Walker Agents for Distributed Network Query in LLNs
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Solution Overview
Problem
Low Power and Lossy Networks (LLNs) face challenges such as limited memory, processing power, and bandwidth, making it difficult to perform computationally-intensive tasks and maintain state information for multiple devices, while traditional computing approaches require known topology and metrics for optimization.
Innovation Solution
The introduction of 'walker agents' that load and execute on devices, update state information, and propagate to other devices for execution, allowing computations to 'hop' across the network, thereby offloading complex tasks without the need for centralized servers and reducing bandwidth consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional centralized computing approaches are used to query distributed network devices, then complete information can be retrieved, but bandwidth consumption increases and network congestion occurs due to continuous reporting to a central database
Solution Approach 1:
Instead of having data continuously reported to a central database, the patent inverts the approach by sending query walker agents to distributed devices that execute queries locally and return only relevant results, thereby reducing bandwidth consumption while maintaining information retrieval completeness
Solution Approach 2:
The patent extracts the querying function from a centralized database model and distributes it across multiple devices through walker agents, allowing queries to be executed locally at the edge of the network rather than funneling all data to a central point
2Productivity
If computationally-intensive tasks are performed on LLN devices with limited resources, then local processing capability is improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent implements dynamic task distribution where walker agents carry computational tasks through the network and execute them on devices that currently have available resources, allowing processing capability to adapt dynamically rather than requiring static high-capacity devices
Solution Approach 2:
The walker agent serves multiple functions: it carries query information, executes computational tasks, collects results, and propagates through the network, thereby providing enhanced processing capability without adding dedicated specialized hardware
3Productivity
If topology and metric information are stored locally on LLN devices for routing optimization, then routing efficiency is improved, but memory capacity requirements increase beyond device limitations
Solution Approach 1:
The patent introduces walker agents as intermediaries that carry topology and metric information through the network rather than storing it locally on resource-constrained devices, enabling routing optimization without exceeding device memory capacity
Data Source
AI summary
In one embodiment, a device in a network receives a query walker agent configured to query information from a distributed set of devices in the network based on a query. The device executes the query walker agent to identify the query. The device updates state information of the executing query walker agent using local information from the device and based on the query. The device unloads the executing query walker agent after updating the state information. The device propagates the query walker agent with the updated state information to one or more of the distributed set of devices in the network, when the updated state information does not fully answer the query.