@article{2573,
  author = {Brahm Prakash Dahiya, Shewta Rani, Pramjeet Singh},
  title = {Swarm Intelligence Techniques to improve lifetime of Wireless Sensor Networks},
  journal = {Signals and Telecommunication Journal},
  year = {2018},
  volume = {7},
  number = {2},
  doi = {https://doi.org/10.6025/stj/2018/7/2/63-75},
  url = {http://www.dline.info/stj/fulltext/v7n2/stjv7n2_3.pdf},
  abstract = {Wireless Sensor networks (WSNs) is collection of various sensor devices to capture the environment conditions.
Node deployment, limited energy capacity, location of sensor devices, Quality of Services (QoS) and data aggregation are
the critical design challenges in WSNs. To overcome these design challenges in WSNs, many techniques have proposed.
Swarm Intelligence (SI) is one of the most appropriate technique to overcome the design challenges in WSNs.SI shows a
current computational and behavioral similitude for taking care of disseminated issues that initially took its motivation from
the biological illustrations gave by social insects like ants, termites, honey bees, wasp. Here, we will discuss many SI
techniques such that Ant Colony Optimization (ACO), Elephant swarm Optimization (ESO), Hnee based optimization (HBO)
and Particle Swarm Optimization (PSO) to make network energy efficient and improve the WSNs lifespan.},
}