• DocumentCode
    3357058
  • Title

    Static worst-case energy and lifetime estimation of wireless sensor networks

  • Author

    Liu, Yu ; Zhang, Wei ; Akkaya, Kemal

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Southern Illinois Univ., Carbondale, IL, USA
  • fYear
    2009
  • fDate
    14-16 Dec. 2009
  • Firstpage
    17
  • Lastpage
    24
  • Abstract
    With the advance of computer and communication technologies, wireless sensor networks (WSNs) are increasingly used in many aspects of our daily life. However, since the battery lifetime of WSN nodes is restricted, the WSN lifetime is also limited. Therefore, it is crucial to determine this limited lifetime in advance for preventing service interruptions in critical applications. This paper proposes a feasible static analysis approach to estimate the worst-case lifetime of a WSN. Assuming known routes with a given sensor network topology and S-MAC as the underlying MAC protocol, we statically estimate the lifetime of each sensor node with a fixed initial energy budget. These estimations are then compared with the results obtained through simulation which run with the same energy budget on each node. Experimental results of our research on TinyOS applications indicate that our approach can safely and accurately estimate the worst-case lifetime of WSNs. To the best of our knowledge, our work is the first one to estimate the worst-case lifetime of WSNs through static analysis method.
  • Keywords
    access protocols; wireless sensor networks; S-MAC protocol; TinyOS applications; WSN worst-case lifetime estimation; service interruption prevention; static analysis; wireless sensor networks; Circuits; Computer networks; Computer science; EPROM; Energy consumption; Life estimation; Lifetime estimation; Network topology; Protocols; Wireless sensor networks; S-MAC; WSNs; worst-case lifetime;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Performance Computing and Communications Conference (IPCCC), 2009 IEEE 28th International
  • Conference_Location
    Scottsdale, AZ
  • ISSN
    1097-2641
  • Print_ISBN
    978-1-4244-5737-3
  • Type

    conf

  • DOI
    10.1109/PCCC.2009.5403808
  • Filename
    5403808