IoT Policy Aggregation for Data Management Efficiency

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Solution Overview

Problem

IoT environments face resource constraints such as storage and processing limitations when collecting, storing, and processing data, which complicates data management due to varying data characteristics like volume, variety, velocity, veracity, and value.

Innovation Solution

A method involving identifying and aggregating policies within a system to create an aggregated policy, disseminating this policy for data collection, and subsequently disaggregating the collected data to optimize resource usage and reduce redundancy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If multiple individual policies are implemented separately in IoT environments, then each policy can be managed independently, but system complexity increases and resource consumption increases due to redundant processing

Engineering Contradiction:

Improvepolicy management complexityVSAvoiddata management efficiency

Core Design Contradiction:

Device complexityVSProductivity

Solution Approach 1:

The patent combines multiple individual policies into a single aggregated policy that encompasses the requirements of all individual policies. This aggregation reduces the number of separate policy implementations needed, thereby reducing system complexity while maintaining the ability to manage diverse data collection requirements efficiently across the IoT environment

Inventive Principle:

Principle #5Merging (Combining)

2Reliability

If data is collected according to multiple individual policies, then each policy requirement is met, but redundant data processing and storage occurs consuming excessive resources

Engineering Contradiction:

Improvepolicy requirement fulfillmentVSAvoidprocessing and storage resource consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The system merges multiple individual policies into one aggregated policy that consolidates data collection requirements. This allows data to be collected once according to the aggregated policy's comprehensive requirements, eliminating redundant collection, processing, and storage operations while still fulfilling all individual policy requirements through the unified framework

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The aggregated policy optimizes data collection parameters such as sampling rates, data types, and collection frequencies by consolidating requirements from multiple individual policies. This parameter optimization ensures that data is collected at the necessary granularity and frequency to satisfy all individual policies simultaneously, reducing unnecessary resource consumption

Inventive Principle:

Principle #35Parameter changes

3Ease of operation

If policies are disseminated individually to all nodes, then each node can implement specific policies, but network traffic increases and dissemination time increases

Engineering Contradiction:

Improvepolicy implementation flexibilityVSAvoidpolicy dissemination time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system disseminates a single aggregated policy to all nodes in the IoT environment instead of distributing multiple individual policies separately. This consolidation reduces network traffic and dissemination time significantly, while the aggregated policy maintains the flexibility to accommodate various individual policy requirements through its comprehensive design that incorporates all individual policy specifications

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS11277310B2Systemic adaptive data management in an internet of things environment

Publication Date: 2022.03.15 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer-implemented method according to one embodiment includes identifying a plurality of policies to be implemented within a system, aggregating the plurality of policies to create an aggregated policy, disseminating the aggregated policy within the system, receiving data collected according to the aggregated policy, and disaggregating the data.