DEVELOPMENT OF A CONTEXT-AWARE NODE BEHAVIOR RECONFIGURATION SYSTEM

ABSTRACT

A sensor node is one of the key components in the design and implementation of a wireless sensor network in its numerous application areas. However, these sensor nodes are inherently energy-constrained as they are mostly battery powered. In order to extend the lifetime of the node, its batteries energy can either be replenished using different energy harvesting mechanisms or replaced once it is completely drained. However, the former approach has only powered limited class of devices with finite capacity while the latter is difficult to implement due to the inaccessibility of most deployment areas as well as its cost implication. As such, it is best practice to minimize as much as possible the rate of energy consumption during its power consuming activities. This research focuses on the development of a context-aware node behavior reconfiguration system for wireless sensor networks. Low power components namely; MSP430 microcontroller, ZE51-2.4 communication module, Gascard NG and Graphene sensors were used to design a smart custom node system which was modeled using MatLab Simulink. A context-aware and energy-efficient data acquisition reconfiguration algorithm (CAEEDARA) which adapts sampling frequency and sampling interval based on its input characteristics as well as its available battery energy was developed. The developed algorithm run on the base station and coordinates the reconfiguration activity when the predefined threshold is exceeded. To perform the validation of the behavior of the developed algorithm, secondary historical data was obtained from AMiner database for three gases namely; carbon dioxide (CO2), methane (CH4) and nitrogen dioxide (NO2). An exploratory data analysis tool (RStudio) was used to perform descriptive statistical analysis on the collected data; the results were then used to set the threshold values for the simulation running on MatLab 2018b. Also, a customized base station application interface was developed using Microsoft Visual Studio 2017 based on Windows form with Visual Basic .Net programming language to monitor threshold values from a remote location was developed and used to validate the behavior of the developed algorithm, and energy consumption deductions were obtained. A comparison of the developed smart custom node system energy consumption and duty cycle was performed with respect to existing literature. Finally, regression analysis and analysis of variance (ANOVA) test were used to test the efficiency of the developed system. vii Result obtained from the energy consumption comparison running the base station application shows that CAEEDARA (Power Saving) mode outperformed the Normal mode with an energy save of 4.155 mAh which is about 80% of the total energy consumed for a twenty (20) minutes of simulation time. The energy consumption and duty cycle comparison with Saraswat & Bhattacharya work proved that CAEEDARA system consumes lesser energy even though it has a much longer duty cycle. Also, the efficiency results showed that there is a strong correlation between the developed CAEEDARA system and existing system. Finally, this research has proved that the lifetime of a custom node for wireless sensor networks can be extended through the use of a context-aware node reconfiguration algorithm in adapting sampling frequency and sampling interval based on its available battery energy which forms part of its context.