Compressive Sensing Using Target Wake Times for IoT Sensor Networks

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Solution Overview

Problem

IoT sensors in low-power and lossy networks face challenges in scheduling wake times for data reporting due to limited resources and changing environmental conditions, leading to inefficiencies in battery power consumption and potential interference.

Innovation Solution

Implementing a supervisory service that uses Target Wake Time (TWT) messages to dynamically schedule sensor reporting, allowing sensors to conserve energy by sleeping until designated wake times and eliminating the need for pre-programmed schedules, enabling flexible and adaptive compressive sensing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Use of energy by moving object

If sensors remain asleep to conserve battery power, then energy consumption is reduced, but scheduling wake times and reporting becomes challenging

Engineering Contradiction:

Improvebattery power consumptionVSAvoidscheduling complexity

Core Design Contradiction:

Use of energy by moving objectVSDevice complexity

Solution Approach 1:

The patent introduces a supervisory service as an intermediary that computes compressive sensing schedules and sends TWT messages to sensors. This mediator handles the complex scheduling logic centrally, freeing individual sensors from needing to store or process schedule information, thus reducing their complexity while enabling energy-efficient sleep-wake cycles

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The supervisory service pre-computes the compressive sensing schedule and sends TWT messages to sensors in advance, telling them when to wake up and report. This preliminary action allows sensors to simply follow pre-determined wake times without needing to make scheduling decisions, reducing their operational complexity

Inventive Principle:

Principle #10Preliminary action

2Ease of operation

If pre-programmed schedules are used, then sensor operation is simplified, but adaptability to changing environmental conditions is reduced

Engineering Contradiction:

Improvesensor operation simplicityVSAvoidenvironmental adaptability

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamic scheduling where the supervisory service can update TWT messages and compressive sensing schedules in response to changing environmental conditions. The system transitions from static pre-programmed schedules to dynamic adaptive scheduling, allowing sensors to adjust their wake times based on current network conditions, traffic patterns, and environmental factors while maintaining operational simplicity through centralized control

Inventive Principle:

Principle #15Dynamics

3Reliability

If all sensors are active continuously, then complete sensor coverage is achieved, but battery power is depleted rapidly

Engineering Contradiction:

Improvesensor coverage completenessVSAvoidbattery power consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The patent applies compressive sensing theory to activate only a subset of sensors at any given time based on computed schedules. Instead of requiring all sensors to be continuously active, the system determines that partial sensor activation is sufficient to reconstruct complete environmental information, thereby maintaining reliable sensor coverage while dramatically reducing overall power consumption across the network

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system implements periodic wake-up cycles for sensors based on TWT messages rather than continuous operation. Sensors alternate between sleep and active states in periodic cycles determined by the compressive sensing schedule, ensuring that sufficient sensors are periodically active to maintain coverage reliability while minimizing cumulative power consumption across the sensor population

Inventive Principle:

Principle #19Periodic action

4Device complexity

If sensors lack resources to store communication schedules, then device complexity is reduced, but scheduling capability is limited

Engineering Contradiction:

Improvesensor memory requirementsVSAvoidscheduling flexibility

Core Design Contradiction:

Device complexityVSAdaptability or versatility

Solution Approach 1:

The supervisory service acts as an external memory and scheduling repository, storing the complete compressive sensing schedules and communicating them to sensors via TWT messages. Sensors with minimal memory resources can still benefit from complex scheduling because the supervisory service maintains the schedule information externally, eliminating the need for sensors to store extensive schedule data while preserving scheduling flexibility

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces the mechanical/memory-based scheduling storage in sensors with a network-based scheduling system. Instead of storing schedules locally in sensor memory, the system uses network communication (TWT messages) to deliver scheduling information dynamically, substituting physical memory resources with network communication capabilities and centralized computation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11057831B2Compressive sensing using target wake times

Publication Date: 2021.07.06 CISCO TECHNOLOGY INC

AI summary

In one embodiment, a supervisory service for a wireless network computes a compressive sensing schedule for a plurality of sensors in the wireless network. The service sends target wake time (TWT) messages to a subset of the plurality of sensors according to the computed compressive sensing schedule. The service receives, in response to the TWT messages, sensor readings from the subset of the plurality of sensors. The service performs compressive sensing on the received sensor readings.