Dynamic Stream Evaluation for Wireless Sensor Energy Efficiency

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Solution Overview

Problem

Existing solutions for stream processing on resource-constrained devices, such as mobile phones, result in unacceptably high communication-related energy overheads, limiting the operational lifetimes of both sensors and mobile devices due to inefficient data acquisition and processing strategies that do not consider variable costs and constraints.

Innovation Solution

A method that dynamically modifies the order and properties of data stream acquisition and processing based on statistical distributions and costs, using an event processing module to optimize data transmission and evaluation, including adjusting sampling rates, chunk sizes, and transmission schedules to minimize energy consumption and extend operational lifetimes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If data streams are continuously acquired and processed from all sensor devices, then complete monitoring functionality is provided, but energy consumption increases significantly

Engineering Contradiction:

Improvemonitoring functionalityVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary actions by pre-calculating and storing statistical distributions and cost metrics for each data stream before actual query processing. When a query arrives, the system uses these pre-computed statistics to quickly determine the optimal evaluation order, avoiding the need to analyze all data streams in real-time and thus reducing energy consumption while maintaining monitoring reliability

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts the data stream evaluation order based on current statistical distributions and cost metrics. Instead of using a fixed processing order, the system adapts the evaluation sequence according to varying data characteristics and query requirements, optimizing energy efficiency while ensuring complete monitoring functionality is maintained

Inventive Principle:

Principle #15Dynamics

2Use of energy by moving object

If data acquisition cost is minimized by selective processing, then energy efficiency improves, but query result accuracy may be compromised

Engineering Contradiction:

Improveenergy efficiencyVSAvoidquery result accuracy

Core Design Contradiction:

Use of energy by moving objectVSMeasurement precision

Solution Approach 1:

The system changes parameters by utilizing statistical distributions and cost metrics as key parameters for determining data stream evaluation order. By incorporating these parameters into the optimization process, the system can selectively process data streams based on their statistical characteristics and associated costs, achieving energy efficiency without compromising query result accuracy through informed selection rather than random or fixed-order processing

Inventive Principle:

Principle #35Parameter changes

3Productivity

If statistical models are used to optimize stream evaluation order, then processing efficiency improves, but system complexity increases

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs preliminary action by pre-computing and storing statistical distributions and cost metrics for all data streams. This advance preparation eliminates the need for complex real-time statistical analysis during query processing, thereby maintaining high processing efficiency while reducing the computational complexity required at runtime

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces statistical distributions and cost metrics as intermediary elements that mediate between raw data streams and query processing. These intermediaries capture the essential characteristics of data streams in advance, allowing the system to make efficient processing decisions without directly analyzing the full complexity of the underlying data, thus improving productivity while managing system complexity

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9137282B2Optimizing evaluation patterns and data acquisition for stream analytics in resource-constrained wireless environments

Publication Date: 2015.09.15 TELCORDIA TECHNOLOGIES INC

AI summary

Mobile wireless devices may receive data streams from multiple remote sensors. The sensors may have limited power supplies and memory capacity. Aspects of the invention use statistical characteristics of the sensor data streams and the cost of acquiring a single element of each stream to determine what sequence the sensors should send their data streams in. The cost of acquiring the data may be modified dynamically, depending on parameters such as block size. Additional factors, such as a sensor's buffer capacity, may limit the amount of stream elements that may be cached and affect the sensors' stream transmit sequence. The evaluation order may be dynamically modified using an event processing engine, to reflect both changing statistics of underlying sensor stream tuples and time-varying acquisition costs associated with individual streams. This helps to increase in the operational lifetime of the sensors and associated monitoring applications.