Perception and Response Model of Danger Signal Based on Immune Peril Principle
Min-Sheng Tan, Chen-Cheng Wang, Miao Guo, Zhi-Guo Zhao, Ting Xiang
Available Online December 2016.
- https://doi.org/10.2991/icwcsn-16.2017.93How to use a DOI?
- Immune peril principle; Internet of Things perception layer; danger degrees of signal; perception, response
- Danger signal perception and response model of perception layer in IoT based on immune peril principle (DSPRM-IPP) and related algorithms were proposed. DSPRM-IPP model includes immunologic tolerance module, danger perception and accumulation module and response module. Immunologic tolerance module's duty is screening detector which is not matching with autologous collection at the beginning of the sensing layer node deployment, it also constantly adjust to the current detector according to the working environment in process of perception. Danger perception and accumulation module is responsible for the danger signal recognition and accumulation, and detector set generated by immunologic tolerance module is used to determine whether the current signal is danger signal or not. Appropriate response strategy will be taken according to the results of comparing potential cost and response cost in response module. The experimental results show that DSPRM-IPP effectively detects the danger with a low rate of false positives, it also has good adaptability that could adjust constantly according to the working environment and node proportion of residual energy.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Min-Sheng Tan AU - Chen-Cheng Wang AU - Miao Guo AU - Zhi-Guo Zhao AU - Ting Xiang PY - 2016/12 DA - 2016/12 TI - Perception and Response Model of Danger Signal Based on Immune Peril Principle BT - 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/icwcsn-16.2017.93 DO - https://doi.org/10.2991/icwcsn-16.2017.93 ID - Tan2016/12 ER -