Linear wireless sensor networks: Classification and applications

Imad Jawhar, Nader Mohamed, Dharma P. Agrawal

    Research output: Contribution to journalArticlepeer-review

    149 Citations (Scopus)

    Abstract

    Wireless sensor networks (WSNs) constitute a rapidly growing technology, taking advantage of advances in electronic miniaturization that consume less energy for both processing and communication. The cost of these devices is also constantly decreasing, making it possible to use a large number of sensor devices in a wide array of commercial, environmental, military, and health care fields. Many of these applications involve placing the sensors in a linear form, making a special class of these networks which we define as a Linear Sensor Network (LSN). In this paper, the concept of LSNs is expanded, along with a set of applications for which this type of network is appropriate. In addition, motivation for designing specialized protocol is provided that explores linearity of the network to increase the communication efficiency, reliability, fault tolerance, energy savings and network lifetime. Furthermore, classification of LSNs from both topological and hierarchical points of views, is presented and various characteristics, research challenges and underlying opportunities are discussed. Simulation experiments are also presented to compare the performance and reliability of LSNs.

    Original languageEnglish
    Pages (from-to)1671-1682
    Number of pages12
    JournalJournal of Network and Computer Applications
    Volume34
    Issue number5
    DOIs
    Publication statusPublished - Sept 2011

    Keywords

    • Ad hoc and sensor networks
    • Applications of linear sensor networks
    • Networking frameworks
    • Routing

    ASJC Scopus subject areas

    • Hardware and Architecture
    • Computer Science Applications
    • Computer Networks and Communications

    Fingerprint

    Dive into the research topics of 'Linear wireless sensor networks: Classification and applications'. Together they form a unique fingerprint.

    Cite this