IoT Task Distribution Reducing Bandwidth and Latency

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Solution Overview

Problem

In IoT environments, managing task execution is challenging due to bandwidth requirements, latency, privacy, and security concerns when transferring tasks to a Cloud platform, and existing solutions do not effectively address low latency and reduced bandwidth consumption.

Innovation Solution

A method for task execution in IoT environments involves defining a task suite that can be divided among sensor nodes, determining overload conditions, predicting resource requirements, and dynamically assigning tasks to other sensor nodes based on available resources and proximity to field devices, thereby reducing the dependency on edge devices and minimizing bandwidth consumption.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If tasks are transferred to a Cloud platform, then resource requirements are managed, but bandwidth consumption increases and latency occurs

Engineering Contradiction:

Improveresource requirementsVSAvoidbandwidth consumption

Core Design Contradiction:

Quantity of substanceVSLoss of energy

Solution Approach 1:

The system segments the IoT network into multiple layers (sensor nodes, edge devices, cloud platform) and distributes task execution across these segments. Tasks are partitioned and executed at the most appropriate level based on resource availability, reducing the need to transfer all tasks to the cloud and thereby reducing bandwidth consumption.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system enables local task execution at sensor nodes and edge devices based on their specific resource capabilities. By allowing tasks to be executed locally where resources are available, the system reduces the need for constant cloud communication, thereby reducing bandwidth consumption and latency.

Inventive Principle:

Principle #3Local quality

2Quantity of substance

If tasks are transferred to a Cloud platform, then resource requirements are managed, but latency increases

Engineering Contradiction:

Improveresource requirementsVSAvoidlatency

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The system performs preliminary assessment of resource availability at sensor nodes and edge devices before task execution. By pre-evaluating local resource capabilities and making advance decisions about task placement, the system avoids delays associated with cloud communication and enables faster task execution.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Inventive Principle:

Principle #3Local quality

3Loss of energy

If tasks are executed locally at sensor nodes, then bandwidth consumption is reduced, but resource overload may occur

Engineering Contradiction:

Improvebandwidth consumptionVSAvoidresource overload

Core Design Contradiction:

Loss of energyVSReliability

Solution Approach 1:

The system continuously monitors resource availability at sensor nodes and edge devices and uses this feedback to dynamically adjust task placement decisions. When local resources are sufficient, tasks are executed locally; when resources are overwhelmed, tasks are redirected to other nodes or the cloud, preventing resource overload and maintaining system reliability.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system dynamically adapts task execution locations based on real-time resource conditions. Task placement is not fixed but changes according to the current state of resource availability at different nodes, enabling the system to optimize between local execution benefits and resource overload prevention.

Inventive Principle:

Principle #15Dynamics

4Loss of time

If tasks are distributed among sensor nodes, then latency is reduced, but system complexity increases

Engineering Contradiction:

ImprovelatencyVSAvoidsystem complexity

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The system implements a universal task management framework that can operate across diverse IoT devices with different resource capabilities. By creating a standardized mechanism for task placement and execution that works across sensor nodes, edge devices, and cloud platforms, the system reduces the complexity of managing distributed task execution across heterogeneous devices.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11954535B2Systems, devices, and methods for execution of tasks in an internet-of-things (IOT) environment

Publication Date: 2024.04.09 SIEMENS AG

AI summary

Systems, devices, and methods of execution one or more tasks in an Internet-of-Things (IoT) environment are disclosed herein. An exemplary method includes determining an event associated with overloading of a first sensor node in the IoT environment based on resources available in real-time on the first sensor node, wherein the event is determined based on number of tasks pending for execution at the first sensor node. Further, the method includes identifying the one or more tasks executable by a second sensor node. Furthermore, the method includes establishing communication with the second sensor node in the IoT environment and assigning the one or more tasks to the second sensor node such that the second sensor node executes the one or more tasks.