A parallel compact sine cosine algorithm for TDOA localization of wireless sensor network

Siqi Zhang, Fang Fan, Wei Li, Shu Chuan Chu, Jeng-Shyang Pan

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


A Parallel and Compact version of the Sine Cosine Algorithm (PCSCA) is proposed in this article. Parallel method can effectively improve search ability and increase the diversity of solutions. We develop three communication strategies based on parallelism idea to serve different types of optimization function to achieve the best performance. Furthermore, compact method uses statistical distribution to represent the solutions, which can save memory space and energy of the digital device. To check the optimization effect of the proposed PCSCA algorithm, it is tested on the CEC2013 benchmark function set and compared to SCA, parallel compact Cuckoo Search (PCCS) algorithms. The empirical study demonstrates that PCSCA has improved by 50.1% and 5.6%, compared to SCA and PCCS, respectively. Finally, we apply PCSCA to optimize the position accuracy of sensor node deployed in 3D actual terrain. Experimental results show that PCSCA can achieve lower localization error via Time Difference of Arrival method.

Original languageEnglish
Pages (from-to)213-223
Number of pages11
Issue number2
Early online date2 Jun 2021
Publication statusPublished - Oct 2021
Externally publishedYes


  • 3D localization
  • Compact strategy
  • Parallel communication strategy
  • Sine cosine algorithm


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