A trust-based fuzzy neural network for smart data fusion in internet of things

Abstract Internet of Things (IoT) devices generates a vast amount of data from extensive applications. Maintaining the sensed data with low energy consumption, delay time, and adaptive coverage fraction rate proportionally influences the storage capacity. To maintain a trade-off between above-listed factors, we proposed an Elfes Sugeno Fuzzy and Trust-based Neural Networks (ESF-TNN) approach enables 3-algorithms. First, Elfes Probability Sensing (EPS) Model addresses the coverage fraction of each IoT sensor. Second, Sugeno Fuzzy Processing model regulates the energy consumption by proportionately distributing data to nodes without the defuzzification process. Third, Trust-based Neural Data Storage algorithm enriches an adequate data storage capacity by considering the average classification ratio while processing regenerated data packets to pertain each interaction information via Trust Mechanism. Simulation results show that our proposed method effectively covers the monitored area with 15 Joules of energy consumption and 1-ms delay time along with sufficient storage capacity.

[1]  Lianbing Deng,et al.  Smart IoT information transmission and security optimization model based on chaotic neural computing , 2019, Neural Computing and Applications.

[2]  Robin Singh Bhadoria,et al.  Uncertainty in sensor data acquisition for SOA system , 2017, Neural Computing and Applications.

[3]  Ugo Fiore,et al.  A dynamic trust model exploiting the time slice in WSNs , 2014, Soft Comput..

[4]  Lu Sun,et al.  Study on supply chain strategy based on cost income model and multi-access edge computing under the background of the Internet of Things , 2019, Neural Computing and Applications.

[5]  Zeyu Sun,et al.  ECAPM: An Enhanced Coverage Algorithm in Wireless Sensor Network Based on Probability Model , 2015, Int. J. Distributed Sens. Networks.

[6]  Zhuo Li,et al.  A novel HBase data storage in wireless sensor networks , 2017, EURASIP J. Wirel. Commun. Netw..

[7]  Jiong Jin,et al.  Cyber security framework for Internet of Things-based Energy Internet , 2018, Future Gener. Comput. Syst..

[8]  Mohamed Elhoseny,et al.  EoT-driven hybrid ambient assisted living framework with naïve Bayes–firefly algorithm , 2019, Neural Computing and Applications.

[9]  Aitor Almeida,et al.  An IoT-Aware Architecture for Collecting and Managing Data Related to Elderly Behavior , 2017, Wirel. Commun. Mob. Comput..

[10]  Florin Pop,et al.  Deep learning model for home automation and energy reduction in a smart home environment platform , 2018, Neural Computing and Applications.

[11]  Hao Wang,et al.  A sector-based random routing scheme for protecting the source location privacy in WSNs for the Internet of Things , 2019, Future Gener. Comput. Syst..

[12]  Lianbing Deng,et al.  IoT complex communication architecture for smart cities based on soft computing models , 2019, Soft Computing.

[13]  Antonio Celesti,et al.  Intelligent equipment design assisted by Cognitive Internet of Things and industrial big data , 2018, Neural Computing and Applications.

[14]  Laurence T. Yang,et al.  A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion , 2019, Inf. Fusion.

[15]  Jin Wang,et al.  An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks , 2019, Int. J. Distributed Sens. Networks.

[16]  G. P. Biswas,et al.  Networking for IoT and applications using existing communication technology , 2017, Egyptian Informatics Journal.

[17]  Jiejun Hu,et al.  A semantics-based approach to multi-source heterogeneous information fusion in the internet of things , 2017, Soft Comput..

[18]  Mohamed Elhoseny,et al.  Hybrid optimization with cryptography encryption for medical image security in Internet of Things , 2018, Neural Computing and Applications.

[19]  Mahammad Shareef Mekala,et al.  (t,n): Sensor Stipulation with THAM Index for Smart Agriculture Decision-Making IoT System , 2019, Wirel. Pers. Commun..

[20]  Partha Pratim Ray.  A survey on Internet of Things architectures , 2018, J. King Saud Univ. Comput. Inf. Sci..

[21]  Fadi Al-Turjman,et al.  Cognitive routing protocol for disaster-inspired Internet of Things , 2017, Future Gener. Comput. Syst..

[22]  Tarek R. Sheltami,et al.  EATDDS: Energy-aware middleware for wireless sensor and actuator networks , 2019, Future Gener. Comput. Syst..

[23]  Xin Zhang,et al.  An novel anonymous user WSN authentication for Internet of Things , 2019, Soft Comput..

[24]  Mahammad Shareef Mekala,et al.  Equilibrium Transmission Bi-level Energy Efficient Node Selection Approach for Internet of Things , 2019, Wirel. Pers. Commun..

[25]  Muhammad Arshad,et al.  Multi-criteria based zone head selection in Internet of Things based wireless sensor networks , 2018, Future Gener. Comput. Syst..

[26]  Mahammad Shareef Mekala,et al.  A survey: energy-efficient sensor and VM selection approaches in green computing for X-IoT applications , 2018, International Journal of Computers and Applications.