• DocumentCode
    3662803
  • Title

    Error diagnosis for energy efficient data aggregation in Wireless sensor networks

  • Author

    Chetan Ambekar;Chirag Shinde;Swapnil Betkar;Aniket Indulkar

  • Author_Institution
    K.J. Somaiya C.O.E., University of Mumbai, India
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Sensor networks are collection of sensor nodes which co-operatively send sensed data to base station. As sensor nodes are battery driven, an efficient utilization of power is essential in order to use networks for long duration hence it is needed to reduce data traffic inside sensor networks, also reduced amount of data need to send to base station. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. Wireless sensor networks (WSN) offer an increasingly Sensor nodes need less power for processing as compared to transmitting data. It is preferable to do in network processing inside network and reduce packet size. One such approach is data aggregation which attractive method of data gathering in distributed system architectures and dynamic access via wireless connectivity. Wireless sensor networks have limited computational power and limited memory and battery power, this leads to increased complexity for application developers and often results in applications that are closely coupled with network protocols. In this paper, a data aggregation framework along with the algorithm on wireless sensor networks is presented. The aim of the proposed work consist a detailed study regarding the error which can occur by the data aggregation and also the circuit complexity which is generated for reduction of these errors.
  • Keywords
    "Temperature sensors","Quality of service","Artificial neural networks"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Control (ISCO), 2015 IEEE 9th International Conference on
  • Type

    conf

  • DOI
    10.1109/ISCO.2015.7282265
  • Filename
    7282265