Sensor Content Encoding With Adjustable Window Compression Split

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Solution Overview

Problem

Integrated circuit devices, such as processors in sensor nodes and gateway devices, face challenges in efficiently processing and communicating diverse and abundant content due to resource constraints, energy consumption, and bandwidth limitations, particularly in geographically distributed sensor networks.

Innovation Solution

The implementation of a processing window of adjustable size for sensor content encoding, utilizing techniques like LZ77 and Huffman encoding, allows for efficient compression and communication of sensor data, distributing encoding tasks between sensor nodes and gateway devices to reduce bandwidth utilization and enhance resource utilization.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If sensor content is processed and communicated without compression, then processing and communication are simpler, but bandwidth consumption increases and resource efficiency deteriorates

Engineering Contradiction:

Improveresource utilization efficiencyVSAvoidenergy consumption

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The encoding process is divided into two distinct stages: LZ77 compression performed at sensor nodes, followed by Huffman encoding performed at gateway devices. This segmentation allows each device to perform only the portion of encoding suitable for its capabilities, reducing overall energy consumption while maintaining compression efficiency.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically adjusts the processing distribution between sensor nodes and gateway devices based on available resources, data characteristics, and network conditions. The split encoding approach allows flexible allocation of computational tasks to optimize energy efficiency under varying operational conditions.

Inventive Principle:

Principle #15Dynamics

2Adaptability or versatility

If a fixed-size processing window is used for encoding, then implementation is simpler, but adaptability to diverse content patterns is reduced

Engineering Contradiction:

Improveadaptability to content patternsVSAvoidencoding implementation complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The processing window size is made dynamic rather than fixed, allowing the encoding algorithm to adapt to different content patterns and redundancy characteristics. The window size can be adjusted based on the observed data patterns, enabling the system to handle diverse sensor content effectively without requiring complex manual configuration.

Inventive Principle:

Principle #15Dynamics

3Power

If all encoding is performed at sensor nodes, then gateway device processing is reduced, but sensor node energy consumption and computational load increase

Engineering Contradiction:

Improvecomputational power distributionVSAvoidsensor node energy consumption

Core Design Contradiction:

PowerVSUse of energy by moving object

Solution Approach 1:

The encoding workload is segmented between sensor nodes and gateway devices. Sensor nodes perform only LZ77 compression which is less computationally intensive, while gateway devices with more resources perform the Huffman encoding stage. This segmentation reduces energy consumption at resource-constrained sensor nodes while maintaining overall compression effectiveness.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Gateway devices act as intermediary nodes that receive partially encoded data from sensor nodes and complete the encoding process. This intermediary role allows the system to distribute computational load optimally, with gateways handling the more intensive Huffman encoding while sensor nodes focus on initial compression and data transmission.

Inventive Principle:

Principle #24Intermediary (Mediator)

4Quantity of substance

If compression encoding is applied to sensor content, then bandwidth consumption is reduced, but processing complexity and energy consumption increase

Engineering Contradiction:

Improvebandwidth consumptionVSAvoidencoding processing complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The compression encoding process is segmented into two stages: LZ77 compression at sensor nodes and Huffman encoding at gateway devices. This segmentation reduces the complexity burden on individual devices while achieving effective bandwidth reduction through combined compression.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes the parameter of encoding distribution, transforming the problem from a single-device complex encoding task to a distributed two-stage process. This parameter change allows bandwidth reduction to be achieved while managing processing complexity through strategic task allocation based on device capabilities.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10931304B1Sensor content encoding

Publication Date: 2021.02.23 ARM IP

AI summary

Disclosed are techniques for encoding a set of sensor content symbols at least in part via applying a processing window of an adjustable size.