An Efficient Model-Based Clustering via Joint Multiple Sink Placement for WSNs

Abstract

Wireless sensor networks consist of many restrictive sensor nodes with limited abilities, including limited power, low bandwidth and battery, small storage space, and limited computational capacity. Sensor nodes produce massive amounts of data that are then collected and transferred to the sink via single or multihop pathways. Since the nodes’ abilities are limited, ineffective data transmission across the nodes makes the network unstable due to the rising data transmission delay and the high consumption of energy. Furthermore, sink location and sensor-to-sink routing significantly impact network performance. Although there are suggested solutions for this challenge, they suffer from low-lifetime networks, high energy consumption, and data transmission delay. Based on these constrained capacities, clustering is a promising technique for reducing the energy use of wireless sensor networks, thus improving their performance. This paper models the problem of multiple sink deployment and sensor-to-sink routing using the clustering technique to extend the lifetime of wireless sensor networks. The proposed model determines the sink placements and the most effective way to transmit data from sensor nodes to the sink. First, we propose an improved ant clustering algorithm to group nodes, and we select the cluster head based on the chance of picking factor. Second, we assign nodes to sinks that are designated as data collectors. Third, we provide optimal paths for nodes to relay the data to the sink by maximizing the network’s lifetime and improving data flow. The results of simulation on a real network dataset demonstrate that our proposal outperforms the existing state-of-the-art approaches in terms of energy consumption, network lifetime, data transmission delay, and scalability.

RETRACTED: Multifactor optimized mobile sink data collection framework for hybrid wireless sensor network‐long term evolution‐assisted Internet of Things network

“…TOSSIM mote sensor model is simulated, and thus, the communication range, MAC protocol, and so forth of TOSSIM model are used as simulation parameters. The performance behavior of the proposed solution is compared with a cluster‐based mobile sink data collection scheme proposed by Wei et al 7 , energy balanced data collected with constrained path for mobile sink by Fu and He, 11 and multisink clustering approach proposed by Bouarourou et al 31 Use of LTE interface as backhaul for emergency packet delivery is a salient feature of the proposed solution. But the compared works don't use LTE interface.…”

“…The simulation was tested for a maximum of 500 nodes to check the scalability of the solution. So, this work started the simulation with 7 , energy balanced data collected with constrained path for mobile sink by Fu and He, 11 and multisink clustering approach proposed by Bouarourou et al 31 Use of LTE interface as backhaul for emergency packet delivery is a salient feature of the proposed solution. But the compared works don't use LTE interface.…”

“…A path connecting the cluster head is found using ant colony optimization, which has a higher maintenance overhead. Bouarourou et al 31 combined clustering and multisink data collection to maximize the sensor network lifespan. The network is clustered using an improvised ant colony algorithm.…”

Multi-factor optimized mobile sink data collection framework for hybrid WSN-LTE assisted IoT network

“…The performance of the proposed solution is compared to a cluster based mobile sink data collection scheme proposed by Wei et al [ 6 ], energy balanced data collected with constrained path for mobile sink by Fu et al [ 10 ] and multi sink clustering approach proposed by Bouarourou et al [ 27 ]. Use of LTE interface as backhaul for emergency packet delivery is a salient feature of the proposed solution.…”

“…A path connecting the cluster head is found using ant colony optimization, which has a higher maintenance overhead. Bouarourou et al [ 27 ] combined clustering and multi-sink data collection to maximize the lifetime of the sensor network. The network is clustered using an improvised ant colony algorithm.…”