Self-Organizing Task Coordination for Ad-Hoc IoT Networks
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Solution Overview
Problem
Distributed IoT devices in ad-hoc networks face challenges in self-organization due to limited resources and lack of infrastructure support, making effective coordination of diverse devices difficult to achieve.
Innovation Solution
A consensus-based coordination infrastructure is established using IoT nodes, with a task assignment approach that allows self-organization by enabling node discovery, capability advertisement, and reliable service publishing, leveraging protocols like Raft for fault-tolerance and resource-awareness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If distributed IoT devices form an ad-hoc network without infrastructure support, then device autonomy and flexibility are improved, but coordination reliability and task execution reliability deteriorate
Solution Approach 1:
The patent introduces a consensus protocol as an intermediary mechanism that enables reliable coordination among distributed IoT devices without requiring external infrastructure. The consensus protocol acts as a mediator that allows nodes to agree on task assignments and coordinate actions reliably, resolving the contradiction between infrastructure-less autonomy and coordination reliability.
Solution Approach 2:
The system implements feedback mechanisms where nodes advertise their capabilities and receive task assignments based on current system state. The consensus protocol continuously monitors and adjusts task assignments based on node availability and capability changes, ensuring reliable coordination while maintaining device autonomy through self-organizing behavior.
2Adaptability or versatility
If diverse IoT devices with different capabilities are coordinated in an ad-hoc network, then system versatility and functionality are improved, but coordination complexity and device complexity increase
Solution Approach 1:
The patent applies local quality by allowing each IoT device to advertise and utilize its own specific capabilities rather than requiring uniform device characteristics. The task assignment system matches tasks to nodes based on their local capabilities, enabling diverse functionality while keeping each node's coordination logic simple and capability-specific.
Solution Approach 2:
The system dynamically changes parameters such as task assignments, node roles, and capability advertisements based on current system conditions. This allows the network to adapt to diverse device capabilities and changing environments, achieving high functionality while maintaining manageable coordination complexity through parameter-based flexibility.
3Quantity of substance
If resource-constrained IoT devices are used in the network, then deployment cost and accessibility are improved, but task execution capability and processing power deteriorate
Solution Approach 1:
The patent segments complex tasks into smaller sub-tasks that can be distributed across multiple resource-constrained IoT devices. Each device executes only the portion of the task it is capable of handling, while the consensus protocol coordinates the overall task completion. This allows the system to achieve substantial processing capability through collective action of many low-power devices.
Solution Approach 2:
The system merges the computational capabilities of multiple resource-constrained devices to achieve task execution capability that exceeds individual device limits. By combining resources and coordinating through consensus, the network accomplishes tasks that would be impossible for single constrained devices, maintaining both accessibility and functional capability.
Data Source
AI summary
Processing nodes in a distributed ad-hoc computing environment are discovered, wherein each processing node is configured to discover other processing nodes. A set of candidate processing nodes is selected from the discovered processing nodes. Selection is based on each discovered processing node advertising its own capabilities to other processing nodes, and processing nodes are selected as candidates based on their advertised capabilities. A subset of processing nodes is formed from the set of candidate processing nodes. The subset of processing nodes forms a self-organized task coordination ensemble wherein each processing node in the task coordination ensemble executes the same consensus protocol. By way of example, the distributed ad-hoc computing environment comprises an IoT network and the processing nodes are IoT devices.