Routing Protocol For Wireless Networks Research Articles

Performance evaluation of low energy adaptive clustering hierarchy-based cluster routing protocols in wireless sensor networks using a new graphical user interface

Wireless sensor network (WSN) is widely used for field data acquisition and monitoring in different domains. To make this type of network functional, efficient routing protocols must be implemented. Nevertheless, WSNs have an energy constraint due to limited batteries. Many clustered protocols are proposed to overcome it. However, the implementation of these protocols would be difficult to understand without a simulation tool, as some problems may arise during their development. Testing real-world applications requires a lot of effort and cost because they often use many nodes in large networks. Therefore, the simulation tool is the most relative way to evaluate these protocols. This paper presents graphical-based cluster protocols simulation interface for WSN(GCPS-WSN), a new interface to simulate some clustered protocols in WSNs. GCPS-WSN allows the user to evaluate the performance of certain low energy adaptive clustering hierarchy (LEACH) enhanced protocols to choose the most appropriate one for his system. The user can simulate protocols without any knowledge of software programming.

A Review on Energy and Latency Efficient Routing Protocol Design for Wireless Sensor Networks

Wireless sensor networks (WSNs) have been utilized by various industries, such as disaster management, the chemical and heavy industries, marine research, and space exploration. One of the primary challenges faced by wireless sensor networks is their limited network lifetime. Several techniques have been devised to extend the duration of network operation. This proposed method introduces a threshold-based algorithm to minimize the amount of data that needs to be transferred. In this approach, the selection of cluster heads and their sizes is not fixed. Instead, they are dynamically determined at the beginning of each iteration. The design of routing algorithms for wireless sensor networks faces three main challenges: lowering the rate at which the average node energy declines, minimizing the number of dead nodes, and eventually prolonging the network's lifetime. This paper provides a thorough examination of efficient routing protocols for wireless sensor networks with the goal of improving network longevity. Keywords: Efficient Routing, WSN Clustering, Network Latency, Network Lifetime.

Elliptic curve encryption-based energy-efficient secured ACO routing protocol for wireless sensor networks

Elliptic curve encryption-based energy-efficient secured ACO routing protocol for wireless sensor networks

Design and Development of a Hybrid Cooperative- Based Routing Protocol avoiding the void nodes in WSNs using the Concepts of Minimum Energy Consumption with good Data Security features

This paper presents a novel cooperative-based routing protocol designed for underwater Wireless Sensor Network Cloud Applications (uWSNCA). The protocol aims to minimize energy consumption by avoiding void nodes, which are areas without sensor coverage. The proposed approach consists of two main steps: first, avoiding void nodes using an adaptive hop-by-hop vector method, and second, applying a cooperative rule-based adaptive hop-by-hop vector method to create a hybrid algorithm that is more efficient than existing approaches, such as the watch-dog protocol. The research focuses on developing an energy-efficient distributed cooperative routing protocol for wireless sensor networks, specifically tailored for cooperation-based uWSNCA. This is achieved by preventing data packets from being forwarded through void nodes. The proposed routing protocol utilizes cooperation-based adaptive hop-by-hop vector-based forwarding concepts, where sensor nodes forward data packets in a multi-hop fashion within a virtual pipeline. In the developed algorithm for the underwater WSN cloud application, data packets are forwarded in a multi-hop manner using a virtual pipelining mechanism.Nodes outside the virtual pipeline do not forward data packets, thereby reducing flooding in the cooperative WSN. To prevent data packets from being forwarded towards void areas in the WSN, 2-hop information is used at each hop. This approach improves the performance of the wireless sensor network in terms of various performance criteria compared to existing routing protocols. The simulation tool NS2 is used to observe the simulation results of the energy packets being transferred from the source to the sink. The simulation results demonstrate the effectiveness of the proposed methodology. Overall, this paper contributes to the field of underwater WSNs by introducing a novel routing protocol that improves energy efficiency and performance for cloud applications.

Fuzzy logic with honey badger algorithm for cluster‐based multi‐hop routing protocol for wireless sensor networks

SummaryIn the last decades, wireless sensor networks (WSNs) have appeared as an active research area owing to their high applicability in different application areas like healthcare, automation, and the military. Several issues have been encountered in the WSNs, including energy consumption, deployment of sensor nodes, routing algorithms, energy efficiency, cluster head (CH) selection, and robustness. Cluster‐based routing is one of the energy‐efficient solutions in the WSN. At the same time, the hot spot problem remains a challenging problem, which needs to be addressed in the design of energy‐efficient solutions for WSNs. Motivated by the abovementioned discussion, c The comprehensive comparison study pointed out the betterment of the FLHBA‐CMHR technique in terms of different measures. The FLHBA‐CMHR technique obtains a maximum half‐node die (HND) of 1629 nodes, while the LEACH, FUCA, URBD, DEFL, and E‐FUCA techniques attain decreased HND of 793, 1085, 1092, 1139, and 1344 nodes correspondingly.

Enhanced reliability in hazardous event detection: A resilient multipath routing protocol for wireless sensor networks

AbstractWith the advance of climate change and the local effects of human activity, it has become of utmost importance to sense spatially extended natural and artificial physical phenomena to predict, monitor, and mitigate hazardous events. Wireless sensor networks are suitable for observing such phenomena, for example, wildfires, floods or landslides, without human supervision. This is due to affordable devices, independent power sources, wireless communication, and a broad range of sensors. During normal operation a few, while during the occurrence of an event a multitude of devices can fail. This leads to further disconnected devices, degrading the network's sensing capabilities. The communication requirements of such applications are difficult to fulfil with general routing protocols. The monitored event is rare compared to the network's lifetime, while its occurrence results in multiple, gradual node failures, still demanding the network to perform reliably. Available routing protocols fail to address every aspect of such application, thus the authors propose the Reliable Resilient Multipath Routing Protocol, designed to construct multiple disjoint paths from each device to a distinguished one, called the sink. The protocol employs proactive and reactive network management techniques to increase connection redundancy and maintain connectivity during failures. To verify the proposed protocol end‐to‐end, we evaluated the supported parameters, performed comparative simulations with routing algorithms known from the literature, and provided estimates of a realistic deployment.

A Taxonomy and Survey on Grid-Based Routing Protocols Designed for Wireless Sensor Networks

Minimization of energy consumption is the main attention of researchers while developing a routing protocol for wireless sensor networks, as sensor nodes are equipped with limited power supply. Virtual topology is an integral part of routing, and grid-based routing protocols are quite popular due to their simplified and efficient virtual grid topology construction. Although a list of surveys exists that either focus on routing protocols in a broader way or on other virtual topologies, none of these surveys are concerned about grid topology and grid-based routing protocols. Having this motivation in mind and considering the impact of these routing protocols on controlling and managing the energy consumption of wireless sensor networks, this article provides an expansive assessment of grid-based routing protocols based on their methodology. In this survey, the existing grid-based routing protocols are classified into two categories from the perspective of sink mobility: static sink and mobile sink. A phase-wise comprehensive overview of these routing protocols is provided in chronological order, along with their comparative analysis. Furthermore, the characteristics, design issues, and challenges of grid-based routing protocols are also provided.

EVRP: A novel geometrical based energy efficient eye vision routing protocol for wireless sensor networks based on the k-means algorithm

The limited energy source used in wireless sensor networks (WSNs) is a crucial aspect when designing a routing protocol. Developing a routing protocol that tries to maximize energy utilization can significantly improve the system's lifetime and balance energy consumption. A novel geometrical-based energy-efficient routing protocol called "EVRP" is presented in this paper. The Cluster generation process is based on the k-means algorithm for nodes grouping. To choose a cluster head (CH) for each cluster, a cost function is calculated for each node considering factors such as remaining energy level for the node, and the mean distance between the node and its neighbors. In the inter-cluster routing phase, a novel geometrical-based routing protocol is introduced considering factors such as the distance to a base station (BS), remaining energy level, and distance between CHs to find the optimal path between BS and CH. The cluster structure is integrated with direct communication in addition to a dynamic clustering mechanism based on the optimum number of CHs and a load balancing mechanism to reduce the load on CHs near BS. The simulation results demonstrate that in different scenarios, the proposed protocol can significantly increase the network lifetime, network throughput, and network stability by 52 %, 45 %, and 30 % respectively compared with the EECRAIFA protocol and by 100 %, 97.6 %, 64.3 % respectively compared with D2CRP protocol.

A novel energy-efficient dynamic programming routing protocol in wireless multimedia sensor networks

Wireless multimedia sensor networks (WMSNs) have characteristics that may influence the routing decisions, such as limited energy resources, storage and computing capacity. Therefore, a routing optimization needs to be done to match the characteristics of the WMSNs. Existing routing protocols only consider energy efficiency regardless of energy threshold, maximum energy, and link cost collectively as the primary basis of routing. In this work, the energy-efficient dynamic programming (EEDP) protocol is proposed to optimize routing decisions that take into account the energy threshold, the maximum energy, and the link cost. Then, the protocol is compared with the dynamic programming (DP), and the ant colony optimization (ACO) protocol. The simulation results show that the EEDP protocol can improve energy efficiency of nodes and network lifetime of the WMSNs. Then, the EEDP protocol is also implemented into a network topology of 10 NodeMCU ESP32 devices. As a result, the EEDP protocol can work very well by selecting routes based on nodes that have the remaining energy above 50 and has the shortest distance. The average delay in sending data for the entire route for the 10 iterations of sending data is 3.99 seconds.

Energy efficient cluster routing protocol for wireless sensor networks using hybrid metaheuristic approache’s

The development of wireless sensor networks (WSNs) has been particularly notable in the context of smart computing, where various application areas have been identified. These networks consist of self-configured, small sensor nodes with battery power. However, sensors have limited energy and resources at their disposal. When unbalanced nodes exist within the network, it adversely affects the network’s lifetime due to increased power consumption. Designing efficient routing for wireless sensor networks remains a challenging task, particularly in terms of energy efficiency. Optimal solutions to address these challenges involve reducing node energy consumption through the implementation of clustering techniques. The current clustering schemes do not take into account node energy balancing, node density, and scalability when selecting low-energy nodes as cluster heads. The existing system is limited to exploring global opportunities within specified search zones. To enhance the performance of WSNs, a hybrid approach combining artificial bee colony (ABC) and ant colony optimization (ACO) has been developed. This approach helps in selecting an ideal cluster head from a group of terminals. Several factors are considered in the cluster head election, including residual energy at the nodes, distance to neighbors, distance to the base station, node degree, and node centrality. ACO determines the path between the cluster leader and the base station (BS) by selecting the most efficient route in terms of distance, remaining power, and node degrees. The performance of this proposed methodology has been analyzed in terms of energy consumption, network lifetime, and data packets at the base station. A comparison has been made between the outputs of the proposed methods and traditional benchmarking methods. The results reveal a substantial improvement in the average network lifetime, showcasing an increase of 40.50%, 33.17%, 25.00%, and 15.49% when compared to LEACH, Beecluster, iABC, and BeeSensor, respectively. In terms of alive nodes, our solution surpasses LEACH, Beecluster, iABC, and BeeSensor by 28.7%, 22.51%, 20.95%, and 12.47%, respectively. Additionally, the energy consumption of our approach proves to be significantly lower than LEACH, Beecluster, iABC, and BeeSensor, recording reductions of 47.25%, 32.40%, 27.38%, and 22.20%, respectively.

Advancing Wireless Sensor Networks through Performance Evaluation of M-PDCH Routing Protocol for Enhanced Quality of Service

Objective: The decisive aim of this investigation is to improve the capabilities and limitations of PEGASIS with Double Cluster Head (PDCH), for enhancing the overall Quality of Service (QoS) in Wireless Sensor Networks (WSNs). Methods: This research is intended at the application of efficient routing protocol for wireless sensor networks. It works on the principle of the formation of cluster head and clustering. This is accomplished to achieve high QoS for WSN. Improving the efficacy of a WSN protocol is decisive for optimizing communication, resource utilization, and overall effectiveness. An innovative and novel protocol named Mobile-PDCH (M-PDCH) has been devised, developed, and tested. Here several parameters have been carefully investigated for enhancing the performance of a WSN protocol such as energy consumption, delay, and packet loss. A simulation environment has been created to evaluate, compare, and validate the performance and to suggest the desired applications of the proposed protocol. Findings: In the hierarchical category, PDCH performs better compared to all the other protocols. But it suffers from high packet drop, which decrease the performance of the protocol. To improve the performance of sensor networks, there is a need for adaptive routing protocol. The examination of simulation outcomes for the recommended protocol, M-PDCH, has been conducted in comparison with PDCH. The findings indicate that the protocol exhibits superior performance. The proposed algorithm improves the packet drop by 29.75%, reduces delay by 23.28%, and lowers energy consumption by 19.18% when compared to PDCH. Novelty: A novel adaptive routing protocol termed M-PDCH has been proposed for the enhancement of the WSN life span and durability of the sensor nodes. The simulation results show that the proposed algorithm produces better results compared to PDCH protocol. The various QoS parameter results are compared, verified, and validated with existing protocol PDCH. Keywords: WSN, PDCH, Design issues, Metrics, QoS, HRP

Performance enhancement of efficient clustering and routing protocol for wireless sensor networks using improved elephant herd optimization algorithm

Performance enhancement of efficient clustering and routing protocol for wireless sensor networks using improved elephant herd optimization algorithm

WOAD3QN-RP: An intelligent routing protocol in wireless sensor networks — A swarm intelligence and deep reinforcement learning based approach

Wireless Sensor Networks (WSN) are a crucial part of the Internet of Things (IoT), and research on WSN routing protocols has always been a hot topic in academia. However, traditional WSN routing protocols have limited utilization of available information during the routing decision process, leading to challenges such as insufficient adaptability to network topology changes, high communication delays, and short network lifetimes. To address these issues, this paper proposes an innovative intelligent routing algorithm WOAD3QN-RP, which cleverly integrates swarm intelligence algorithms and deep reinforcement learning. The WOAD3QN-RP not only effectively reduces delay but also balances energy consumption and flexibly adapts to changes in network topology, while simultaneously determining the optimal multi-hop path, effectively extending the lifetime of the network. Firstly, the WOAD3QN-RP algorithm employs the Whale Optimization Algorithm (WOA) to determine the optimal cluster heads (CHs). In the process of selecting CHs, the algorithm comprehensively considers key factors such as the residual energy of nodes, node distance, and communication delay, thereby significantly improving the accuracy and efficiency of CH selection, which contributes to better energy distribution and performance of the network. Secondly, in terms of multi-hop path selection, WOAD3QN-RP uses a dueling double deep Q-network (D3QN) to determine the optimal multi-hop path. Through utilizing neural networks to interact with the environment, intelligent agents are trained to learn routing policies to adapt to dynamic changes in the network topology and ensure the balance between energy consumption and multi-hop routing performance. Experimental results show that WOAD3QN-RP exhibits significant advantages over existing routing protocols in terms of network lifetime, energy efficiency, and communication delay.

Routing Methods For Data Transmission In Large Networks: A Review

A wireless sensor network (WSN) is a network consisting of miniaturized smart sensors communicating the information gathered or collected from a monitored environment via a wireless link. The sensors are capable of sensing the events within their environment, process the data, and transmit the data to the base station (BS). The entire processing of data and subsequent transmission to BS requires high energy consumption. The operation of WSN is limited by repeated dead nodes, which results in energy depletion. Hence, to prolong the life-span of the network, several routing protocols have been developed. However, the effectiveness of these protocols has not been well examined in terms of increasing node population for a given WSN field or area. Therefore, in this work the effect of increasing node density on cluster based energy-efficient routing protocols in wireless sensor network was analysed. The implemented routing protocols were Low Energy Adaptive Clustering Hierarchy LEACH, stable election protocol (SEP), and zone-SEP (Z-SEP). The dimension of the WSN was 100 × 100 square metre area with varying number of sensor nodes: 50, 60, 70, 80, 90, and 100. The results of the simulation conducted in MATLAB revealed that increasing node density resulted in increased alive node and throughput (measures in terms of transmitted number of packets). On the contrary, the protocol with the best performance was ZSEP.

Advanced Recursive Best-First Search (RBFS) based Routing Protocol for Multi-hop and Multi-Channel Cognitive Wireless Mesh Networks

Cognitive Wireless Mesh Network (CWMN) is an opportunistic network in which radio channels can be assigned according to their availability to establish connections among nodes. After establishing a radio connection among nodes, it is necessary to find an optimal route from the source node to the destination node in the network. If there remain more channels among nodes, the minimum weighted channel should be taken into account to establish expected routes. The graph theoretic approach fails to model the multi-channel cognitive radio networks due to abrupt failure in finding new successful routes as it can’t figure multi-channel networks. In this paper, a multi-edged graph model is being proposed to overcome the problems of cognitive radio networks, such as flooding problems, channel accessing problems etc. A new channel accessing algorithm has been introduced, and optimal routes have been selected using a heuristic algorithm named RBFS. Simulation results are compared with DJKSTRA based routing protocols.

Priority RPL for IOT Based Smart Manufacturing Industries

A routing protocol used in heterogeneous transport networks for low-power, lossy networks. This is a routing protocol for wireless networks. This protocol follows the same specifications as Zigbee, 6 lopan is IEEE 802.15. 4 Enables both many-to-one and one-to-one communication. To address the need for enhancing in this study proposes a novel methodology called RPL-PG (Routing Protocol for Low-Power and Lossy Networks Priority Generation). Initially sensors like Temperature, Humidity, Vibration, Proximity, Gas and Current Monitoring Sensors are used for smart manufacturing. Consequently, Destination Oriented Directed Acyclic Graph (DODAG) is used for RPL configuration. Based on selected RPL configuration the priority is generated using assign priority count and priority-based queuing. Finally, Fuzzy rules are used to select the RPL path and then update the DODAG finally reached the destination. The study involves setting up a simulated environment using appropriate tools, such as MATLAB. Experimental findings evaluate and compares performance measures, such as Energy Consumption, Network Life Time, Packet Loss Ratio, Packet Delivery Ratio (PDR), E2E Delay, and Network Throughput. The Energy Consumption of the proposed RPL-PG method achieves 43.6 % lower than 38 % and 35.8 % in terms of OMC-RPL and RMA-RP respectively.

A HSEERP—Hierarchical secured energy efficient routing protocol for wireless sensor networks

A HSEERP—Hierarchical secured energy efficient routing protocol for wireless sensor networks

Trust And Energy-Aware Routing Protocol for Wireless Sensor Networks Based on Secure Routing

Wireless Sensor Network (WSN) is a network area that includes a large number of nodes and the ability of wireless transmission. WSNs are frequently employed for vital applications in which security and dependability are of utmost concern. The main objective of the proposed method is to design a WSN to maximize network longevity while minimizing power usage. In a WSN, trust management is employed to encourage node collaboration, which is crucial for achieving dependable transmission. In this research, a novel Trust and Energy Aware Routing Protocol (TEARP) in wireless sensors networks is proposed, which use blockchain technology to maintain the identity of the Sensor Nodes (SNs) and Aggregator Nodes (ANs). The proposed TEARP technique provides a thorough trust value for nodes based on their direct trust values and the filtering mechanisms generate the indirect trust values. Further, an enhanced threshold technique is employed to identify the most appropriate clustering heads based on dynamic changes in the extensive trust values and residual energy of the networks. Lastly, cluster heads should be routed in a secure manner using a Sand Cat Swarm Optimization Algorithm (SCSOA). The proposed method has been evaluated using specific parameters such as Network Lifetime, Residual Energy, Throughpu,t Packet Delivery Ratio, and Detection Accuracy respectively. The proposed TEARP method improves the network lifetime by 39.64%, 33.05%, and 27.16%, compared with Energy-efficient and Secure Routing (ESR), Multi-Objective nature-inspired algorithm based on Shuffled frog-leaping algorithm and Firefly Algorithm (MOSFA) , and Optimal Support Vector Machine (OSVM).

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.

Secure Data Transmission in IoT based on Optimization Based Routing Protocol for Wireless Body Area Networks

The security of Internet of Things (IoT) networks has become highly significant due to the growing number of IoT devices and the rise in data transfer across body area networks. The main purpose is to enhance the security level of data transmission between patients and health service providers by considering the availability of energy at sensor nodes through the Wireless Body Area Network. Energy efficiency is considered a foremost challenge to increase the lifetime of a network. To deal with energy efficiency, one of the important systems is selecting the relay node, which can be modeled as an optimization problem. This research proposes the patient health collected data are needed for transmission in IoT-Patient Care Monitoring (PCM) based on the Optimized Routing Protocol along WBANs. The proposed model focuses on a routing mechanism that makes use of an Optimization Routing-based Algorithm along with the relay node selection based on distances and residual energies. DO NOT USE SPECIAL CHARACTERS, SYMBOLS, OR MATH IN YOUR TITLE OR ABSTRACT.