On the energy efficiency of lossless data compression in wireless sensor networks

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Principle of democracy as governance is for the people by the people and of the people. People are not the recipient of state framed There has been a lot of research on using less data techniques to minimize the volume and to result ultimately in reducing power consumption. In this page we will study about a way to save data known as Model based clustering which reduces communication flow between nodes to reduce power consumption. The suggested study uses the capacity of mixture-model based group to use both the temporal locality i.e. reuse of specific data and slowly changing properties of the sensing data to framework the sensor network’s traffic. These frameworks can be used by the sensor nodes to the sensed measurements and node to recover the data without data to be fully transferred by a number of sensor nodes. Consequences show that our study contributes to limiting in energy consumption in a resource-limited sensor network

     

     

     

  • Keywords


    Wireless Sensor; Data Compression Devices or Software; Energy Effectiveness.

  • References


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      [2] Daniele Apiletti Elena Baralis Tania Cerquitelli, “Energysaving models for wireless sensor networks”, London Limited: Springer-Verlag, april 2010.

      [3] S.Anandamurugan, C.Venkatesh, “Increasing the Lifetime of Wireless Sensor Networks by using AR (Aggregation Routing) Algorithm”, IJCA, 2010.

      [4] Tzung-Cheng Chen, Tzung-Shi Chen, “On Data Collection Using Mobile Robot in Wireless Sensor Networks”, IEEE Transactions On Systems, November 2011.

      [5] Laxmi Choudhary, “Challenges for data mining”, IJREAS, February 2012.

      [6] Miao Zhao and Yuanyuan Yang, “Bounded Relay Hop Mobile Data Gathering in Wireless Sensor Networks”, IEEE Transactions on Computers, February 2012.

      [7] Emad M. Abdelmoghith, Hussein T. Mouftah, “A DataMining Approach to Energy Efficiency in Wireless Sensor Networks”, IEEE 24th International Symposium on Personal, Indoor and Mobile Radio Communications, 2013.

      [8] S.Nithyakalyani, Dr.S.Suresh Kumar, “Data aggregation in WSNs using node clustering algorithms”,IEEE Conference on Information and Communication Technologies , 2013.

      [9] Phiros Mansur, Sasikumaran Sreedharan, “Survey of Prediction Algorithms for Object Tracking in Wireless Sensor Networks”, IEEE International Conference on Computational Intelligence and Computing Research, 2014.

      [10] Vickey Sharma,“Data Mining and Data Gathering Algorithm in WSN”, IJARCSSE , April 2015.


 

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Article ID: 19325
 
DOI: 10.14419/ijet.v7i3.29.19325




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