TECEAP: Two-tier era-based clustering energy-efficient adaptive and proactive routing protocol for wireless sensor networks

The role of relay nodes in Wireless Sensor Network in proactive periodic monitoring applications is to route data from all the sensors in the Region of Interest (ROI) to the Base Station (BS). Accordingly, random relay nodes selection is used in energy-efficient routing protocols to avoid the energy-hole problem; however, cluster-based routing protocols usually depend on periodic topology formation, which adds significant energy overhead. The proposed cluster-based routing protocol has a two-tier structure that combines the benefit of cluster-head distribution and chain-based routing to minimize cluster-head (CH) loss due to data aggregation and ROI to BS data transmission. Additionally, it uses an adaptive length of time for network reconstruction to maintain network adaptability with minimal network overhead through network awareness approach to maintain network connectivity. The results of our work have been compared to competing for energy efficient routing protocols that have probabilistic nature like LEACH and NEECP and routing protocols that tackle the same problem of relay nodes loss in far ROI to BS transmission. These results proved the advancement of TECEAP by showing about 100% increase in network stability period, and the extremely low rate of network energy and node losses. The results also proved that in TECEAP, the ROI coverage is sufficiently preserved through the network lifetime.

[1]  Mubashir Husain Rehmani,et al.  Applications of wireless sensor networks for urban areas: A survey , 2016, J. Netw. Comput. Appl..

[2]  Li Qing,et al.  Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks , 2006, Comput. Commun..

[3]  Manuel Filipe Santos,et al.  WSN4QoL: WSNs for remote patient monitoring in e-Health applications , 2016, 2016 IEEE International Conference on Communications (ICC).

[4]  Ahmed I. Saleh,et al.  Energy-efficient routing protocols for solving energy hole problem in wireless sensor networks , 2017, Comput. Networks.

[5]  Walid Osamy,et al.  IBLEACH: intra-balanced LEACH protocol for wireless sensor networks , 2014, Wireless Networks.

[6]  Qiang Li,et al.  Poster Abstract: Piezoelectric Energy Harvesting Powered WSN for Aircraft Structural Health Monitoring , 2016, 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[7]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[8]  Shouning Qu,et al.  An Efficient Data Aggregation Algorithm for WSNs Based on Dynamic Message List , 2016, ANT/SEIT.

[9]  Ridha Bouallegue,et al.  Exploiting machine learning strategies and RSSI for localization in wireless sensor networks: A survey , 2017, 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC).

[10]  Cauligi S. Raghavendra,et al.  PEGASIS: Power-efficient gathering in sensor information systems , 2002, Proceedings, IEEE Aerospace Conference.

[11]  Rajeev Kumar,et al.  NEECP: Novel energy-efficient clustering protocol for prolonging lifetime of WSNs , 2016, IET Wirel. Sens. Syst..

[12]  Peng Shi,et al.  Distributed Hybrid Particle/FIR Filtering for Mitigating NLOS Effects in TOA-Based Localization Using Wireless Sensor Networks , 2017, IEEE Transactions on Industrial Electronics.