Hierarchical Routing Protocol Research Articles

Performance and QoS Assessment in WSN: Comparative Analysis of MBC, ECHERP, and PDCH Routing Methods

Objective: The objective of this research is to assess the performance and Quality of Service (QoS) provided by PDCH when compared with ECHERP and MBC routing protocols(RPs) within Wireless Sensor Networks (WSNs). Methods: Utilizing the NS2 Simulator, this paper provides an in-depth exploration of three hierarchical RPs viz. Equalized Cluster Head Election RP (ECHERP), Mobility Based Clustering (MBC), and PDCH (PEGASIS with Double Cluster head). A thorough examination of each protocol's performance is conducted, focusing on a range of QoS metrics such as Energy Consumption, Packet Drop Ratio, Throughput, and Delay. Findings: A comparative assessment is conducted between PDCH, ECHERP, and MBC, extracting QoS parameters. The examination and findings reveal that PDCH exhibits superior performance over ECHERP by 26.15%, 20%, 15.71%, and 37.73%. Similarly, PDCH outperforms MBC by 23.19%, 14.29%, 4.87%, and 15.13% across the mentioned parameters. Novelty: In this simulation, the NS2 software is utilized, with a specific emphasis on the suggested parameters. These metrics are crucial for evaluating the overall performance of different RPs in Wireless Sensor Networks (WSNs).

Performance Analysis of LEACH, SEP and Z-SEP Protocols in Heterogeneous Wireless Sensor Network

Wireless sensor networks use thousands of sensors to monitor the physical environment. This sensor node consumes a limited amount of energy since it is battery-powered. Researchers regularly develop energy-efficient routing protocols to extend the lifetime of WSNs. The threshold-based cluster head (CH) selection techniques used by hierarchical routing protocols have been shown to extend network lifetime in many studies. Through the implementation of several routing protocols, sensor networks can be made to last longer and consume less energy. Z-SEP introduces a new heterogeneous routing protocol using a hybrid communication mechanism. Others use clustering mechanisms, while others use the base station directly. Energy efficiency and stability are improved by 11% and 19%, respectively, over Z-SEP

Energy efficient gateway based routing with maximized node coverage in a UAV assisted wireless sensor network.

Ad-hoc wireless sensor networks face challenges of optimized node deployment for maximizing coverage and efficiently routing data to control centers in post disaster events. These challenges impact the outcome for extending the lifetime of wireless sensor networks. This study presents a uav assisted reactive zone based EHGR (energy efficient hierarchical gateway routing protocol) that is deployed in a situation where the natural calamity has caused communication and infrastructure damage to a major portion of the sensor network. EHGR is a hybrid multi layer routing protocol for large heterogeneous sensor nodes (smart nodes, basic nodes, user handheld devices etc.) EHGR is tailored to meet two important concerns for a disaster hit wsn ie. optimized deployment and energy efficient routing. The first part of EGHR focuses on maximized coverage during node deployments. Maximized coverage is an important aspect to be considered during the event of disaster since most of the nodes loose coverage and are detached from the wireless sensor network. The first part of EHGR uses state of the art game theory approach to build a model that maximizes the coverage of nodes during the deployment phase from all participating entities i.e. nodes and uavs. Rather than fixing the cluster head as is the case in traditional cluster-based approaches EHGR uses the energy centroid nodes. Energy centroid nodes evolve on the basis of aggregated energy of the zone. This approach is superior to simply electing cluster head nodes on the basis of some probability function. The nodes that fail to achieve any successful outcome from the game theory matching model fail to get any association. These nodes will use multi hop d2d relay approach to reach the energy centroid nodes. Gateway relay nodes used with the game theory approach during the deployment of the uav assisted wsn improves the overall coverage by 25% against traditional leach based hierarchical approaches. Once the optimum deployment phase is completed the routing phase is initiated. Aggregated data is sent by the energy centroid nodes from the ECN nodes to the servicing micro controller enabled un manned aerial vehicles. The routing process places partial burden of zone formation and data transmission to the control center for each phase on the servicing uavs. Energy centroid nodes engage only in the data aggregation process and transmission of data to servicing uav. Servicing-uavs reduce energy dissipated of the entire zone which result in gradual decrease of energy for the zone thus increasing the network lifetime. Node deployment phase and the routing phase of EHGR utilize the computations provide by the mirco controller enabled unmanned aerial vehicles such that the computationally intensive calculations are offloaded to the servicing uav. Experiment results indicate an increase in the first dead node report, half dead node report, and last dead node report. Network lifetime is extended to approximately 1800 rounds which is an increase by ratio of 100% against the traditional leach approach and increase by 50% percent against the latest approaches as highlighted in the literature.

Effect of Energy-Efficient Routing for Packet Splitting using Chinese Remainder Theorem (CRT) for Wireless Sensor Networks (WSNS)

The most popular Wireless Sensor Network (WSN) protocol utilized for energy optimization of WSN nodes is the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, which is a basic energy-efficient routing protocol of hierarchical routing protocol’s family, where the sensor nodes remain static. There is a need to extend the lifetime with respect to reducing the energy consumption of nodes, and this was accomplished using the Chinese Remainder Theorem (CRT. In this research large data packets are broken into smaller packets. The focus of the study is to develop an energy routing for splitting packets in Wireless Sensor Networks (WSNs) using Chinese Remainder Theorem (CRT) techniques. A further improvement in WSN lifetime is by utilizing fuzzy logic. Factoring node parameters such as residual energy of nodes, their centrality within clusters, and their distance to the base station and improving upon the selection of nodes as cluster heads are required. The developed application can be used to reduce the communication cost of Energy efficiency of WSN. The forwarding technique for this research is to split the packet sent by the source node of a WSN so that the maximum number of bits per packet that a node has to transmit is significantly minimized.

Computational intelligence techniques for energy efficient routing protocols in wireless sensor networks: A critique

AbstractWireless Sensor Networks (WSNs) play a pivotal role in modern data acquisition systems, but their energy‐efficient operation remains a significant challenge. This work provides a concise overview of the key challenges and proposed solutions discussed in the context of energy‐efficient routing protocols for WSNs based on a systematic literature review. The need for fault tolerance to ensure network resilience is vital, given the limited resources and environmental challenges faced by sensor nodes. This work emphasizes the importance of addressing several open research questions, including the integration of diverse topologies, cross‐layer routing, and the use of multiple mobile sinks. Additionally, it highlights the need for QoS‐aware routing for real‐time applications, mathematical modeling for protocol evaluation, and the challenges of testing routing protocols on real hardware. Furthermore, this article suggests leveraging the RPL routing protocol with the Node‐based Metric RNE for enhanced energy efficiency and explores the promising field of hierarchical routing protocols, exemplified by the LEACH protocol and its variants. This work serves as a roadmap for researchers and practitioners, identifying critical challenges and proposing directions for future research to achieve energy‐efficient routing protocols in WSNs, ultimately enabling effective communication in resource‐constrained environments.

Clustering Algorithms and Optimization Strategies in WSNs: A State-of-the-Art Review

Wireless Sensor Networks (WSNs) have emerged as a groundbreaking technology for collecting data on various physical phenomena, offering the potential to revolutionize infrastructure systems. The paper provides an exhaustive exploration of the existing literature on clustering algorithms within WSNs and the diverse optimization techniques proposed for cluster head selection. A comprehensive analysis of various routing protocols, mobility-based solutions, and energy conservation strategies is presented, shedding light on their respective strengths and limitations. The examination encompasses a wide spectrum of approaches, including hierarchical cluster-based routing, mobile sensor integration, and energy-efficient techniques inspired by industry standards like ZigBee. The paper further explores ecological monitoring applications, redundancy reduction mechanisms, and power- efficient hierarchical routing protocols, offering valuable insights into their contributions to the field. This review paper aims to consolidate and synthesize the wealth of knowledge in the domain of clustering algorithms and optimization techniques for WSNs. By assessing the strengths and weaknesses of these methodologies, it seeks to provide a comprehensive resource for researchers and practitioners in the field, ultimately contributing to the advancement of energy-efficient and reliable wireless sensor networks. Keywords— APTEEN, EARP, ECCP, GPS, HEED, LEACH, PEGASIS, TEEN, WSN.

Trust management based multidimensional secure cluster with RSA cryptography algorithm in WSN for secure data transmission

WSNs are now widely used for information gathering and transmission using WSN. Due to its low cost and simple communication, this type of network is widely used in many applications. Although hierarchical routing protocols may handle a variety of applications, choosing a Cluster Head (CH) and balancing network overload are difficult problems. This recommended strategy provides LEACH Protocol based on Novel Trust Management with Cryptographic RSA algorithm (NTM-LEACH-RSA) to extend the lifetime of network and to consume less energy. Here the proposed methodology includes two aspects for improving Security in WSN. Using the suggested NTM-LEACH technique, cluster formation and cluster head election are carried out in the first phase. Here, the threshold function value, the distance and density between nearby nodes, and the trust value are used to elect the cluster head. Based on the energy domain and the distance domain, the threshold function value is estimated in this case. The RSA cryptography technique is employed in the second phase to protect data transmission and guarantee data integrity. By using simulation tools, the proposed NTM-LEACH-RSA methodology's performance analysis is estimated. In comparison to other algorithms currently in use, it also offers higher performance results.

The measurement and monitoring of Quality of service based on security analysis in wireless sensor network using deep learning architecture

Wireless sensor networks comprise of unattended little sensor hubs having low energy and low scope of correspondence. Machine learning has demonstrated its effectiveness in creating proficient cycles to deal with complex issues in different organization perspectives. This exploration propose novel procedure in wireless sensor network routing and security improvement by network observing utilizing profound learning model. The organization routing is done utilizing cluster based scalable hierarchical energy routing protocol (CSHERP) and the organization checking is completed utilizing fuzzy Boltzmann adversarial learning (FBAL). This routing protocol adopts an information driven strategy, with moderate hubs collecting information and sending it to a sink hub. The arrangement gave is valuable to additional investigation of expanded WSN networks. The trial examination is completed as far as energy efficiency, throughput, end-end delay, latency, QoS. The proposed technique attained energy efficiency of 96%, throughput of 91%, end-end delay of 86%, latency of 85%, QoS of 96%.

An Efficient Routing Awareness Based Scheduling Approach in Energy Harvesting Wireless Sensor Networks

Wireless sensor networks (WSNs) have emerged as a promising technology for various Internet of Things (IoT)-based sensing applications. Generally, sensor nodes are powered by non-rechargeable and low-capacity batteries; they only last for a small amount of time. Due to their dispersed nature, sensor nodes cannot have their batteries replaced or maintained locally. The energy harvesting (EH) concept shows commitment as a method for addressing the current energy shortage. Another problem is the intra-energy control of various network load functions, including coverage preservation, routing, clustering, etc. This study proposes an ERAS (efficient routing awareness scheduling) algorithm to address the abovementioned issues. The ERAS method employs a solar harvesting system as a hierarchical clustering-based routing protocol. The presented scheme dynamically alters nodes between states and adjusts to new states based on the insides of sensed data packets. Synchronization-based scheduling ensures proper coordination between the cluster head (CH) and cluster members (CMs). It selects the CH based on both remaining and harvested energy and the number of active nodes to improve throughput. Surprisingly proposed EASR algorithm performs efficiently while considering various performance matrices, including network lifetime, packet delivery ratio, energy consumption, and network sustainability. Extensive simulation results exhibit the network lifetime of the proposed ERAS technique (79.8%) compared to ERA, SEED and CREST methods as 67.3%, 73.8%, and 75.2%, respectively.

Review study about Hierarchical Routing Protocol in wireless sensor networks

Wireless Sensor Networks (WSNs) are crucial in various applications, including smart homes, military surveillance, health monitoring, and environmental sensing. These networks consist of distributed sensor nodes that collect and transmit environmental data to a central location for processing. However, WSNs face challenges such as limited energy resources, scalability, complexity, security, fault tolerance, and quality of service. Researchers have proposed different routing protocols tailored to WSN characteristics to address these issues. This article comprehensively overviews WSN design issues, focusing on routing protocol classification and comparative analysis. Among the hierarchical protocols, LEACH (Low-Energy Adaptive Clustering Hierarchy) is highlighted as a prominent clustering-based protocol that reduces energy consumption by forming clusters and utilizing cluster heads for data aggregation. Each addresses specific challenges and enhances network performance. The comparative analysis evaluates the protocols based on energy efficiency, network lifetime, data delivery, scalability, and security. The findings help researchers, practitioners, and network designers select appropriate routing protocols for their specific WSN applications. This article offers valuable insights into WSN design issues and presents a comprehensive classification and comparison of routing protocols. By understanding the strengths and limitations of different protocols.

THSI-RP: A two-tier hybrid swarm intelligence based node clustering and multi-hop routing protocol optimization for wireless sensor networks

Wireless sensor networks exploit clustering and routing techniques to improve energy efficiency, but these methods are generally considered as a non-deterministic polynomial (NP-hard) problem. To tackle this problem, we propose a novel two-tier hybrid swarm intelligence-based hierarchical routing protocol (THSI-RP). In the first tier, THIS-RP incorporates a hybrid swarm intelligence algorithm that combines Grey Wolf Optimization (GWO) and Marine Predators Algorithm (MPA) for the clustering algorithm. By incorporating the wolf factors from GWO into MPA as elite predators, we enhance the network search efficiency. This algorithm achieves adaptive optimal clustering with a controllable scale, considering the residual energy of nodes, relative distance between nodes, and node centrality. In the second tier, the routing algorithm uses a hybrid SI algorithm based on GWO and the graph model. First, we integrate distance and energy factors to dynamically select forwarding nodes using GWO. Then, based on the distance and energy balance principle, a weight cost function is established and combined with the minimum spanning tree method to construct a communication routing tree between the forwarding node and the base station to achieve optimized inter-cluster multi-hop routing. Simulation results demonstrate that THSI-RP outperforms several typical routing protocols in various metrics over EEUC, LPSO, LGWO, and LACO. For instance, THSI-RP achieves percentage improvement total packets by 290%, 10.9%, 8.9%, 19.9%, respectively. It also performs better in FND by 88.7%, 10.9%, 8.6%, and 16.3%, in HDN by 86.6%, 8.1%, 6.3%, and 17.1%, and in ADN by 41.7%, 8.2%, 6.4%, 18.3%.

LEACH-based hierarchical energy efficient routing in wireless sensor networks

Wireless Sensor Networks (WSNs) not only have a constantly increasing range of applications but also stimulate the amazing growth of 5G mobile communications and the Internet of Things (IoT). Yet, the lifetime of WSNs is restricted due to the severe energy limitations of their components. For this reason, the achievement of energy sustainability in WSNs is extremely important. Given that the greatest part of energy consumption in a WSN takes place during data routing, numerous research works are carried out in order to develop protocols for energy efficient routing. This article aims to clarify the most popular subdivision of this category of protocols i.e. the so-called hierarchical energy efficient routing protocols. Specifically, LEACH, which is considered to be the pioneer protocol of this kind, is studied along with 18 of its descendant protocols. A theoretical comparison of these protocols in terms of various metrics is also performed. Additionally, the performance of LEACH is compared with that of 3 descendant protocols through simulation tests that are carried out. Finally, a discussion takes place and concluding remarks are drawn.

MMSCM: A multiple mobile sinks coverage maximization based hierarchical routing protocol for mobile wireless sensor networks

AbstractMobile wireless sensor network (MWSN) adapts to the requirements of mobility of civil and military network devices and has received a lot of attention. Designing an efficient, low‐energy, and fault‐tolerant routing protocol for the frequently changing topology of highly mobile MWSNs is challenging. Most routing protocols today only support the movement of sensor nodes or only sink. This paper proposes a Multiple Mobile Sinks Coverage Maximization based hierarchical routing protocol for mobile wireless sensor networks (MMSCM), which allows sensor nodes and sinks to move simultaneously. The MMSCM divides the monitoring area into virtual grids and deploys a movable sink in each grid cell. Sink selects the appropriate next hop for each cluster head in the area to build an optimal routing forest and collects data from all routing tree root nodes at a uniform speed along the specified path with maximum coverage. Simulation results show that, compared with current advanced routing algorithms, the MMSCM protocol can better solve the network delay problem and improve data throughput while extending the network life cycle, which is more suitable for time‐sensitive application scenarios.

CMSTR: A Constrained Minimum Spanning Tree Based Routing Protocol for Wireless Sensor Networks

How to extend the network lifetime with given limited energy budget is always one of the main concerns in Wireless Sensor Networks (WSNs). However, imbalanced energy consumption and overlong intra-cluster communication paths are prevalent in the hierarchical routing protocols, which shortens the network lifetime inevitably. To this end, an energy-efficient routing Protocol based on Constrained Minimum Spanning Tree (CMSTR) is proposed in this paper. To be specific, a new multichain routing scheme to balance the energy consumption for intra-cluster communications is presented. Based on the multichain routing scheme, the problem of establishing intra-cluster routing is transformed into a shortest Hamiltonian path problem on the basis of a graph-theoretic analysis model, which is solved through a Constrained Minimum Spanning Tree (CMST) algorithm proposed in this paper, with the aim to obtain the initial path for intra-cluster communications. In order to shorten the initial path length to obtain higher energy-efficient chain routes, a Neighbor Node Replacement (NNR) algorithm and a Link Intersection Detection and Elimination (LIDE) algorithm are proposed, in which the problem of potential long links and intersections is to be effectively alleviated. With shorter chain routes, unnecessary intra-cluster communication energy depletion can be reduced accordingly. In order to evaluate the performance of CMSTR, extensive simulation experiments are conducted. The results show that CMSTR can greatly prolong the network lifetime with regard to the metrics of FND and HND. To be specific, compared with LEACH, R-LEACH, and DCMSTR, the value of FND increased by 800%, 540% and 57%, that of HND increased by 322%, 286% and 22%, and overall network lifetime (AND) increased by 29%, 10% and 5%, respectively. Besides, CMSTR has a stable and lowest packet loss percentage (0.4%). In summary, CMSTR has excellent performance in terms of energy efficiency and network stability.

A Novel Spider Monkey Optimized Fuzzy C-Means Algorithm (SMOFCM) for Energy-Based Cluster-Head Selection in WSNs

AI is getting increasingly complex as a result of its widespread deployment, making energy efficiency in Wireless Sensor Network (WSN)-based Internet of Things (IoT) systems a highly difficult problem to solve. In energy-constrained networks, cluster-based hierarchical routing protocols are a very efficient technique for transferring data between nodes. In this paper, a novel Spider Monkey Optimized Fuzzy C-Means Algorithm (SMOFCM) is proposed to improve the lifetime of the network and less energy consumption. The proposed SMOFCM technique makes use of the Fuzzy C-means clustering framework to build up the cluster formation, and the Spider Monkey Optimization technique to select the Cluster Head (CH). MATLAB was used to model the suggested SMOFCM. The suggested framework's network lifetime, number of alive nodes (NAN), energy consumption, throughput, and residual energy are compared to those of more established frameworks like LEACH, K-MEANS, DRESEP, and SMOTECP. SMOFCM technique improves the network lifetime by 11.95%, 7.59%, 4.97% and 3.83% better than LEACH, K-MEANS, DRESEP, and SMOTECP. According to experimental findings, the proposed SMOFCM technique outperforms the existing model.

A Q-Learning-Based Hierarchical Routing Protocol With Unequal Clustering for Underwater Acoustic Sensor Networks

Underwater acoustic sensor networks (UASNs) have emerged as a viable networking approach due to their numerous aquatic applications in recent years. As a vital component of UASNs, routing protocols are essential for ensuring reliable data transmissions and extending the longevity of UASNs. Recently, several clustering-based routing protocols have been proposed to reduce energy consumption and overcome the resource constraints of deployed sensor nodes. However, they rarely consider the hot-spots’ problem and the sink node isolation problem in the multihop underwater sensor networks. In this article, we propose a Q-learning-based hierarchical routing protocol with unequal clustering (QHUC) for determining an effective data forwarding path to extend the lifespan of UASNs. First, a hierarchical network structure is constructed for initialization. Then, a combination of unequal clustering and the Q-learning algorithm is applied to the hierarchical structure to disperse the remaining energy more evenly throughout the network. With the use of the Q-learning algorithm, a global optimal CH and next-hop can be determined better than a greedy one. In addition, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula> value that guarantees the optimal routing decisions can be computed without incurring any additional costs by combining the Q-learning algorithm with clustering. The simulation results show that the QHUC can achieve efficient routing and prolong the network lifetime significantly.

WSN Network Node Malicious Intrusion Detection Method Based on Reputation Score

Wireless sensor network (WSN) is the Internet of Things by a large number of sensors in the external physical environment to obtain data information, and use wireless communication technology to provide users with information transmission services. At this stage, communication and security mechanisms are the main problems faced by WSN. This is because most of the existing sensors are powered by batteries with very limited energy, and most of them are deployed in an outdoor open environment, which is easy to be captured as a malicious node. Network attacks. However, the existing malicious node detection methods have shortcomings such as low efficiency, high energy consumption, and insufficient performance. Therefore, this paper proposes a WSN malicious node intrusion detection method based on genetic algorithm optimization of LEACH hierarchical routing protocol. Based on the optimization of the LEACH protocol by genetic algorithm, the method integrates the reputation evaluation mechanism, and screens and eliminates malicious nodes by calculating direct reputation, indirect reputation and comprehensive reputation, thereby ensuring the safe operation of WSN. The simulation results show that this method can effectively resist the attack of malicious nodes on WSN, and has obvious advantages over other methods.

Performance Enhancement of MANET based on Cross-layered Reconfigurable Hierarchical Routing Protocol

High speed data communication is the demanding factor in both commercial and defence applications. Several algorithms are proposed to support the high-speed data exchange while ensuring the quality, performance and reliability. However, there is still a gap, citing various compatibility issues with variety of transceiver technologies. This paper proposes a novel algorithm for enhancing the performance of mobile ad-hoc networks using Free-Space Optics (FSO). The FSO has the natural ability to the interference while capable of large bandwidth and excellent compatibility. Low power and adaptability are the features with which it has contributed to the latest technologies like storage area network, wireless area network etc. The proposed work uses optical spheres with a multi-transceiver system and a cross-layered reconfigurable routing mechanism. Parameters such as delay, residual energy, throughput, and drop are verified for the Crosslayered Reconfigurable Hierarchical Routing Optical Sphere (CRHROS) protocol for varying numbers of optical transceivers. The proposed work also compares the performance of two traffic sources, Constant Bit Rate (CBR) and Variable Bit Rate (VBR), for the proposed algorithm.

An Energy-Efficient Multi-swarm Optimization in Wireless Sensor Networks

Wireless Sensor Networks are a group of sensors with inadequate power sources that are installed in a particular region to gather information from the surroundings. Designing energy-efficient data gathering methods in large-scale Wireless Sensor Networks (WSN) is one of the most difficult areas of study. As every sensor node has a finite amount of energy. Battery power is the most significant source in the WSN. Clustering is a well-known technique for enhancing the power feature in WSN. In the proposed method multi-Swarm optimization based on a Genetic Algorithm and Adaptive Hierarchical clustering-based routing protocol are used for enhancing the network’s lifespan and routing optimization. By using distributed data transmission modification, an adaptive hierarchical clustering-based routing algorithm for power consumption is presented to ensure continuous coverage of the entire area. To begin, a hierarchical clustering-based routing protocol is presented in terms of balancing node energy consumption. The Multi-Swarm optimization (MSO) based Genetic Algorithms are proposed to select an efficient Cluster Head (CH). It also improves the network’s longevity and optimizes the routing. As a result of the study’s findings, the proposed MSO-Genetic Algorithm with Hill climbing (GAHC) is effective, as it increases the number of clusters created, average energy expended, lifespan computation reduces average packet loss, and end-to-end delay.

Minimizing Energy Hole Problem Comparisons in Some Hierarchical WSN Routing Protocols

This paper study the efficient use of energy as a challenging task of designing these protocols. The energy holes are created due to non-uniform node distribution in the network when quickly drain the energy in a few nodes. It is studies removing energy holes by using sleep and awake mechanism for sensor nodes to save energy. This approach finds the maximum distance nodes to calculate the maximum energy for data. It intends to enumerate the dead nodes transmission, alive nodes, throughput, overhead and packet delivery ratio consumed by the entire network and affected by the network area changes. lastly, a brief performance analysis of Low Energy Adaptive Clustering Hierarchy (LEACH), Distributed Energy-Efficient Clustering (DEEC), Threshold sensitive Energy Efficient sensor Network protocol (TEEN) and Stable Election Protocol (SEP) is carried out considering metrics of the previous characteristics of wireless sensor network.