E2DA: Energy Efficient Data Aggregation and End-to-End Security in 3D Reconfigurable WSN

This paper deals with energy consumption and security limitations in the reconfigurable WSN’s in order to improve the network lifetime with end-to-end data privacy. The network consists set of nodes placed in distributed environment such that each node performs a reconfiguration task to support users requirements. We proposed novel solutions that improved network lifetime through efficient reconfigurable routing and less network traffic. We proposed an in-network task to eliminate duplicate packets at the node level using hashing distance computation (HDC). Further, we introduced power-efficient reconfigurable cell-by-cell golden sector-based emperor penguin colony (CbC GSEPC) for trust-based routing. In terms of data confidentiality in the energy-constrained environment, a lightweight key expandable cryptography method was proposed for end-to-end confidentiality. Additionally, a reading-based dual validation (RbDV) audits the information at sink level for intrusion detection and isolates suspicion nodes. The proposed and existing works simulated with NS-3.26 and the results show that the proposed work’s average energy consumption is 5.82% lower than the existing 2D-WSN while offering end-to-end confidentiality and node reconfiguration opportunity.

[1]  Ioannis Stavrakakis,et al.  Energy and Distance Optimization in Rechargeable Wireless Sensor Networks , 2021, IEEE Transactions on Green Communications and Networking.

[2]  Wencong Su,et al.  A Machine-Learning-Based Cyber Attack Detection Model for Wireless Sensor Networks in Microgrids , 2021, IEEE Transactions on Industrial Informatics.

[3]  Fortunato Santucci,et al.  Development of an extended topology-based lightweight cryptographic scheme for IEEE 802.15.4 wireless sensor networks , 2020, Int. J. Distributed Sens. Networks.

[4]  Haris Pervaiz,et al.  FESDA: Fog-Enabled Secure Data Aggregation in Smart Grid IoT Network , 2020, IEEE Internet of Things Journal.

[5]  Geoffrey Ye Li,et al.  Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities , 2020, IEEE Transactions on Cognitive Communications and Networking.

[6]  Li Tian,et al.  Secure big data communication for energy efficient intra-cluster in WSNs , 2019, Inf. Sci..

[7]  Ashraf Hossain,et al.  Improved low energy adaptive clustering hierarchy and its optimum cluster head selection , 2019, International Journal of Electronics.

[8]  S. K. Srivatsa,et al.  Energy effectual reconfigurable routing protocol (E2R2P) for cluster based underwater wireless sensor networks , 2019, Journal of Ambient Intelligence and Humanized Computing.

[9]  D. Yuvaraj,et al.  Intelligent detection of untrusted data transmission to optimize energy in sensor networks , 2019, Journal of Information and Optimization Sciences.

[10]  Yong Xiang,et al.  Compressed Sensing Based Selective Encryption With Data Hiding Capability , 2019, IEEE Transactions on Industrial Informatics.

[11]  Sherali Zeadally,et al.  Data collection using unmanned aerial vehicles for Internet of Things platforms , 2019, Comput. Electr. Eng..

[12]  K. Raghava Rao,et al.  Hybrid based cluster head selection for maximizing network lifetime and energy efficiency in WSN , 2019, J. King Saud Univ. Comput. Inf. Sci..

[13]  Sadoullah Ebrahimnejad,et al.  Emperor Penguins Colony: a new metaheuristic algorithm for optimization , 2019, Evolutionary Intelligence.

[14]  Fazidah Othman,et al.  Energy Management in RFID-Sensor Networks: Taxonomy and Challenges , 2019, IEEE Internet of Things Journal.

[15]  Sudip Misra,et al.  Energy-Efficient and Distributed Network Management Cost Minimization in Opportunistic Wireless Body Area Networks , 2018, IEEE Transactions on Mobile Computing.

[16]  Dilip Sarkar,et al.  Detection of Good and Bad Sensor Nodes in the Presence of Malicious Attacks and Its Application to Data Aggregation , 2018, IEEE Transactions on Signal and Information Processing over Networks.

[17]  Gihwan Cho,et al.  An Eccentricity Based Data Routing Protocol with Uniform Node Distribution in 3D WSN , 2017, Sensors.

[18]  Jie Cui,et al.  Data aggregation with end-to-end confidentiality and integrity for large-scale wireless sensor networks , 2017, Peer-to-Peer Networking and Applications.

[19]  Sudip Misra,et al.  A Cooperative Bargaining Solution for Priority-Based Data-Rate Tuning in a Wireless Body Area Network , 2015, IEEE Transactions on Wireless Communications.

[20]  Sudip Misra,et al.  Social choice considerations in cloud-assisted WBAN architecture for post-disaster healthcare: Data aggregation and channelization , 2014, Inf. Sci..

[21]  Shan Gao,et al.  DRRP: A dynamically reconfigurable routing protocol for WSN , 2014, 2014 IEEE International Conference on Progress in Informatics and Computing.

[22]  M. Dehghan,et al.  FEDA: Fault-tolerant Energy-Efficient Data Aggregation in wireless sensor networks , 2008, 2008 16th International Conference on Software, Telecommunications and Computer Networks.

[23]  Priyanka Ahlawat,et al.  Lightweight Two-factor Authentication Protocol and Session Key Generation Scheme for WSN in IoT Deployment , 2020 .

[24]  Zhidong Zhao,et al.  An Energy-Optimization Clustering Routing Protocol Based on Dynamic Hierarchical Clustering in 3D WSNs , 2019, IEEE Access.

[25]  Seokjoo Shin,et al.  Energy efficient K-means clustering-based routing protocol for WSN using optimal packet size , 2018, 2018 International Conference on Information Networking (ICOIN).

[26]  Ravindara Bhatt,et al.  Privacy Preservation in WSN for Healthcare Application , 2018 .