rather than a negotiation. We add two refinements: time-based expiry treated as a first-class FSM transition enabling declarative traffic decay, and per-state multi-tier outputs that let one machine serve every service level. The design is fully declarative, engine-agnostic, and scales to N engines without re-architecture.