DrrASidM

DrrASidM is a theoretical framework and software architecture proposed for coordinating decentralized autonomous agents operating in distributed environments such as smart manufacturing, logistics, and unmanned systems. It describes a class of approaches focused on distributed resource allocation, scheduling, and decision-making under uncertainty, with emphasis on resilience and security.

The name is used to denote a family of approaches rather than a single product, highlighting the integration of resource allocation, task scheduling, and collaborative decision making across heterogeneous agents and devices. DrrASidM aims to enable scalable coordination without centralized control while maintaining robust performance in dynamic settings.

Core components commonly described within DrrASidM include a local agent layer that runs on individual devices, a distributed coordination layer implementing consensus or market-based allocation, a policy and constraints layer for governance, and a common information model with standardized interfaces. Communications rely on asynchronous messaging, periodic synchronization, and event streams. The architecture supports fault tolerance through redundancy, state replication, and rollback mechanisms, and it emphasizes security through authentication, authorization, and data integrity checks.

Applications cited for DrrASidM encompass dynamic job routing on manufacturing floors, automated fleet management in logistics, autonomous drone swarms for inspection, and collaborative robotics in complex environments. In each domain, the framework is described as enabling better resource utilization, adaptability, and resilience to disruptions.

Status and reception are largely theoretical or experimental, with prototypes and pilot studies reported in academic literature. Benefits cited include scalability and flexibility, while challenges include communication overhead, interoperability, and the lack of universal standards. See also: multi-agent systems, distributed scheduling, industrial IoT.