Research Area:  Wireless Sensor Networks

Abstract:

In recent decades, Sensor nodes (SNs) are used in numerous uses of heterogeneous wireless sensor networks (HWSNs) to obtain a variety of sensing data sources. Sink mobility shows a significant part in the enhancement of sensor system execution, energy utilization, and lifetime. To manage sink mobility, rendezvous points (RPs) are introduced where some SNs are chosen as RPs, and the non-RP nodes convey the information to the cluster heads (CHs). The CHs then forward their information to the nearby RPs. To determine the set of RPs and travelling path of mobile sinks (MSs) that visits these RPs is quite challenging. This work presents an energy-efficient SOSS based routing method that depends on RPs and multiple MSs in HWSNs. At first, all the heterogeneous nodes are distributed into the number of clusters using mean shift clustering (MSC). Then, the Bald eagle search (BES) algorithm is used for an optimal selection of CHs whereas multiple MS is employed for effective data gathering. The use of multiple MSs can enhance the data collection efficiency and decreases the energy utilization for HWSNs. Finally, the hybrid seagull optimization and salp swarm (SOSS) algorithm is used to find the RPs and travelling routes of MS. The entire simulation work of the heterogeneous network is simulated in the NS2 platform. The simulation outcomes display that the suggested method provides superior performance in HWSN than other current routing protocols.

Keywords:  

Author(s) Name:  Preeti Gupta,Sachin Tripathi,Samayveer Singh

Publisher name:  Springer

DOI:  10.1007/s11276-021-02714-y

Volume Information:  volume 27, pages 3733–3746 (2021)

Paper Link:   https://link.springer.com/article/10.1007/s11276-021-02714-y