Autonomic Agents for Wireless Mesh Network Partitioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless mesh networks (WMNs) face challenges in scaling capacity and reducing latency while maintaining centralized control, especially in large-scale deployments.
Innovation Solution
The implementation of two autonomic agents within wireless devices that perform self-organizing and self-healing operations using local information to manage network partitions, enhancing capacity and connectivity while respecting network constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If centralized control is implemented in WMN to manage network operations, then network coordination and control capability are improved, but control latency and management complexity increase
Solution Approach 1:
The network is divided into multiple partitions, each managed by a partition manager. This segmentation allows distributed decision-making while maintaining centralized coordination benefits, reducing control latency by enabling local autonomy within partitions.
Solution Approach 2:
Partition managers act as intermediaries between individual wireless devices and the central controller. They handle local control decisions and only communicate with the central controller when necessary, reducing overall control latency and bandwidth requirements.
2Area of stationary object
If network scale is increased in WMN to provide broad coverage, then coverage area is improved, but capacity and performance deteriorate
Solution Approach 1:
The large-scale network is segmented into multiple smaller partitions, each with its own manager. This allows the network to maintain broad coverage while preserving capacity within each partition by limiting the number of devices per partition and enabling parallel operation of multiple partitions.
3Reliability
If network density is increased in WMN to improve coverage, then coverage quality is improved, but latency and capacity performance worsen
Solution Approach 1:
Each partition is configured with specific quality parameters (diameter bound, degree bound) that define its local characteristics. This allows the network to maintain high coverage quality within each partition while preventing latency degradation through controlled partition size and topology.
Data Source
AI summary
The systems, devices, and methods provide agents that implement self-organized partitioning with the connectivity recovery through self-healing using local information. A method may include determining, by a wireless device, one or more metrics for each agent and/or for each partition of the one or more other agents using internal and neighboring state information from information with respect to validity and/or a quality of a connection by an evaluating agent of the wireless device to each partition based on an agent type of the evaluating agent. The agent type may include a first agent and a second agent. The method may further include determining, by the first wireless device, one or more agent operations to be deployed by a wireless interface of the first wireless device with respect to the first agent or the second agent, based on the one or more metrics and the agent type.