Wireless sensor networks (WSNs) are application‐oriented and mainly used in the following fields, such as battleground surveillance, border security, and disaster management. The sensor nodes should be extra reliable, and also, high consistency is needed to perform these tasks. Therefore, heterogeneous wireless sensor networks (HWSNs) are introduced to enhance the network lifetime and stability period by minimizing the node's communicative distance from mobile sinks (MSs). The maximum amount of energy is consumed while communicating the data from nodes to a single sink. In this work, multiple mobile sinks (MMSs) are used to transfer the data from nodes to sink with less energy consumption and a reduced number of hops. Also, higher connectivity is ensured as the sinks are placed close to the nodes, and data can be successfully delivered to sinks. This work reveals the importance of multiple MSs in HWSNs. The use of MMSs and cluster‐based routing approaches improves the efficiency of data collection in HWSNs. K‐medoid with adaptive sunflower optimization algorithm is used for the selection of cluster head (CH). To achieve energy efficiency (EE), detecting an optimal route for MS is a critical task. Then, the hybrid Harris Hawk and ant colony optimization (HANT) algorithm‐based sink moving strategy is used for finding an optimal traversal path. The proposed heterogeneous network is implemented in the network simulator (version 2) (NS2) platform. Simulation results show enhancement in EE in terms of network lifetime, stability period, several dead and alive nodes, and network's remaining energy.

Energy efficient hotspot problem mitigation techniques using multiple mobile sink in heterogeneous wireless sensor network

Heterogeneous mobile networks are a vital cue for Internet of Things (IoT) networks and their applications. Therefore, an optimal routing protocol is essential for the heterogeneous network to realize energy efficiency and robustness. However, designing an optimal routing protocol is more complex due to uneven energy depletion and dynamic event generation. The complexity further increases with the node mobility. In this context, the multi-hop routing approach with a controlled mobility pattern provides an energy efficient network by improving memory and storage utilization. This work proposes a new energy-efficient model for heterogeneous network, considering the effect of mobility and residual energy of nodes for cluster head selection in multi-hop-LEACH (M-LEACH). The performance of the proposed mobility induced multi-hop LEACH (Mob M-LEACH) protocol is further compared with existing baseline methods. The robustness of the network is evaluated considering static and dynamic environments for multiple network technologies. The simulation results show that the proposed method reduces network latency by 25% and enhances the throughput by 75%, improving energy consumption and network lifetime when compared with the state-of-art methods. 

Mobility Induced Multi-Hop LEACH Protocol in Heterogeneous Mobile Network

Heterogeneous mobile networks are a vital cue for Internet of Things (IoT) networks and their applications. Therefore, an optimal routing protocol is essential for the heterogeneous network to realize energy efficiency and robustness. However, designing an optimal routing protocol is more complex due to uneven energy depletion and dynamic event generation. The complexity further increases with the node mobility. In this context, the multi-hop routing approach with a controlled mobility pattern provides an energy efficient network by improving memory and storage utilization. This work proposes a new energy-efficient model for heterogeneous network, considering the effect of mobility and residual energy of nodes for cluster head selection in multi-hop-LEACH (M-LEACH). The performance of the proposed mobility induced multi-hop LEACH (Mob M-LEACH) protocol is further compared with existing baseline methods. The robustness of the network is evaluated considering static and dynamic environments for multiple network technologies. The simulation results show that the proposed method reduces network latency by 25% and enhances the throughput by 75%, improving energy consumption and network lifetime when compared with the state-of-art methods.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09982453.pdf

Energy efficiency has always been the foremost issue from early time in Wireless Sensor Networks (WSNs). To address the issues of energy, many optimized routing protocols have been proposed. Many challenging problems may occur mainly due to drainage of batteries in the network. These problems can be resolved by improving the network lifetime as well as stability period using some efficient routing-based protocols. WSN can be categorized as homogeneous and heterogeneous WSN relying on the attributes of the network. Heterogeneous sensor nodes have more advantages as compared with homogeneous with the advancement of energy and resources in the network. In this work, nodes are distributed among multiple regions where all the nodes are divided into certain clusters. The clusters automatically elect the cluster heads (CHs), which are carriers of data to sink node. Multi-objective differential evolution is used to select the shortest path among the CHs and the base station. Results have shown that this protocol improves the execution of the network field using heterogeneous nodes.

Efficient multi-objective differential-evolution-based clustering protocol

Over the last few epochs, researchers have shown an emergent interest in the domain of sensor networking due to an increasing number of machine-driven industries and battlefield-associated applications. Wireless Sensor Networks comprises thousands or even more number of unsystematically placed energy-deficient sensor units. These sensors are basically deployed for varied purposes mainly aimed to transfer the data from the sensor fields to the distant sink or base station (BS). This operation demands excessive amount of energy. Spreading WSN lifetime and minimizing energy costs are preeminent colossal tasks in the field of sensor networking. Developing a desired energy equivalent routing mechanism is the core consideration while dealing with WSNs. In applied scenarios, almost all types of WSNs are heterogeneous in nature or are intended to become heterogeneous after a slight life span. Essentially, efficiency of any protocol changes with varied heterogeneity environments. This is the reason why there is an absolute need for testing of various routing protocols underling variable heterogeneous constraints to cope with the hands-on problems. The following paper reviewed the impact of different clustering patterns based on standard Heterogeneous WSNs. The analysis shows the adaptable behavior of various protocols with altering environment. The main aim here is to present a basic consideration in designing clustering algorithms.

A Literature Review on Energy-Efficient Routing Protocols for Heterogeneous WSNs

The prominent criteria for the Wireless Sensor Network are a lifetime of the network, stability, and the energy parameter. To enhance these crucial parameters, the paper introduces Routing Algorithms for hybrid nodes in sensor networks ‘RA-HNW’ protocol having four forms of sensor nodes varying in energy and capacities to improve the stability and lifespan of the sensor networks. The simulations for the proposed RA-HNW is simulated in MATLAB 2018b. It is observed that using the functionalities and capabilities of the different types of nodes taken in the work, the stability of the proposed schema increases by 49.12% as compared to the DCHRP4, twice and thrice as compared to ETSSEP, TSEP, and SEP. The lifetime criteria also upgrade by 10.49% over DCHRP4 with level four heterogeneity, 15.85% over DCHRP, 19.65% over ETSSEP, and about 64.87% over TSEP. The proposed RA-HNW methodology is well suited for working in the fixed sink environment.

Routing Algorithms for Hybrid Nodes in WSNs

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A Literature Review on Energy-Efficient Routing Protocols for Heterogeneous WSNs

Routing Algorithms for Hybrid Nodes in WSNs