A conciliation mechanism for self-organizing dynamic small groups

Area of Science:

• Computer Science
• Information Systems
• Artificial Intelligence

Background:

• Internet of Things (IoT) environments involve dynamically self-organizing small groups.
• These groups exhibit distinct behaviors compared to larger collectives.
• Effective group operation necessitates dynamic alignment of member requirements with available resources.

Purpose of the Study:

• To develop an artifact using design science methods for reconciling collective requirements and resources in small, dynamic groups.
• To ensure individual member satisfaction is maintained during the reconciliation process.
• To support dynamic adjustments as group membership evolves.

Main Methods:

• Application of design science methodology to create a novel artifact.
• Modeling member requirements as explicit/implicit objectives.
• Validation through simulation with a manufacturing service group experiencing dynamic membership changes.

Main Results:

• The developed artifact effectively reconciles collective requirements and resources.
• The mechanism maintains member satisfaction amidst dynamic group composition.
• Simulations demonstrate the artifact's capability to handle evolving group needs and resources.

Conclusions:

• The artifact provides a robust solution for managing requirements and resources in dynamic IoT groups.
• It facilitates adaptive self-organization by balancing individual needs with collective goals.
• This approach enhances the operational efficiency and stability of virtual and IoT-based organizations.