Hierarchical Routing Protocol Research Articles

Notice of Removal: An Improved Equal Hierarchical Cluster-Based Routing Protocol for EH-WSNs to Enhance Balanced Utilization of Harvested Energy

Notice of Removal: An Improved Equal Hierarchical Cluster-Based Routing Protocol for EH-WSNs to Enhance Balanced Utilization of Harvested Energy

Incremental Linear Discriminant Analysis Dimensionality Reduction and 3D Dynamic Hierarchical Clustering WSNs

Optimizing the sensor energy is one of the most important concern in Three-Dimensional (3D) Wireless Sensor Networks (WSNs). An improved dynamic hierarchical clustering has been used in previous works that computes optimum clusters count and thus, the total consumption of energy is optimal. However, the computational complexity will be increased due to data dimension, and this leads to increase in delay in network data transmission and reception. For solving the above-mentioned issues, an efficient dimensionality reduction model based on Incremental Linear Discriminant Analysis (ILDA) is proposed for 3D hierarchical clustering WSNs. The major objective of the proposed work is to design an efficient dimensionality reduction and energy efficient clustering algorithm in 3D hierarchical clustering WSNs. This ILDA approach consists of four major steps such as data dimension reduction, distance similarity index introduction, double cluster head technique and node dormancy approach. This protocol differs from normal hierarchical routing protocols in formulating the Cluster Head (CH) selection technique. According to node’s position and residual energy, optimal cluster-head function is generated, and every CH is elected by this formulation. For a 3D spherical structure, under the same network condition, the performance of the proposed ILDA with Improved Dynamic Hierarchical Clustering (IDHC) is compared with Distributed Energy-Efficient Clustering (DEEC), Hybrid Energy Efficient Distributed (HEED) and Stable Election Protocol (SEP) techniques. It is observed that the proposed ILDA based IDHC approach provides better results with respect to Throughput, network residual energy, network lifetime and first node death round.

Hybrid energy efficient network using firefly algorithm, PR-PEGASIS and ADC-ANN in WSN

Every wireless sensor network is threatened mainly due to Lifespan, Energy, Distortion, Security etc. Life time and energy are two major concerns of Wireless Sensor Network. The way Energy is utilized in the network will define how much the lifespan of a WSN is. To improve the lifespan of sensor nodes, the researches focus on the reduction of energy consumption rate of the nodes during the process of transmission and reception of data. The foremost emphasis of this research work is to project a distortion free wireless network with the help of appropriate Cluster head selecting through firefly algorithm. A grid-based clustering approach is used to select an appropriate CH from clusters of networks. The aim of selecting an appropriate CH is to reduce the energy consumption rate followed by swarm inspired optimization algorithm such as Firefly algorithm. After the selection of the CH, the route is form by using Proficient Routing based Power-Efficient Gathering in Sensor Information (PR-PEGASIS) hierarchical routing protocol. To face the distortion in the network due to battery discharge problem or from various other issue, Active Distortion Control Artificial Neural Network (ADC-ANN) is used to classify the optimal nodes within the route. At last, the comparison between existing work and proposed work is performed to determine the accuracy of the proposed work. This research emphases the best possible utilization of existing techniques and framed new algorithm to reduce the energy consumption of the WSN. The energy consumption rate up to 17.6% is reduced as compared to the existing work.

Types Routing Protocols based one Energy Efficiency

Abstract: Wireless sensor networks (WSNs) consist of autonomous sensors distributed in space to monitor physical or environmental conditions such as temperature, sound, and pressure, and to coordinate communications. The information collected reaches its destination through the network infrastructure. Energy-efficient routing protocols are becoming more important because sensor nodes are power-limited devices. Several tiered routing protocols have recently been proposed to minimize power consumption. For example, LEACH is a basic hierarchical routing protocol that uses clustering to achieve energy efficiency. Much research has been done to eliminate the shortcomings and improve the performance of hierarchical routing protocols. WSN hierarchical routing protocols and analyzes the capabilities and performance of existing hierarchical routing protocols. It also compares existing routing protocols, highlights key technical differences, and provides a performance comparison of some LEACH-based routing protocols. Finally, this article highlights the issues and challenges of existing WSN routing protocols. It supports future research on the selection of appropriate research areas and provides guidance on the selection of energy saving methods in the energy efficient design of WSN routing protocols. Keywords: wireless sensor network, routing protocols, CSMA, CH, TDMA

Energy-Efficient Clustering Scheme for Flying Ad-Hoc Networks Using an Optimized LEACH Protocol

A Flying Ad-hoc network constitutes many sensor nodes with limited processing speed and storage capacity as they institute a minor battery-driven device with a limited quantity of energy. One of the primary roles of the sensor node is to store and transmit the collected information to the base station (BS). Thus, the life span of the network is the main criterion for the efficient design of the FANETS Network, as sensor nodes always have limited resources. In this paper, we present a methodology of an energy-efficient clustering algorithm for collecting and transmitting data based on the Optimized Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. The selection of CH is grounded on the new optimized threshold function. In contrast, LEACH is a hierarchical routing protocol that randomly selects cluster head nodes in a loop and results in an increased cluster headcount, but also causes more rapid power consumption. Thus, we have to circumvent these limitations by improving the LEACH Protocol. Our proposed algorithm diminishes the energy usage for data transmission in the routing protocol, and the network’s lifetime is enhanced as it also maximizes the residual energy of nodes. The experimental results performed on MATLAB yield better performance than the existing LEACH and Centralized Low-Energy Adaptive Clustering Hierarchy Protocol in terms of energy efficiency per unit node and the packet delivery ratio with less energy utilization. In addition, the First Node Death (FND) is also meliorated when compared to the LEACH and LEACH-C protocols.

Cluster Based Communication In Wsn: A Survey

WSN establishes an essential role in industrial applications. WSN consists of multiple tiny sensor nodes (SNs), which are organized in an outlying area.These sensor nodes consist of battery and thus it’s very challenging to interchange these SNs in a brassy environment once deployed.Therefore, in order to increase the network life, the sensor node energy needs to be preserved. Thus, in some protocols these wsn’s nodes grouped to form a cluster for efficient communication. In hierarchical approach,there aretwo concepts- one based on cluster and other one based on grid concepts. In cluster-based concepts, SN’s assembled to form clusters, where nodes having more residual energy become a leader of the cluster and thus known as Cluster Head. Thus, the network is separatedinto virtual grids in case of a grid based concept. This paper discusses the hierarchical routing protocol, its design challenge andan advantages and disadvantages of protocols.

Research perspective on energy-efficient protocols in IoT: emerging development of green IoT

PurposeInternet of Things (IoT) is an up-and-coming conception that intends to link multiple devices with each other. The aim of this study is to provide a significant analysis of Green IoT. The IoT devices sense, gather and send out significant data from their ambiance. This exchange of huge data among billions of devices demands enormous energy. Green IoT visualizes the concept of minimizing the energy consumption of IoT devices and keeping the environment safe.Design/methodology/approachThis paper attempts to analyze diverse techniques associated with energy-efficient protocols in green IoT pertaining to machine-to-machine (M2M) communication. Here, it reviews 73 research papers and states a significant analysis. Initially, the analysis focuses on different contributions related to green energy constraints, especially energy efficiency, and different hierarchical routing protocols. Moreover, the contributions of different optimization algorithms in different state-of-the-art works are also observed and reviewed. Later the performance measures computed in entire contributions along with the energy constraints are also checked to validate the effectiveness of entire contributions. As the number of contributions to energy-efficient protocols in IoT is low, the research gap will focus on the development of intelligent energy-efficient protocols to build up green IoT.FindingsThe analysis was mainly focused on the green energy constraints and the different robust protocols and also gives information on a few powerful optimization algorithms. The parameters considered by the previous research works for improving the performance were also analyzed in this paper to get an idea for future works. Finally, the paper gives some brief description of the research gaps and challenges for future consideration that helps during the development of an energy-efficient green IoT pertaining to M2M communication.Originality/valueTo the best of the authors’ knowledge, this is the first work that reviews 65 research papers and states the significant analysis of green IoT.

ZHLS Security Enhancement by integrating SHA256, AES, DH in MANETS

In this century fast growing and progressive change of technology, Mobile Ad hoc Network (MANET) which is a no centralized structure plays great role. The routing protocol in this network is objective to deliver efficient route since sender to receiver. One of the hybrid routing protocols example is Zone Based Hierarchical Link State Routing Protocol (ZHLS) that is can’t allowable huge amount of inside attacks which arise from malevolent nodes. The third party in the routing system may drop the data, as well as disturbs the progression of the routing. To resolve this difficult, ZHLS Security is enhanced by integrating SHA256, AES, DH in MANETS. Security to routing protocols in MANETS is incorporated with different traditional Security mechanisms. My idea behind this thesis is to use integrated security ZHLS protocol by integrating Advanced Encryption Standard (AES) as well as secure hash algorithms to provide the data security. Also, it is, Deffi-Hellman to preserve privacy among the data transmission nodes. In the proposed method, AES is applied to symbol, also authentication to provide the confidentiality of the message in the routing system. This work will be simulated on NS2 environment and it may highly improve the security of data transmission among wireless mobile nodes.

Energy conserving ring cluster‐based routing protocol for wireless sensor network: A hybrid based model

AbstractThe recent advancement in WSNs has drawn its attentive toward number of researchers as it is supportive to the wide range of applications. During the routing mechanism in WSN, the tiny sensors powered with batteries can be expired soon. Number of solutions have been proceeded so far to resolve this issue, and the ring routing protocol is one among them. The ring routing protocol is an energy‐proficient mobile sink routing protocol that can be easily accessible and configures based on the virtual ring composition. Moreover, ring routing is a hierarchical routing protocol with a mobile sink in WSN that uses greedy geographic routing. In this research work, an energy‐aware ring routing protocol is developed based on the defined multi‐objective. Initially, the ring is constructed with a pre‐defined radius and the normal nodes now send data to the sink node via the constructed ring structure. More particularly, the nodes near the sink deplete faster than the other nodes and introduce overhead in terms of “energy consumption and packet delays.” When a ring node tends to exhaust, then its neighbor switches its role automatically, and this selection of the normal node as the ring node is accomplished optimally on the basis of the defined multi‐objectives like energy , distance between the ring node and the regular node and distance between network centers to regular node . As optimization has a key role in selecting the neighbors as the ring nodes, a new optimization model referred to as Moth Integrated Firefly Algorithm (MIFA) is introduced in this research work. The performance of the proposed model is compared over other conventional models with respect to throughput, energy dissipation, and transmission delay as well.

Load‐based node ranked low‐energy adaptive clustering hierarchy: An enhanced energy‐efficient algorithm for cluster head selection in wireless sensor networks

AbstractA Wireless Sensor Network typically uses a large number of power‐constrained sensor nodes for sensing phenomenal data and for its processing. The lifetime of a sensor node is limited and this is a great challenge for researchers to sustain the network for a long time. Since, the data transmission from a sensor node to the base station is more power consuming, the hierarchical routing protocols play a major role in multihop communication and to prolong the network life time. It uses a clustering approach with an overhead of cluster head (CH) selection to attain this. This overhead needs proper addressing and to be reduced by some means. The work in this paper employs a new approach based on low‐energy adaptive clustering hierarchy (LEACH) and considers network load for electing CH in addition to number of links, residual sensor energy and distance. Here, energy and time are used for calculating load on a CH. The simulation results show that the proposed protocol performs better than LEACH, LEACH‐I, and NR‐LEACH algorithms on the parameters of average energy ratio throughput, end‐to‐end delay, packet delivery ratio, and a number of alive nodes.

Overlapped hierarchical clusters routing protocol for improving quality of service

The rapid development in communications and sensors technologies make wireless sensor networks (WSNs) as essential key in several advanced applications such as internet of things (IoT). The increasing demands on using WSNs required high quality of services (QoS) because most WSNs applications have critical requirements. This work aims to offer a routing protocol to improve the QoS in WSNs, taking in consideration its ability to prolong the lifetime of the network, optimize the utilization of the limited bandwidth available, and decrease the latency that accompanies the packets transmitted to the gateway. The proposed protocol is called overlapped hierarchical cluster routing protocol (OHCRP). OHCRP is compared with the traditional routing protocols such as SPEED, and THVR. The results show that OHCRP reduces latency effectively and achieve high energy conservation, which lead to increase the network lifetime and insure network availability.

Optimized Network lifetime and path loss of Underwater Wireless Sensor Network (UWSN) Using Multi-objective multi-verse optimization algorithm

In ocean scanning applications, such as ocean tracking, pollution sensor, ocean resource control, underwater system maintenance, etc, the underground wireless sensor networks (UWSNs) are commonly used. Due to the problems of underwater communication, underwater Wireless Sensor Networks (UWSN) have become a common research subject. One of the key purposes of an underwater network is to evaluate the improved path through the sensor nodes to the onshore station for the assignment of monitoring data. The transmission cycle requires energy from every node and energy is limited in UWSNs. The most demanding task in the underwater wireless sensor network, therefore, is energy efficiency. This paper focuses primarily on coping with the energy usage and network life.This paper proposes a Multi-Objective Multi-verse Optimization Algorithm (MOMVO) to optimize network life, path loss and minimize power consumption in UWNNs. In this paper, a comparative analysis of hierarchical routing protocols such as the stable election protocol (SEP), the Zonal-Stable Election Protocol (Z-SEP) and the LEACH-based Multi-Objective Multi-verse Optimization (MOMVO) is presented in a variety of performance metrics such as live nodes per round, base station packets (BS) per round, and dead nodes per round.

Design and Implementation of EOICHD Based Clustered Routing Protocol Variants for Wireless Sensor Networks

Efficient energy utilization and network life prolongation are primary objectives to be considered when designing a Wireless Sensor Network. Cluster-based routing protocols are most suitable for achieving such goals. Energy and Optimal Inter Cluster Head Distance (EOICHD) is a cluster-based hierarchical routing protocol inspired by the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. EOICHD resolves the problems associated with LEACH protocol, such as selecting cluster head nodes in close proximity. By carefully selecting the cluster head nodes based on residual energy and optimal inter-cluster head distance, EOICHD ensures that selected cluster head nodes are separated by a certain optimal distance. This approach ensures uniform distribution of cluster head nodes across the entire network. The study of the EOICHD protocol presented so far is not sufficient. Hence, in this paper, we propose three variants of EOICHD protocol to understand its behavior in a better manner. A comparative analysis of all three EOICHD variants, LEACH and LEACH-central constrained (LEACH-C) protocol, is performed by considering comparative parameters such as alive nodes, cumulative network energy, data packets arrived at the base station, and stability of the network.

Trust management-based and energy efficient hierarchical routing protocol in wireless sensor networks

The single planar routing protocol has a slow convergence rate in the large-scale Wireless Sensor Network (WSN). Although the hierarchical routing protocol can effectively cope with large-scale application scenarios, how to elect a secure cluster head and balance the network load becomes an enormous challenge. In this paper, a Trust Management-based and ​Low Energy Adaptive Clustering Hierarchy protocol (LEACH-TM) is proposed. In LEACH-TM, by using the number of dynamic decision cluster head nodes, residual energy and density of neighbor nodes, the size of the cluster can be better constrained to improve energy efficiency, and avoid excessive energy consumption of a node. Simultaneously, the trust management scheme is introduced into LEACH-TM to defend against internal attacks. The simulation results show that, compared with LEACH-SWDN protocol and LEACH protocol, LEACH-TM outperforms in prolonging the network lifetime and balancing the energy consumption, and can effectively mitigate the influence of malicious nodes on cluster head selection, which can greatly guarantee the security of the overall network.

Machine Learning-Based Optimized Hierarchical Routing Protocols for WSN Lifetime: A Review

In Wireless Sensor Networks, network lifetime optimization has challenging and significant issue. Subsequently, most of the existing works delineate several factors to improve the network lifetime: by decreasing the amount of the consumption of energy, reducing latency, load balancing, clustering, efficient data aggregating and by minimizing the data transmission delays. This paper provides a review of recent techniques and presents a Machine Learning-based Optimized Hierarchical Routing Protocols for WSN Lifetime. Research has been done, and reviews have been studied to explore the energy management schemes using optimized routing approach and Machine Learning Adaptability for WSN’s. Further, recommend future directions related to the Optimized Clustering Approaches to enhance wsn lifetime.

Hierarchical clustering and routing protocol to ensure scalability and reliability in large-scale wireless sensor networks

Cluster-based routing protocols have been proven efficient in prolonging the life cycle of wireless sensor networks (WSNs). Periodic and multi-hop clustering are the most popular techniques which provide the required energy-efficient communication and scalability in large-scale WSNs. In clustering, WSN is divided into number of clusters, and cluster head is selected in each cluster. However, in the existing clustering protocols, CH’s near base station undergoes large number of receiving, aggregating and transmitting operations in comparison with far away CHs. This imbalance of load on CHs and lack of structured multi-level clustering framework leads to early death of WSNs. Moreover, resolving the issues of scalability and data reliability along with load balancing is a very tedious task. In this paper, a hierarchical clustering and routing (HCR) protocol is proposed to formulate a load-balanced approach for clustering while taking care of energy efficiency, reliability and scalability. Firstly, a hierarchical layered framework is created to split the WSN into virtual circular layers for efficient transmission of data in hierarchical fashion. Subsequently, an ant lion optimizer is employed for the selection of CHs to ensure reliable, energy balanced and scalable cluster formation. Simulation results demonstrate that HCR protocol outperforms existing state-of-the-art clustering protocols in terms of network lifetime, balanced clustering, throughput and energy efficiency.

ZHRP-DCSEI, a Novel Hybrid Routing Protocol for Mobile Ad-hoc Networks to Optimize Energy Using Dynamic Cuckoo Search Algorithm

In the wireless network advancement, Mobile Ad-hoc Networks (MANET) has been one of the developing areas of research. MANET is a group of wireless mobile nodes, which dynamically interchange information by modeling a short-term network without any framework. In MANET, routing is a highly challenging problem. Routing refers to discovering a path between the source (transmitter) and the destination (recipient) to forward the data packets. In a dynamic environment like MANET, another challenging issue is to prolong the network lifetime by optimizing the energy to avoid broken links. An improved version of hybrid Zone based Hierarchical Routing Protocol (ZHRP) based on Dynamic Cuckoo Search (DCS) algorithm has been proposed to optimize the path selection process and energy utilization. Initially, the DCS algorithm has been applied to zone based hierarchical routing protocol to discover and sustain the best routes for each node. Then, the stability of the wireless link is evaluated using this meta-heuristic technique. In the DCS algorithm, to maintain the balance between the global and the local random walks, a dynamic switching parameter has been applied. Different versions of dynamic switching parameters in the cuckoo search algorithm such as linear decreasing, linear increasing, exponential increasing, and power increasing are implemented to enhance the performance of the routing process in MANETs. The simulation results show that the proposed dynamic cuckoo search based hybrid routing technique has comparatively improved the performance of zone based hierarchical routing in terms of energy consumption, average delay, packet delivery rate, and throughput. Finally, the simulation results indicate that the DCS algorithm with a switching parameter, which increases exponentially, outperforms the variants of the DCS algorithm.

Intersection-Based V2X Routing via Reinforcement Learning in Vehicular Ad Hoc Networks

With the rapid development of the Internet of vehicles (IoV), routing in vehicular ad hoc networks (VANETs) has become a popular research topic. Due to the features of the dynamic network structure, constraints of road topology and variable states of vehicle nodes, VANET routing protocols face many challenges, including intermittent connectivity, large delay and high communication overhead. Location-based geographic routing is the most suitable method for VANETs, and such routing performs well on paths with an appropriate vehicle density and network load. We propose an intersection-based V2X routing protocol that includes a learning routing strategy based on historical traffic flows via Q-learning and monitoring real-time network status. The hierarchical routing protocol consists of two parts: a multidimensional Q-table, which is established to select the optimal road segments for packet forwarding at intersections; and an improved greedy strategy, which is implemented to select the optimal relays on paths. The monitoring models can detect network load and adjust routing decisions in a timely manner to prevent network congestion. This method minimizes the communication overhead and latency and ensures reliable transmission of packets. We compare our algorithm with three benchmark algorithms in an extensive simulation. The results show that our algorithm outperforms the existing methods in terms of network performance, including packet delivery ratio, end-to-end delay, and communication overhead.

WITHDRAWN: Comparison of hybrid GACS – TEEN with fuzzy – TEEN and GA – TEEN in hierarchical routing protocol for WSN

Abstract Wireless Sensor Network Nodes (WSNs) are power-limited devices, and the rational use of Sensor’s node energy and extending network life are key objectives of the WSN routing protocol. However, unsubstantiated considerations of node energy diversity can tents to an energy inequity among the cluster’s nodes in a heterogeneous WSN (HWSN).WSN using a Clusteing type routing protocol, which one is the best routing method for conservation of sensor’s energy. Evenlthough, in cluster-based routing a fault-aware routing is not full-fill in research issue. In this study, a novel based routing protocol for WSN by hybrid cuckoo search algorithm combined with genetic algorithm. This make to attain the better performance in WSN such as energy consumption, lifetime, and throughput. In this paper an energy based clustering routing protocol called TEEN (Threshold based Sensitive Energy-Efficient Network Sensor) for reactivated networks. Also these parameters our model is compared with the fuzzy-TEEN and GA-TEEN. After that comparison analysis our cuckoo search optimization protocol method is much better than other two protocol model. The approach can be expanded for various scenarios by increasing the size of nodes, receivers and networks.

Energy-efficient hierarchical routing in wireless sensor networks based on fog computing

Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the twenty-first century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize the energy consumption of sensor nodes to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called energy-efficient hierarchical routing protocol for wireless sensor networks based on fog computing. Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of things applications. In addition, we propose an improved ant colony optimization algorithm that can be used to construct an optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses, and extends the network lifetime. We are aware that in WSNs, the certainty of the sensed data collected by a sensor node can vary due to many reasons such as environmental factors, drained energy, and hardware failures.