10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing

Research Article

A Framework for Component Selection in Collaborative Sensing Application Development

Download721 downloads
  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2014.257552,
        author={JIE CAO and Lingmei Ren and Weisong Shi and Zhifeng Yu},
        title={A Framework for Component Selection in Collaborative Sensing Application Development},
        proceedings={10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing},
        publisher={IEEE},
        proceedings_a={COLLABORATECOM},
        year={2014},
        month={11},
        keywords={component selection collaborative sensing},
        doi={10.4108/icst.collaboratecom.2014.257552}
    }
    
  • JIE CAO
    Lingmei Ren
    Weisong Shi
    Zhifeng Yu
    Year: 2014
    A Framework for Component Selection in Collaborative Sensing Application Development
    COLLABORATECOM
    IEEE
    DOI: 10.4108/icst.collaboratecom.2014.257552
JIE CAO,*, Lingmei Ren1, Weisong Shi1, Zhifeng Yu2
  • 1: Wayne State University
  • 2: MobiHealth Technologies
*Contact email: jiecao@wayne.edu

Abstract

Wireless sensor network-based technologies and applications have attracted a lot of attention in the past two decades because of their huge potential to change people’s way of life. These applications usually need close collaboration among multiple sensors, gateways, services and end users. When developing these applications, system designers and practitioners usually face several performance requirements such as the accuracy, battery life and system reliability. Given the hard requirements in system performance, how to choose an optimal combination from various sensors, algorithms and collaborative systems to form the application is the most important problem that practitioners need to address. Ad hoc solutions were proposed in specific applications in the past; however, a general methodology that can be easily applied to future applications is lacking. In this paper, we take the challenge and propose a general framework aiming to address the component selection problem, illustrate how this framework can be applied to real life applications through a case study, and discuss challenging issues and two interesting finds from our implementation.