GAFO: genetic adaptive fuzzy hop selection scheme for wireless sensor networks

ABSTRACT

Throughput and energy efficiency are two important parameters to evaluate the performance of a Wireless Sensor Network (WSN). For WSNs involved in varying channel conditions, packet transmission reliability can be affected. This results in increased number of retransmissions and therefore energy consumption, with low throughput. Making optimal choices for robust packet transmission in this scenario is vital. For the purpose of this study, we propose a genetic adaptive fuzzy scheme that uses current network conditions in hop node selection. Signal to noise ratio (SNR) and outage probability (Pout) are chosen as input parameters for the proposed scheme, to decide in a distributed manner, the best hop for reliable packet forwarding. Simulation results show the proposed scheme does indeed provide advantages in improving on transmission reliability by 20% and energy efficiency performance by 15%, under different channel conditions.

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INDEX TERMS

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

Additional Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.2 Network Protocols

General Terms:
Algorithms

Keywords:
energy efficiency, fuzzy logic, genetic algorithms, wireless sensor networks