Network-Distributed Agent Coordination Without Central Servers

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Solution Overview

Problem

Existing surveillance and autonomous driving systems face challenges with limited hardware capacity and bandwidth, especially on mobile devices, leading to difficulties in processing large amounts of image data in real-time, particularly when multiple agents or objects need recognition.

Innovation Solution

A decentralized network-distributed agent system where autonomous agents, such as drones and vehicles, cooperate to solve real-world tasks without a central server, using swarm intelligence and iterative task adaptation, with agents identifying and communicating with each other to process and share subtasks.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If a central server is used to coordinate agents and process data, then task coordination and data processing are centralized, but the system becomes vulnerable to attacks and errors, reducing reliability

Engineering Contradiction:
Improvesystem reliabilityVSAvoidcentralized architecture complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the centralized server architecture into distributed autonomous agents. Each agent independently performs task coordination and data processing functions that were previously centralized, eliminating the single point of failure. The agents communicate peer-to-peer through imaging sensors, distributing the system's intelligence and improving reliability against attacks and errors.

Inventive Principle:
Principle #1Segmentation

2Measurement precision

If image data from multiple agents is transmitted to a remote server for processing, then comprehensive data analysis is achieved, but bandwidth requirements increase and real-time processing becomes difficult

Engineering Contradiction:
Improvedata analysis accuracyVSAvoiddata transmission volume
Core Design Contradiction:
Measurement precisionVSQuantity of substance

Solution Approach 1:

The patent extracts the data processing function from the remote server and implements it locally within each autonomous agent. Each agent processes its own captured image data and selectively transmits only relevant information to other agents, dramatically reducing the total data transmission volume while maintaining comprehensive analysis through distributed processing.

Inventive Principle:
Principle #2Taking out (Extraction)

Solution Approach 2:

The patent transitions from a single-dimension centralized processing model to a multi-dimensional distributed processing architecture. Multiple agents simultaneously process data in parallel across the network, enabling comprehensive analysis without concentrating all data transmission through a single bottleneck, thus reducing overall bandwidth requirements.

Inventive Principle:
Principle #17Another dimension (Dimensionality change)

3Productivity

If extensive hardware capacity is provided for real-time image processing, then processing speed and accuracy improve, but device cost and complexity increase

Engineering Contradiction:
Improvereal-time processing speedVSAvoidhardware capacity requirements
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent merges the processing capabilities of multiple agents through networked collaboration. Instead of requiring each individual agent to have extensive hardware capacity, the system combines the computational resources of multiple agents to achieve real-time processing speeds and accuracy, reducing the hardware burden on each individual device.

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentEP4629076A1Network-distributed agent system for cooperative problem solving
Publication Date: 2025.10.08 KIESSIG RENE
  • EP4629076A1 patent drawingFigure 1
  • EP4629076A1 patent drawingFigure 2
  • EP4629076A1 patent drawingFigure 3

AI summary

The proposed invention creates a network-distributed agent system for cooperative problem-solving, wherein individual agents, which may be physical hardware components, cooperatively accomplish a common task. The agents can be, for example, drones, robots, and/or autonomous vehicles. These manage themselves in a decentralized and autonomous manner and, via an interface unit, are assigned a task which they complete cooperatively in individual steps. The proposed method is iterative; after assessing sub-steps, the task is adapted such that a final result is achieved after several iterations. The individual agents are able to interact and communicate with each other autonomously. No central server unit is necessary; instead, the present invention utilizes so-called swarm intelligence.For example, some of the agents can be equipped with imaging sensors, which then monitor the work steps and identify and contact potentially collaborating agents. The present invention is also directed to a correspondingly configured system arrangement for carrying out the method, as well as to a computer program product with control commands that implement the proposed method or operate the proposed system arrangement.