M2M Broker Data Processing Delegation

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Solution Overview

Problem

The rapid deployment of sensor networks and increased usage of Machine-to-Machine (M2M) communication lead to a significant data processing workload on brokers, especially when streaming data is sent, necessitating a method to reduce computational load while maintaining data security and privacy.

Innovation Solution

Delegating data processing from the broker entity to a remote data-processing entity by generating and sending a data key and processing algorithm, encrypting and decrypting data, and ensuring authentication through public key certificates, allowing secure data processing outside the broker, thereby distributing the workload and maintaining privacy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data processing is centralized at the broker entity, then data security and privacy are maintained, but computational load on the broker increases significantly

Engineering Contradiction:

Improvedata securityVSAvoidcomputational load

Core Design Contradiction:

ReliabilityVSPower

Solution Approach 1:

The patent segments the data processing function from the broker entity and delegates it to remote data-processing entities. The broker retains control over key generation and algorithm distribution, while actual data processing occurs at distributed endpoints, reducing the broker's computational burden while maintaining security through centralized key management.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces remote data-processing entities as intermediaries between the broker and sensor networks. These entities receive encrypted data, apply processing algorithms, and return results without the broker directly handling the computationally intensive processing tasks, thus reducing broker load while maintaining security through the intermediary layer.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Power

If data processing is decentralized to remote entities, then computational load on broker is reduced, but system complexity increases

Engineering Contradiction:

Improvecomputational loadVSAvoidsystem complexity

Core Design Contradiction:

PowerVSDevice complexity

Solution Approach 1:

The patent creates universal data-processing entities that can handle multiple types of data processing tasks. These entities receive processing algorithms from the broker and can execute various processing functions, reducing the need for specialized processing components and simplifying the overall system architecture despite the decentralized nature.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent uses copying of processing algorithms and encryption keys to multiple remote data-processing entities. Instead of replicating complex processing logic throughout the system, the broker generates and distributes copies of processing algorithms and keys, simplifying the deployment and management of decentralized processing capabilities.

Inventive Principle:

Principle #26Copying

3Productivity

If more data is processed and shared with applications, then service quality improves, but data privacy of sensor networks is compromised

Engineering Contradiction:

Improveservice qualityVSAvoiddata privacy

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The patent applies local quality by allowing different levels of data processing and sharing for different applications. The broker can distribute specific processing algorithms to remote entities based on application requirements, enabling each application to receive appropriately processed data while maintaining privacy for data not intended for sharing.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent implements partial action by processing and sharing only the specific portions of data that applications require, rather than sharing all raw sensor data. Remote data-processing entities apply algorithms to extract only the necessary information, improving service quality while minimizing privacy loss through selective data sharing.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS8560835B2Method and apparatus for machine-to-machine communication

Publication Date: 2013.10.15 TELEFONAKTIEBOLAGET LM ERICSSON (PUBL)

AI summary

According to a first aspect of the present invention there is provided a method of at least partly delegating processing of data in a machine-to-machine system to reduce computational load on a broker entity 11 while maintaining security of the data to be processed, the broker entity 11 serving as a link between a node 13 of a sensor network providing the data and an application node 12 requesting the data. In the method, at the broker entity 11, following receipt of a request for processed data from the application node 12, determining the node to provide the data to be processed, generating a data key for the data-providing node 13, generating a data-processing algorithm for processing the data in dependence upon the request, sending the data key to the data-providing node 13, and sending the data key and data-processing algorithm to a remote data-processing entity 15. At the data-providing node 13, encrypting the data using the data key and sending the encrypted data to the data-processing entity 15. At the data-processing entity 15, decrypting the data using the data key, processing the data using the data-processing algorithm, and sending the processed data to the application node 12.