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access icon free Spatio-temporal probabilistic query generation model and sink attributes for energy-efficient wireless sensor networks

  • Author(s): Pramod Kumar 1  and  Ashvini Chaturvedi 2
    • View affiliations
    • Affiliations: 1: Department of Electronics and Communication Engineering, Manipal Institute of Technology, Manipal 576104, India ;
      2: Center of Excellence: WSN, ECE Department, National Institute of Technology Karnataka, Mangaluru 575025, India
  • Source: Volume 5, Issue 6, November 2016, p. 170 – 177
    DOI:  10.1049/iet-net.2016.0014 , Print ISSN 2047-4954, Online ISSN 2047-4962
© The Institution of Engineering and Technology
Received 11/03/2016, Accepted 04/09/2016, Revised 27/07/2016, Published 01/11/2016

Proliferation in Micro-Electro-Mechanical-Systems (MEMS) technology along with advancement in distributed computing infrastructure has facilitated the versatile usage and deployment of wireless sensors networks (WSNs) in last one and half decades. WSNs support large number of applications from the civilian and military regimes. Irrespective of these regimes; owing to difficulty associated with battery replenishment, proper energy usage has been at centre stage in WSNs operations. The lifetime of WSNs typically depends upon sensor's energy dissipation pattern, which is non-homogeneous with respect to spatial distribution over any short epochs. The genesis behind this non-homogeneity is random generation of queries, which owes to application specific spatio-temporal parameters. Importance of spatio-temporal parameters is ubiquitous in WSNs paradigm and uncertainties are inevitable with these parameters, although the degree of uncertainties varies in accordance to applications served. Thus, from network design perspectives, precision involved with spatio-temporal aspects must be given due priority to obtain a mathematical model that maintains a good rapport with realistic query generation process. With these motivations, the study explores: (i) uses of energy-efficient clustering schemes, (ii) incorporation of spatio-temporal parameters uncertainties into probabilistic model of query generation using fuzzy-intervals bound, and (iii) sink attributes to enhance network lifetime. For various network surveillance scenarios; the performance measures average residual energy status and service-time-duration are estimated and analysed.

Inspec keywords: spatiotemporal phenomena; probability; wireless sensor networks; query processing; telecommunication power management

Other keywords: fuzzy-intervals bound; wireless sensors networks; distributed computing infrastructure; energy-efficient WSN; sink attributes; residual energy status; realistic query generation process; WSN lifetime; service-time-duration; energy dissipation pattern; spatial distribution; MEMS technology; energy usage; spatio-temporal parameters; battery replenishment; energy-efficient clustering schemes; microelectro-mechanical-systems technology; spatio-temporal probabilistic query generation model; probabilistic model

Subjects: Telecommunication systems (energy utilisation); Wireless sensor networks; Probability theory, stochastic processes, and statistics; Other topics in statistics

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