Heterogeneous Wireless Sensor Networks Research Articles

Secondary cluster head based SEP in heterogeneous WSNs for IoT applications

AbstractA wireless sensor network (WSN) consists of specialized sensor nodes that perform sensing services for Internet of Things devices with limited battery power. As the replacement or recharging of batteries is not possible, energy consumption becomes the most important design issue in WSNs. The energy‐efficient routing protocol gets the most priority in such energy‐constrained networks. The utilization of clustering‐based routing protocols like stable election protocol (SEP) has gained much attention as the network's lifetime is significantly improved due to the clustering of sensor nodes. Moreover, the inclusion of a secondary CH (SCH) is beneficial when the member node with the most remaining energy performs data aggregation and reduces the energy burden of the CH. This article characterizes SEP and Prolong SEP (P‐SEP) protocols and then extends them by incorporating SCH, which ensures balanced energy consumption. The performance of the proposed Extended SEP and Extended P‐SEP protocols has been analysed regarding stability period, network lifetime, energy usage and throughput. The simulation results demonstrate that the proposed protocols outperform state‐of‐the‐art protocols like P‐SEP, Modified SEP (M‐SEP) and SEP. In particular, the stability period of Extended SEP and Extended P‐SEP has improved up to 42% and 89%, respectively, compared to M‐SEP.

Light Weight Concurrent Scheduling of Mobile Sink routing protocol towards Minimization of Propagation Delay against Spatial and Temporal Uncertainties of Cluster based Wireless Sensor Network

Wireless Sensor Network highly exposed to certain security attacks due to various uncertainties of the network which lead to node compromise. Hence considerable attention has been made by researcher during scheduling of the mobile sink to data collection of sensed information from the sensor nodes. Many secure data aggregation mechanism has been proposed to withstand the network against these kind of attack. Despite of many advantageous, those architectures will lead to several limitations such as large propagation delay and high energy consumption and spatial and temporal uncertainties. In order to mitigate those challenges, Light Weight Concurrent Scheduling of Mobile Sink routing protocol towards Minimization of Propagation Delay against Spatial and Temporal Uncertainties of Wireless Sensor Network is designed. It should be capable achieving energy efficiency and collision avoidance due to uncertainty in transmission and reception. Proposed model eliminates the packet collision and poor channel utilization challenges. Initially, node is partitioned and cluster head is selected based on the highest energy density of the node in the particular location. Employing Full duplex channel easily examines the spatial and temporal characteristic of the node through utilization cache information of routing table. It further helps to build the light weight scheme with behavioral strategies of the nodes for secure propagation of the sensed data to the mobile sink. Light weight scheme deployed in mobile sinks estimate the node trustworthiness and simultaneously collects the secure aggregated data packets of the sensor node through cluster head against dynamic time slots concurrently .Comparing with traditional secure routing architecture, simulation results demonstrates that proposed architecture can reduce the propagation delay against various uncertainties and maximizes the life time of the network on increasing the networking performances with respect to packet delivery ratio, throughput and propagation delay. Finally proposed model obtains the cooperative communication of sensor node information to the base station through mobile sink on heterogeneous wireless sensor network environment. DOI: https://doi.org/10.52783/pst.387

Retraction Note: A novel energy-efficient scheduling method for three-dimensional heterogeneous wireless sensor networks based on improved memetic algorithm and node cooperation strategy

Retraction Note: A novel energy-efficient scheduling method for three-dimensional heterogeneous wireless sensor networks based on improved memetic algorithm and node cooperation strategy

Secure authentication and key management based on hierarchical enhanced identity based digital signature in heterogeneous wireless sensor network

Secure authentication and key management based on hierarchical enhanced identity based digital signature in heterogeneous wireless sensor network

LBAS: Load-Balancing Aware Clustering Scheme for IoT-Based Heterogeneous Wireless Sensor Networks

LBAS: Load-Balancing Aware Clustering Scheme for IoT-Based Heterogeneous Wireless Sensor Networks

Latency and Residual Energy Analysis of MIMO Heterogeneous Wireless Sensor Networks

Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized application of MIMO technology within WSNs. This approach operates effectively, especially in challenging and resource-constrained environments. By facilitating collaboration among sensor nodes, Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments. Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring, industrial automation, and healthcare applications. This research paper presents a comparative performance analysis of MIMO wireless sensor networks and traditional wireless sensor networks without MIMO using Network Simulator NS2.35 for analysis of End to End Delay for packet transmission and Residual energy of nodes. The research work shows application of MIMO in Wireless Sensor Networks with considerable improvements in Quality of Service parameters which is achieved through Spatial Multiplexing and Diversity Gain. MIMO enables multiple spatial streams, allowing several data streams to be transmitted simultaneously on the same channel. This increases the overall throughput as multiple sensors can transmit their data concurrently without interference. MIMO systems also provide diversity gain by transmitting multiple copies of the same data over different antennas which helps in mitigating the effects of fading and interference, resulting in a more reliable and higher-throughput communication link as compared to a SISO channel. Another advantage of employing MIMO in WSN is reduction in End-to-End delays in data transmission. Last but not the least, MIMO can be configured to optimize the power consumption of individual sensors by adjusting the number of antennas used and transmission power levels based on channel conditions. Hence, MIMO can help to extend the network's lifetime by conserving energy in resource-constrained sensor nodes by preservation of Residual Energy.

Novel AMI in Zigbee Satellite Network Based on Heterogeneous Wireless Sensor Network for Global Machine-to-Machine Connectivity

This study endeavored to enhance the efficiency and utility of microcomputer meters. In the past, their role was predominantly confined to remote meter reading, entailing high construction and communication transmission costs, coupled with subsequent maintenance and operational expenditures. These factors collectively impacted the enthusiasm of various stakeholders to invest in this realm. Hence, in alignment with the smart city development initiative, the natural gas industry has pioneered the establishment of an advanced metering infrastructure with heterogeneous wireless sensor networks (HWSNs) at its core. This visionary leap incorporates global machine-to-machine connectivity (G-M2MC) technology, interconnecting all facets of its operations, thereby positioning itself as a trailblazer within the industry. While advancing this endeavor, the project’s scheduling aligns with the enterprise’s sustainability goals in the early stages of digital transformation. This strategic allocation of resources is responsive to government policies and aspires to cultivate a digitally connected smart green energy hub, thereby expediting the transformation of the living environment. The objective is to provide a stable, secure, cost-effective, and reliable system that can be shared among peers. Furthermore, this study delved into the analysis of congestion avoidance in intelligent Zigbee satellite transport networks based on the HWSNs-GM2MC of non-synchronous satellite orbit system (NGSO) pivotal technologies, utilizing them to integrate the smart LNGas management system (SGMS). Concurrently, it developed application services through the smart meter application interface (SMAPI), distinct from conventional microcomputer meters. However, it is imperative to acknowledge that cloud computing, while processing sensitive data, grapples with issues of latency, privacy, efficiency, power consumption, and zero-trust security risk information management and ethical authority management capabilities in the defense of disaster relief responses.

Efficient configuration of heterogeneous multistatic sonar networks: A mixed-integer linear programming approach

The work undertaken in this paper pertains to the optimal spatial configuration of a heterogeneous Wireless Sensor Network (WSN) for the Area Coverage (AC) problem. Specifically, this research falls under the heading of Anti-Submarine Warfare (ASW) with an emphasis on active sonar systems and, more pointedly still, on a specific type of sensor: sonobuoys (portmanteau word formed by “sonar” and “buoy”). These buoys are further divided into three main categories: transmitter-only (Tx), receiver-only (Rx) and transmitter–receiver (TxRx). In this paper, we will therefore try to determine the geographical location of the different buoys comprising a Multistatic Sonar Network (MSN), special case of WSN, so as to maximize the overall surface area covered. To do this, we discretize an Area of Interest (AoI) into regular cells using bathymetric and altimetric data, and place a deployment position and a fictitious target at the center of each cell so that we can evaluate the network’s performance. More precisely, we are taking into account a limited number of sensors (buoys) with possible pairwise incompatibilities, variable performances, probabilistic detection models, an adverse masking effect (direct blast) as well as coastlines features. Finally, in order to solve this problem, we have developed several efficient Mixed-Integer Linear Programs (MILPs), all of which have been thoroughly tried-and-tested on a benchmark set of 100 instances derived from real elevation data. This has led us to identify an ideal model, i.e. one that is significantly better than all the others in the statistical sense.

Design and implementation of energy-efficient hybrid data aggregation in heterogeneous wireless sensor network

Heterogeneous wireless sensor network (HWSN) is a trending technology in both the industrial and academic sectors, consisting of a large number of interconnected sensors. However, higher energy consumption and delay are significant drawbacks of this technology in applications such as military, healthcare, and industrial automation. The main objective of this research is to enhance the energy efficiency of HWSN using a clustering technique. In this article, a novel approach, namely power optimization and hybrid data aggregation (POHDA), is proposed to address these challenges in HWSN. POHDA-HWSN focuses on power optimization and congestion avoidance through effective CH selection using hybrid data aggregation based on parameters such as residual energy, distance, mobility, threshold value of the node, and latency. By weight-based effective cluster head (CH) selection, the energy consumption, end-to-end delay, and overhead during communication are reduced in this network. The POHDA-HWSN approach considers specific parameters to compare the results and outcomes with earlier research such as HCCS-WSN, FMCA-WSN, and APCC-WSN. The results prove that the proposed POHDA-HWSN approach achieves higher energy efficiency and delivery ratio.

On Practical Reconstruction of Quality Virtual Backbones in Heterogeneous Wireless Sensor Networks With Faulty Nodes

On Practical Reconstruction of Quality Virtual Backbones in Heterogeneous Wireless Sensor Networks With Faulty Nodes

Energy-efficient cluster-based routing protocol for heterogeneous wireless sensor network

Energy-efficient cluster-based routing protocol for heterogeneous wireless sensor network

Heterogeneous Wireless Sensor Network Design with Optimal Energy Conservation and Security through Efficient Routing Algorithm

A heterogeneous wireless sensor network (H-WSN) comprises multiple sensor nodes having varied abilities, like diverse processing power and sensing range. H-WSN deployment and topology control seem to be more difficult than homogeneous WSNs. Research on H-WSNs has increased in the last few years to improve real-time sensor networks' reliability and deliver better networking services than a homogenous WSN does. When it comes to H-WSN's energy consumption and security, the major problem remains the efficient routing process. To that end, this research aims at demonstrating how an efficient routing algorithm of hierarchical H-WSN can greatly enhance the network's performance. It is important to note that the nodes' capabilities mostly determine the suitability of a given routing algorithm. Hence, the H-WSN design issues for routing in a heterogeneous environment are discussed in this paper. This research designs an Optimal Energy Conservation and Security-aware Routing Algorithm (OECS-RA) for H-WSN using clustering and a secure-hop selection scheme. In this proposed model, the optimal cluster head selection and routing have been found through various computational stages based on the energy conservation of each sensor node. It further secures the transmission by selecting the secured node with credential factor computation and comparing each hop of the optimal route. The MATLAB simulation scenario finds the significant performance of the routing mechanism with security compared to existing models. The proposed OECS-RA gives highly recognizable throughput, lifetime, energy efficiency, and reliability. With these results, this proposed algorithm is suggested for real-time implementation in the medical industry, transportation, education, business, etc.

Adaptive sleep scheduling in heterogeneous WSN using GWO for energy efficiency

Wireless Sensor Networks are instrumental in various domains, including environmental monitoring, healthcare, and industrial automation. Despite their ubiquity, the energy constraints of sensor nodes remain a pivotal concern. This research delves into energy conservation in WSNs by implementing Adaptive Sleep Scheduling using the Grey Wolf Optimizer (GWO) in the context of heterogeneous networks. Heterogeneous WSNs, characterized by nodes with diverse computational capacities and energy reservoirs, pose unique challenges for optimizing energy efficiency. The conventional static sleep scheduling strategies prove inadequate in accommodating this heterogeneity, often leading to suboptimal energy consumption. In this context, the application of GWO, an optimization algorithm inspired by the social behavior of grey wolves, offers a novel and promising approach to address the energy efficiency challenge. Heterogeneous WSNs necessitate tailored energy management strategies to optimize the utilization of resources. The disparity in the capabilities of sensor nodes, in terms of processing power and energy reserves, demands an adaptive solution for sleep scheduling to minimize energy consumption while maintaining the necessary data collection and transmission capabilities. This research demonstrates the significance of integrating GWO-based adaptive sleep scheduling in heterogeneous WSNs through extensive simulations and in-depth analysis. The proposed approach is compared with the LEACH, E-LEACH, and DEEC. The results show due to the use of GWO in adaptive sleep mechanisms in Heterogenous WSNs nodes die late as compared to other algorithms and energy consumption is also slow. So, in all one can say, GWO is a better approach in terms of energy efficiency and lifetime. quantity demand and investment in research and development, while the other model focuses on a more realistic relationship between the quantity demand and the price.

Energy Competent Clustering Algorithm for Minimization of Holes in Heterogeneous Wireless Sensor Networks

Energy Competent Clustering Algorithm for Minimization of Holes in Heterogeneous Wireless Sensor Networks

Energy competent clustering algorithm for minimisation of holes in heterogeneous wireless sensor networks

Energy competent clustering algorithm for minimisation of holes in heterogeneous wireless sensor networks

Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

Rao Algorithms-Based Structure Optimization for Heterogeneous Wireless Sensor Networks

Data Traffic Based Shape Independent Adaptive Unequal Clustering for Heterogeneous Wireless Sensor Networks

Data Traffic Based Shape Independent Adaptive Unequal Clustering for Heterogeneous Wireless Sensor Networks

Optimized Group-Centric Data Routing in Heterogeneous Wireless Sensor Networks for Enhanced Energy Efficiency

Wireless Sensor Networks (WSNs) are increasingly being utilized in environments where human presence is limited or dangerous. The main goal is to enhance the data processing capabilities of these components to extend the overall lifespan of the design. Researchers have explored conventional energy-saving methods to address the energy constraints of sensor nodes. However, it became clear that traditional routing methods, specifically those based on packet grouping, were inadequate. The proposed system, known as Optimized Group-Centric Data Routing (OGC-DR), introduces an efficient method of data routing by utilizing the concept of grouping nodal points. This approach enhances data routing management by differentiating between routing within a nodal group and routing between adjacent nodal groups. Group Heading Nodes (GHN) are assigned to each group of sensory nodes according to fitness criteria. The implementation of a tree-based routing structure improves data routing by creating a meeting-zone and strategically selecting intermediary nodes between the source and destination node. To improve data privacy, a sender and receiver engage in an asymmetric secret-key exchange at nodal points. Data is then directed to its ultimate destination via predetermined intermediary nodes and Group Heading Nodes. Simulations of the proposed method indicate several advantages, such as lower end-to-end delays, reduced energy consumption, higher active node count, and enhanced packet delivery rates. Furthermore, it improves data privacy for all communication within the sensory architecture.

Dominating Sets-Based Approach for Maximizing Lifetime of IoT-Based Heterogeneous WSNs Enabled Sustainable Smart City Applications

Dominating Sets-Based Approach for Maximizing Lifetime of IoT-Based Heterogeneous WSNs Enabled Sustainable Smart City Applications

Improved Security-Based Model for Heterogeneous Wireless Sensor Networks Using the Dispense Incline Drop Algorithm

Numerous real-time applications rely on heterogeneous wireless sensor networks (HWSNs), including the Internet of Vehicles (IoV), Internet of Sensors (IoS), medical applications, and so on. Due to the restricted computational capacity, memory, and connectivity of wireless nodes, it is essential to establish authentication techniques that consume less energy, yet guarantee strong security. It takes a lot of time and energy to construct trust models between sensor devices that can recognize and differentiate between benign and malicious attackers, which, in turn, reduces the detection rate and increases overhead. This article suggests a hybrid forewarn approach based on improved security to attain this degree of safety in HWSN communication called the Improved Security-based hybrid forewarn model (ISBHF) and the Dispense Incline Drop Algorithm. It is recommended to offer a trust score and evaluations for messages and knowledge transfer to improve detection capabilities against attackers targeting essential data transmission. To further minimize packet loss, a reliability secure measure is created, and a weighted averaging strategy is implemented to ensure the robustness and veracity of the secure scores. Furthermore, empirical evidence from measurements and simulations will demonstrate that unsecured paths of communication are key to identifying fraudulent nodes that are causing an outsized fraction of network traffic or data breaches. The suggested protocol is superior to the current approach in terms of efficiency and security, making it ideal for use in HWSN networks by decreasing communication overhead, increasing detection performance, and other parameters such as packet delivery ratio and connectivity ratio.