arrow
Return

Model-Driven Approach for Body Area Network Application Development

delete2016-05-12
delete6
delete
OA
AI
A
Algimantas Venčkauskas *
V
Vytautas Štuikys
N
Nerijus Jusas
R
Renata Burbaitė
DOI:10.3390/s16050670delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN) applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level) and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS)). We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD) variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD)) and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor) is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application.
Keywords:
Internet of Things
security and privacy
body area network
WNS
quality-of-service
BAN software design
model-driven approach
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Sensors cover
Sensors
IF:
3.5
Papers:
7.1W
Citations:
20.9W

Organization

K
Kaunas University of Technology
Scholars:
3.1K
Papers: 2.7K
Citations: 4