Towards Energy Efficient Big Data Gathering in Densely Distributed Sensor Networks, IEEE Transactions on Emerging Topics in Computing, 2014.
  • To achieve an energy-efficient data collection in densely distributed WSNs, this paper propose a clustering method based on Expectation-Maximization (EM) algorithm. The EM algorithm is a classical clustering algorithm, which assumes that nodes are distributed according to Gaussian mixture distribution. To minimize the energy to send data, all sensor nodes send the sensed information according to the value of responsibility of the cluster.

+ Description
  • To achieve an energy-efficient data collection in densely distributed WSNs, this paper propose a clustering method based on Expectation-Maximization (EM) algorithm. The EM algorithm is a classical clustering algorithm, which assumes that nodes are distributed according to Gaussian mixture distribution. To minimize the energy to send data, all sensor nodes send the sensed information according to the value of responsibility of the cluster.

  • To minimize the energy consumption by using optimal number of clusters.

  • To maintain network connectivity.

+ Aim & Objectives
  • To minimize the energy consumption by using optimal number of clusters.

  • To maintain network connectivity.

  • A technique is contributed to further reduce the energy consumption in the Distributed Sensor Networks.

+ Contribution
  • A technique is contributed to further reduce the energy consumption in the Distributed Sensor Networks.

  • OS : Window 7 (Cygwin) / Ubuntu 12.04 LTS 64bit.

  • Simulator: NS 2.35, Language : TCL and AWK script, (C++)

+ Software Tools & Technologies
  • OS : Window 7 (Cygwin) / Ubuntu 12.04 LTS 64bit.

  • Simulator: NS 2.35, Language : TCL and AWK script, (C++)

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

+ Related Projects

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