Device Shadowing Service Aggregated Group State Calculation
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Solution Overview
Problem
Existing IoT systems face challenges in efficiently managing and aggregating states of networked devices due to intermittent connectivity, bandwidth limitations, and computing capacity constraints, which hinder real-time monitoring and control of device states across large networks.
Innovation Solution
The implementation of a device shadowing service that manages device representations, allowing for the calculation of aggregated group states by querying last known device states from representations rather than directly from devices, thereby reducing query time and improving data availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If device states are queried directly from devices in real-time, then data accuracy is improved, but query time increases and devices with intermittent connectivity cannot be monitored
Solution Approach 1:
The system performs preliminary actions by maintaining device representations that store the last known state of each device. These representations are updated whenever devices report their state, so when queries are made, the most recent available data is already prepared and stored, eliminating the need for real-time device communication.
Solution Approach 2:
Device representations act as intermediaries between the query system and the actual devices. Instead of querying devices directly, the system queries these intermediary representations that hold cached state information. This mediator layer allows queries to be answered quickly even when devices are offline, while still maintaining data accuracy by using the most recent known state.
2Loss of information
If device states are queried from all devices in a large network, then complete state aggregation is achieved, but bandwidth consumption and computing capacity requirements increase
Solution Approach 1:
The system extracts only the essential state information from devices and stores it in device representations. When aggregation is needed, only the aggregated data from representations is retrieved rather than querying every device individually. This extraction approach maintains complete state aggregation while minimizing bandwidth usage by eliminating redundant data transmission.
Solution Approach 2:
The system creates copies of device state information in the form of device representations. These copies are maintained on the server side and can be queried without involving the actual devices. The copies contain all necessary state information for aggregation purposes, allowing complete state monitoring without the bandwidth overhead of continuous direct device communication.
3Speed
If device representations are maintained for all devices, then query speed is improved, but system complexity and memory requirements increase
Solution Approach 1:
The system segments device information into structured device representations that contain only relevant state attributes. Each representation is a simplified data structure holding specific state information rather than complete device configurations. This segmentation enables fast queries by organizing data in an easily accessible format while keeping each individual representation simple and lightweight.
Data Source
AI summary
A technology is described for operating a device shadowing service that calculates an aggregated group state for a group of device representations. An example method may include receiving device states for devices represented using a group of device representations, where the devices connect over a network to a device shadowing service configured to manage the device states. In response to an event, device representations included in the group of device representations may be identified. Device states indicated by the device representations may be obtained and an aggregated group state for the group of device representations may be calculated using the device states indicated by the device representations.