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Wireless Sensor Networks (WSNs) have led to tremendous growth in the development of sensor technology and offer numerous applications, such as wildlife monitoring, environment, healthcare, military surveillance and security systems. In terms of performance, the evolutions of WSN routing protocols play a vital role in extending the lifetime of networking operations. Due to the limited resources of power in sensor nodes, the design and implementation of an energy-efficient routing protocol comprise a key challenge for researchers. Before, in the case of a static sink, nodes at farther areas from the sink transmit their sensed data at a longer transmission range and die early, while nearby nodes face lesser transmission costs and stay alive for a longer period. This unbalanced energy distribution creates energy holes in ares far from the sink in WSNs. Mobility-based sink routing protocols are proposed to minimize the sub-optimal energy consumption in WSNs, as the sink mobility covers the sensor field, which alleviates the overall load-balancing among sensor nodes. In order to overcome the energy hole issue while prolonging the network lifetime, it is important to determine the optimal mobility pattern. In this regard, we propose the Spiral Mobility based on Optimized Clustering (SMOC) routing protocol and the Multiple sink-based SMOC (M-SMOC) routing protocol for large-scale WSNs. Performance evaluations of the proposed protocols are compared with various existing routing protocols based on static sink, random mobility and grid mobility. Different numbers of performance parameters are considered for evaluation, such as network lifetime, network stability, packet drop ratio, packet delivery ratio, end-to-end delay, average energy consumption, network connection time and the impact of different heterogeneity levels. Experimental results show the benefits of the spiral mobility pattern and how it improves the network lifetime and stability period over the existing state-of-the-art routing protocols.

Spiral Mobility Based on Optimized Clustering for Optimal Data Extraction in WSNs