Dual Cluster Heads Research Articles

ALGORITHME DE CLUSTERING AGGLOMÉRATIF BASÉ SUR MOJO AVEC STRATÉGIE EDMT POUR LES RÉSEAUX DE CAPTEURS SANS FIL À GRANDE ÉCHELLE

The wireless sensor network (WSN) is a distributed sensor network that monitors and stores environmental data wirelessly by connecting dispersed sensor nodes. Since wireless sensor nodes rely on batteries for energy, energy consumption, and limitations are considered fundamental problems. A novel multi-objective jellyfish optimization based on energy, degree, distance, mobility, and time parameters (MOJO-ED2MT) technique has been proposed to overcome these challenges. Three phases are involved in the proposed method: selection of cluster heads, compression of data, and routing of the data. In this first phase, a fuzzy agglomerative clustering algorithm is employed to choose an optimal dual cluster head from inter-cluster and intra-cluster. In the second phase, a neighborhood indexing sequence (NIS) algorithm can compress the number of bits in the data before it is transmitted. In the third phase, jellyfish optimization selects the shortest path based on multi-objective parameters. The simulation analysis and result statistics show that the suggested MOJO-E MT approach performs better than the state-of-the-art algorithms across various performance measures. The proposed MOJO-E MT framework achieves 11.5, 15.4 %, and 17.99 % more network lifetime than EOR-iABC, C3HA, and ML-AEFA algorithms.

Multi-Objective ED2MT Strategy-based Clustering Algorithm for Large Scale WSN

Wireless Sensor Networks play a crucial role in everyday life, providing a wide range of networking structures to develop real-time applications. Energy consumption is limited by WSN devices, so reducing the energy consumption of malicious nodes is crucial to improving network performance. A main concern of WSNs from an application perspective is the prolonged lifetime of the network and reduced energy usage. To overcome these challenges a novel multi-objective ED2MT (Energy, Distance, Degree, Mobility, Time) driven strategy has been proposed which consists of three phases namely dual Cluster Head Selection, data compression, and routing. In the first phase, the proposed ED2MT uses a Fuzzy C-Means (FCM) clustering algorithm to select dual Cluster Head (CH) which has been performed in two stages, namely Inter-Cluster and Intra-Cluster. In the second phase, a Neighborhood Indexing Sequence (NIS) technique is utilized to compress the number of bits in the data before it is transmitted. In the third phase, a multi-objective shortest-path routing algorithm is utilized for route selection. The performance of the ED2MT method has been evaluated using network lifetime, delay, throughput, alive nodes, energy efficiency, and packet delivery ratio to provide a better result. The proposed ED2MT framework achieves 20.55%, 18.4%, and 15.2% more residual energy than C3HA, CAFL, and DHSCA algorithms.

A Combined Dual Leader and Relay Node Selection for Markov Cluster Based WSN Routing Protocol

The major challenge in Wireless Sensor Networks (WSNs) is to increase the node’s lifespan and decrease energy utilization. To avoid this issue, many Clustering Routing Protocols (CRPs) have been developed, where Cluster Head (CH) in each cluster accumulates the data from each other node and transfers it to the sink through Relay Nodes (RNs). But both CHs and RNs dissipate more energy to aggregate and transfer data. As a result, it is vital to choose the appropriate CHs and RNs concurrently to reduce energy utilization. Hence, this article proposes a Weighted Markov Clustering with Dual Leader and Relay node Selection based CRP (WMCL-DLRS-CRP) in WSNs. This protocol aims to lessen energy dissipation during inter- and intra-cluster communication. Initially, a Markov Clustering (MCL) algorithm is applied by the sink to create nodes into clusters based on a threshold distance. Then, a dual leader selection scheme is proposed to elect dual CHs in each cluster according to the node weighting factor that considers the node’s remaining energy, the distance between CHs and sink, the distance among all nodes, and abundance. Also, an RN selection scheme is proposed to choose the appropriate RNs based on a new Predicted Transmission Rate (PTR) factor. Moreover, the elected RNs transfer the data from the CHs to the sink, resulting in a tradeoff between the node’s energy utilization and lifetime. At last, extensive simulations illustrate that the WMCL-DLRS-CRP achieves better network performance compared to the existing protocols.

Survivability Analysis of Unmanned Aerial Vehicle Network based on Dynamic Weighted Clustering Algorithm with Dual Cluster Heads

The unmanned aerial vehicles (UAVs) network is vulnerable due to the high mobility and energy-constrained characteristics of UAVs. Nonetheless, as a UAV-based communication network, a stable network topology is crucial for efficient communication. To this end, in this paper, we propose a dynamic weighted clustering algorithm with dual cluster heads (DWCA-DCH) in this paper to deploy the UAV network. To trade off communication efficiency and lifetime, the selection of prime and backup cluster heads is designed by synthetically considering communication quality and remaining energy of the UAV. Furthermore, a survivability analysis method based on Markov process (SAM-MP) is constructed to analyze the survivability performance of the proposed UAV network based on DWCA-DCH when the UAV node suffers from energy exhausting or accidents. The simulation results show that the survivability and stability of the UAV cluster ad hoc network based on DWCA-DCH proposed in this paper is improved by about 35% compared with the single cluster head network.

A detection probability guaranteed energy-efficient scheduling mechanism in large-scale WSN

In intrusion detection wireless sensor network (WSN), ensuring detection performance and prolonging network lifetime are two equally important but contradictory pursuits. In this paper, we propose a node scheduling scheme jointly considering the detection probability, energy consumption, and energy balance to ensure the detection performance and maximize the network lifetime. We mathematically transform the scheduling process into an optimization problem and further propose a novel mechanism called greedy-like step-by-step trimming heuristic algorithm (GLSTA) to obtain the optimal task nodes set. By gradually trimming unnecessary nodes, GLSTA intelligently eliminates redundancy and obtains a task set that can save energy and balance the residual energy of nodes. Moreover, we propose a dual cluster head (OCH-DCH, organization cluster head-data cluster head) scheme to realize the smooth update of the cluster due to the target movement. Simulation results show that the rounds of half nodes death of GLSTA are extended by at least 28.6% compared with existing mechanisms.

DC-LEACH: A unique cluster head selection algorithm with improved QoS in real time applications for WSN

The Wireless sensor network incorporates high density tiny sensor nodes. These sensor nodes are placed in the mission critical areas where human intervention becomes difficult. Sensor nodes run through the disadvantage of limited battery life because of which they die out in the network. There are several techniques to make these sensor nodes to stay for longer period; Out of this clustering is widely used practice. The LEACH clustering technique is one of the simple protocols to study upon improvement of network lifetime. All nodes get a chance to become a cluster head which aggregate data within the cluster and send data to the base station. This paper presents the selection of dual controller cluster heads. The selection is done on the basis of the first highest and the second highest energy node, these dual controllers are selected for transmission and reception which is based on residual energy in each round. The nodes are made alternatively on and off, so that the round time for selection increases. When both controller nodes have energy value less that threshold values the round occurs. The simulation result shows increase in the time required for the last node to die. The proposed method extended the network lifespan and hence QoS using the unique dual controller approach.

Dual Cluster Head Optimization of Wireless Sensor Networks Based on Multi-Objective Particle Swarm Optimization.

Energy conservation is one of the main problems in a wireless sensor network (WSN). Compared with a single cluster head (CH), a dual CH optimization was proposed for less energy consumption by the WSN and an acquisition delay by the mobile sink (MS). Firstly, a fuzzy c-means clustering algorithm and a multi-objective particle swarm optimization were utilized for the determinations of the first and second CHs. Following that, the ideal trajectory of MS was assessed using the improved ant colony algorithm. Finally, the lifetimes, the death rounds of the first node and the 50% node, and the number of packets received at the base station were compared among the proposed approach. Moreover, five algorithms were compared to validate the optimization, and the improved trajectory was compared with the original one as well. It was found that, for 100 nodes, the number of dead rounds from the proposal increased by 7.9%, 22.9%, 25.1%, 61%, and 74.4% for the first node, and that of the 50% nodes increased by 27.8%, 34.2%, 98.3%, 213.1%, and 211.2%, respectively. The base station packet reception increased by about 19.3%, 53.5%, 27%, 86.8%, and 181.2%, respectively. The trajectory of MS could also decrease by about 10%.

A Dual Cluster-Head Energy-Efficient Routing Algorithm Based on Canopy Optimization and K-Means for WSN

Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent battery replacement is not feasible. Therefore, it is important to reduce the energy consumption of sensors and extend the network lifetime. An effective way to achieve this is clustering. This paper proposes a dual cluster-head energy-efficient algorithm (DCK-LEACH), which is based on K-means and Canopy optimization. Considering that the K-means algorithm is sensitive to the location of the initial clustering centers, this paper uses both the dynamic Canopy algorithm and K-means algorithm for clustering. For cluster-head election, this algorithm uses a hierarchy to minimize the cluster-head burden and balance the network load. The primary cluster-head is selected by two objectives: the node's residual energy and the distance from the node to the clustering center. The vice cluster-head is selected by the residual energy of the node, and the distance from the nodes to the base station. Simulator results show that DCK-LEACH significantly prolongs the energy-critical node lifetime and the network lifetime compared with existing protocols.

Retraction Note to: Bio-inspired dual cluster heads optimized routing algorithm for wireless sensor networks

Retraction Note to: Bio-inspired dual cluster heads optimized routing algorithm for wireless sensor networks

Weighted Boost Spearman Correlative Dual Cluster Head for Robust Transmission in Wsn

Wireless Sensor Networks (WSNs) are widely used in various applications, but they are often subject to environmental factors that result in poor network performance and packet loss. To address this challenge, correlation-based routing algorithms have been proposed. However, the performance of these algorithms degrades when the correlation between nodes is low. In this paper, we propose a Weighted Boost Spearman Correlative Dual Cluster Head (WBSCDCH) approach for robust transmission in WSNs. The proposed approach uses weighted boosting to assign higher transmission power to cluster heads with low correlation and utilizes dual cluster heads for efficient data collection and transmission. Our simulation results show that the proposed approach outperforms existing algorithms in terms of packet delivery ratio, energy consumption, and end-to-end delay. This paper contributes to the field of WSNs by providing a novel approach for improving the robustness of data transmission in WSNs.

Low‐Energy Secure Routing Protocol for WSNs Based on Multiobjective Ant Colony Optimization Algorithm

As one of the three pillars of information technology, wireless sensor networks (WSNs) have been widely used in environmental detection, healthcare, military surveillance, industrial data sampling, and many other fields due to their unparalleled advantages in deployment cost, network power consumption, and versatility. The advent of the 5G standard and the era of Industry 4.0 have brought new opportunities for the development of wireless sensor networks. However, due to the limited power capacity of the sensor nodes themselves, the harsh deployment environment will bring a great difficulty to the energy replenishment of the sensor nodes, so the energy limitation problem has become a major factor limiting its further development; how to improve the energy utilization efficiency of WSNs has become an urgent problem in the scientific and industrial communities. Based on this, this paper researches the routing technology of wireless sensor networks, from the perspective of improving network security, and reducing network energy consumption, based on the study of ant colony optimization algorithm, further studies the node trust evaluation mechanism, and carries out the following research work: (1) study the energy consumption model of wireless sensor networks; (2) basic ant colony algorithm improvement; (3) multiobjective ant colony algorithm based on wireless sensor routing algorithm optimization. In this study, the NS2 network simulator is used as a simulation tool to verify the performance of the research algorithm. Compared with existing routing algorithms, the simulation results show that the multiobjective ant colony optimization algorithm has better performance in evaluation indexes such as life cycle, node energy consumption, node survival time, and stability compared with the traditional algorithm and the dual cluster head ant colony optimization algorithm.

Quantitative survivability analysis using probability model checking: A study of cluster-based vehicle networks with dual cluster heads

As an important part of future 5G wireless networks, a vehicular network demands safety, reliability and connectivity. In this context, networking survivability is usually considered an important metric to evaluate network performance. In this paper, we propose a survivability model for vehicle communication networking based on dual cluster heads, wherein a backup cluster head (CH) will be activated if the primary CH fails, thereby effectively enhancing the network lifetime. Additionally, we introduce a software rejuvenation strategy for the prime CH to further improve the survivability of the entire network. Using the Probabilistic Symbolic Model Checker (PRISM), we verify and discuss the proposed survivability model via numerical simulations. The results show that network survivability can be effectively improved by introducing an additional CH and further enhanced by adopting the software rejuvenation technique.

RETRACTED ARTICLE: Bio-inspired dual cluster heads optimized routing algorithm for wireless sensor networks

The optimal usage of scarce and inadequate resources is the current need of wireless sensor networks (WSNs). Reducing power consumption and increasing WSN’s lifetime can contribute to this. Energy-efficient algorithms should be proposed for effective routing, as a lot of energy is consumed during the communication between sensor nodes. A principal practice followed to bring down energy consumption is, combining together in-network data aggregation and standardized routing. Numerous conventional data aggregation algorithms exist, and each of these have their own disadvantages like delayed delivery of packets, time constraints, or high costs. The most suitable solution can therefore be achieved via optimization alone. The current research seeks to address these challenges faced in the wireless network by using the dual-cluster heads technique based on Krill Herd Optimisation (DC-KHO) Routing algorithm. Since the existing wireless routing approaches choose a random path for data transmission, the end- to- end delay, which is directly proportional to energy consumption, is high. So, the current study chooses an optimized path by calculating its path trust value using the devised krill herd maximization algorithm. The proposed DC-KHO algorithm is energy- efficient, and invariably amplifies the network’s lifetime. The study’s results reveal the ability of the proposed method in overcoming the challenges faced in transmission time, residual energy and computational time. Further, the method increases the life span of the network by 64.58%, when a 9 V battery is used for the nodes.

Threshold Driven Energy-Efficient and Scalable Dual Cluster Head Protocol

In WSN cluster-based routing approach is a major step in the direction of energy efficiency. However, research shows that energy dissipation in a cluster-based approach predominantly occurs in two cases; first during data transmission to the base station and second during data fusion/aggregation. Eventually, this leads to sizable energy dissipation, the early death of CHs and results in lower network lifetime. Moreover, in most of the recent proposed works, it is never assured that an individual node selected as a Cluster-Head would perform all the assigned tasks without dying in the process. Thus to address these problems, a new approach is proposed in this paper, where two cluster-heads (CHs) in every cluster are selected; first cluster-head being used for data aggregation (Primary-CH) and second for data transmission (Secondary-CH), which assists in reducing the burden of a single Cluster Head. Along with the dual Cluster-Heads, another key feature adopted in this paper is the Energy Threshold values for PCH and SCH. These Energy Thresholds for different CHs calculates the minimum energy required by a node to perform all the tasks assigned to it when elected as CH. So, while electing Primary Cluster-Head (PCH) and Secondary Cluster-Head (SCH) along with other criterions energy threshold values for PCH (EPO) and energy threshold values for SCH (ESO) are also used. Any node with remaining energy less than that of energy thresholds would never be considered for Cluster-Heads. Therefore, by employing the above-mentioned criterions, this article proposes a new protocol that uses dual heads and assists in enhancing the network life of a network as compared to LEACH protocol.

An Energy-Efficient Clustering Routing Protocol for Wireless Sensor Networks Based on AGNES with Balanced Energy Consumption Optimization.

To further prolong the lifetime of wireless sensor network (WSN), researchers from various countries have proposed many clustering routing protocols. However, the total network energy consumption of most protocols is not well minimized and balanced. To alleviate this problem, this paper proposes an energy-efficient clustering routing protocol in WSNs. To begin with, this paper introduces a new network structure model and combines the original energy consumption model to construct a new method to determine the optimal number of clusters for the total energy consumption minimization. Based on the balanced energy consumption, then we optimize the AGglomerative NESting (AGNES) algorithm, including: (1) introduction of distance variance, (2) the dual-cluster heads (D-CHs) division of the energy balance strategy, and (3) the node dormancy mechanism. In addition, the CHs priority function is constructed based on the residual energy and position of the node. Finally, we simulated this protocol in homogeneous networks (the initial energy = 0.4 J, 0.6 J and 0.8 J) and heterogeneous networks (the initial energy = 0.4–0.8 J). Simulation results show that our proposed protocol can reduce the network energy consumption decay rate, prolong the network lifetime, and improve the network throughput in the above two networks.

Dual Cluster Head Routing Protocol with Super Node in WSN

This paper introduces dual cluster head routing protocol with super node (DCHRP4) having dual cluster head with four level of heterogeneity to improve the lifetime of a wireless sensor network. The main objective is to reduce the number of selection of cluster head so that the energy consumption can be minimized. In a clustering based sensor network cluster head does all the work from collecting to transmitting data to sink. Therefore, Cluster head loses its energy very fast. Energy plays an important role in efficient management of sensor network. Due to the handling of multiple tasks, energy of a cluster head is lost very fast. So, the paper focuses on reduces the energy consumption, improving the stability, the lifetime of the network, and throughput. From the simulation performed it is observed that the stability period of DCHRP4 upgrade 56.11% over enhanced threshold sensitive stable election protocol (ETSSEP) and twice and more than thrice over threshold sensitive stable election protocol (TSEP) and stable election protocol (SEP) respectively. The overall lifetime of DCHRP4 also upgrade by 8.29% and 49.22% over ETSSEP and TSEP respectively whereas about thrice in comparison with SEP. The throughput improved by 7.75% over ETSSEP, twice over TSEP and SEP respectively.

Zone-based dual sub sink for network lifetime maximization in wireless sensor network

Wireless sensor network (WSN) consists of large number of tiny sensor nodes connected through wireless network. The major challenge of WSN is to ensure lifetime extension of sensor nodes, as they are battery powered. Static or mobile sinks are deployed for data acquisition from these sensor nodes. Nodes near the sink are responsible to relay data from other nodes, raising the possibility of energy wear out of these nodes. This paper discusses on the extension of lifetime of sensor nodes that are near the trajectory of the mobile sink, in particular considering navigation in fixed trajectory. Energy efficient zone-based dual sub sink protocol with dual cluster head is developed to schedule the data transmission of these relay nodes with mobile sink. The hybrid adaptive time synchronization method minimizes collision during data transfer between clusters and helps to improve the throughput of the network. It is proved from simulation and real time experiments that the proposed protocol outperforms the existing techniques in terms of energy utilization and throughput.

SDN Enabled 5G-VANET: Adaptive Vehicle Clustering and Beamformed Transmission for Aggregated Traffic

With the anticipated arrival of autonomous vehicles, supporting vehicle generated data traffic due to the dramatically increased use of in-vehicle mobile Internet access will become extremely challenging in 5G-based vehicular networks. This is mainly due to the high mobility of vehicles on the road and the high complexity of 5G HetNets. In order to support the increasing traffic and improve Het- Net management, an SDN enabled 5G VANET is proposed in this article, where neighboring vehicles are clustered adaptively according to real-time road conditions using SDN's global information gathering and network control capabilities. With proposed dual cluster head design and dynamic beamforming coverage, both trunk link communication quality and network robustness of vehicle clusters are significantly enhanced. Furthermore, an adaptive transmission scheme with selective modulation and power control is proposed to improve the capacity of the trunk link between the cluster head and base station. With cooperative communication between the mobile gateway candidates, the latency of traffic aggregation and distribution is also reduced. Computer simulation results show that the proposed design substantially improved 5G users' bit error rate and trunk link throughput rate.

Dual Cluster Head Algorithm for Proficient Routing in Wireless Sensor Networks

Objectives: In cluster based algorithms, the group head needs to do the transmission, gathering, aggregation, collection and the timing administration. Due to this the head of the cluster will lose its energy rapidly and another head ought to be found. A new election process creates unwelcome control message movement in that particular network. The main objective is to reduce the number of elections hence the wastage of energy can be minimized. Methods/Statistical Analysis: To reduce the number of election we propose our model Dual Cluster Head Protocol (DCH). The key idea is to have a group head and sub group head, where the work load will be shared between them. The sub head will perform the information gathering and aggregation inside the cluster and it will report just to the main cluster head. The clusters will be managed by the Sub-Cluster Head (SCH) node, but the session management will be carried out by the cluster head. All the outward communications will be carried out by main cluster head; also it relays the information from other heads. Findings: Our algorithm uses lesser amount of control messages than other conventional algorithms since the number of cluster head re-elections is reduced. The performance of the algorithm matches with protocols like LEACH and SEECH. We have used 3 scenarios for testing the protocol; in the first scenario with 100 nodes DCH protocol performed 31% better than SEECH and 86% better than LEACH. In second scenario with 400 nodes DCH protocol performed 6% better than SEECH and 20% better than LEACH. In third scenario with 1000 nodes DCH protocol performed 38% better than LEACH but fell short of 45% when compared with SEECH. Application/Improvements: Right now the algorithm performs well in low and medium density sensor fields. It can be improved to work efficiently in high density sensor fields. The comparison can be made with newer protocols like HEED

Energy Efficient Wireless Sensor Networks using Dual Cluster Head with Sleep/Active Mechanism

Objectives: In wireless sensor networks, high energy consumption occurs when the generated data is transmitted to the base station. This high energy consumption affects the longevity of the network. In a wireless sensor network, the energy of sensor nodes is a scarce resource. To extend the lifetime of wireless sensor network, it is essential to reduce the energy consumption. Methods/Statistical Analysis: In the proposed work, the classical LEACH protocol clustering algorithm is enhanced with sleep/active schedule and a new algorithm namely ESDCH (Energy Saving Dual-Cluster Head) protocol is proposed to prolong the network lifetime. In the proposed ESDCH method, the sensor nodes are organized into clusters. The sensor nodes in each cluster set their states into sleep/active mode based on their residual energies. In lieu of selecting a single cluster-head, our protocol selects two cluster heads in each cluster based on their residual energies. Firstly, a Primary-CH is chosen which is having the highest energy level, and a Secondary-CH is chosen from the remaining nodes which is having energy level next to Primary-CH and also closer to the Primary-CH. Because of wireless transmission capability, Primary-CH is able to receive data from other sensor nodes. Using multi-hop communication, every Primary-CH can aggregate data within each cluster and send the aggregated data to the base station. The Secondary-CH assumes the role of CH whenever the Primary-CH fails in its purpose. The entire simulations are carried out using MATLAB environment. Findings: The performance results obtained using ESDCH and the LEACH protocols are matched and the superiority of ESDCH performance is evaluated. From the simulation results, we show that the proposed protocol marginally reduces the total energy consumption in the network. Also, the simulation results show that the number of live nodes in the network is increased, packet transmission delay reduced and packet delivery rate increased in the proposed method. Application/ Improvement: In the newly introduced dual cluster head protocol, it would be shown that the energy consumed is much less and hence the network’s lifetime is increased.