Nodes localization in sensor networks based on vectors and particle swarm optimization

ABSTRACT

This paper proposed a design of an integrated algorithm based on DV-Hop. A Location Correction Vector (LCV) was constructed by the difference between estimated distance and range measurement, nodes were clustered when anchors were heads of clusters, where object function expressing total distance error was constructed in a cluster. Particle Swarm Optimization (PSO) was used to solve the minimization problem, then correction steps of all member nodes had been done; the value of location correction equals the product of LCV and step; then extra location correction had been executed by using the relative positions among edge nodes of neighbor clusters. Simulation results show that the localization error of DV-Hop has been reduced by 75% and indicate that the present algorithm is also applicable to low-density networks.

REFERENCES

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INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Distributed networks

Additional Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Wireless communication
      C.2.4 Distributed Systems
          Subjects: Distributed applications

General Terms:
Algorithms, Performance

Keywords:
DV-Hop, location correction vector, node localization, particle swarm optimization, wireless sensor networks