Reliable Routing Research Articles

Reliable routing in MANET with mobility prediction via long short-term memory

A MANET consists of a self-configured group of transportable mobile nodes that lacks a central infrastructure to manage network traffic. To facilitate communication, govern route discovery, and manage resources, all moving nodes in multi-hop wireless networks (MANETs) work together. These networks struggle with dependability, energy consumption, and collision avoidance. The goal of this research project is to establish a new, dependable MANET routing model, where the selection of predictor nodes comes first. For selecting predictor nodes based on factors like distance, security (risk), Receiver Signal Strength Indicator (RSSI), Packet Delivery Ratio (PDR), and energy, the adaptive weighted clustering algorithm (AWCA) is used in this case. Using the Interfused Slime and Battle Royale Optimization with Arithmetic Crossover (IS&BRO–AC) model, the node with the lower weight is selected as the Cluster Head (CH). Additionally, mobility prediction is carried out, in which the node mobility is forecast using Improved Long Short Term Memory (LSTM) while taking distance and Receiver Signal Strength Indicator (RSSI) into account. Based on the forecast, trustworthy data transfer is implemented, ensuring more accurate and dependable MANET routing. The examination of RSSI, PDR, and other metrics is completed at the end.

A cross-layer approach for load balancing and energy-efficient QoS-based routing reliability for UWSN

Considering several fundamental needs of network performance, the Routing and Media Access Control (MAC) layers are crucially checked out for their operations. Sometimes, MAC protocol faces difficulties in modifying the situations over underwater communication which are specifically considered to be dynamic. The nodes in water tend to remain unstable and network fluctuations are made depending upon the number of competitors. The existing hybrid MAC protocol does not possess dynamic network loads. It also involves a lack of modification in access control approaches which provide variations in network loads. Finally, it leads to delayed network performance. The routing layer focus on some difficult parameters like increased packet loss, restricted bandwidth with substantial energy incursion, reduced network lifetime, increased propagation delay, less remaining energy, consistent data transfer, and energy organization which are considered to be the most important research issues in Underwater Acoustic Sensor Networks (UWASNs). In MAC and routing layers, a Cross-layer approach involves some techniques which are discussed and implemented using Ns3 simulation to obtain the performance report. It is also proposed to compare the algorithm with existing techniques to provide accurate results. Reinforcement Learning (RL) in the MAC layer for SINR-based time slot allocation and Integrated Artificial Fish Swarm with Bacterial Foraging Algorithm (IAFSBFA) for energy-aware QoS reliable routing in the network layer are used in this system. In this cross-layer approach, load balancing in the MAC layer and efficient routing using a hybrid algorithm gives out better performance in the underwater network.

Reliable scheduling and routing in robust multiple cross-docking networks design

This study introduces a novel framework called Reliable Pollution Scheduling and Routing with Multi-Cross-Docking. The core idea behind this framework is to optimize the processing and transportation of products through each vehicle, ensuring that each vehicle serves its specified destinations only once before returning to the cross-dock. The objective of this research is to develop a multi-objective mixed integer programming model that efficiently manages scheduling and routing complexities in a multi-cross-docking system, taking into account uncertainties in demand. The primary goals of the model are to minimize the overall costs associated with pollution, loading/unloading, and transportation, while simultaneously reducing distribution and shipping durations. Additionally, the model aims to maximize the reliability of the supply chain for perishable products, contributing to sustainable development in the supply chain domain. To address the inherent complexity of the model, especially in dealing with demand uncertainties, we employ a robust optimization method. The multi-objective challenge is tackled using an innovative hybrid approach that combines goal programming and genetic algorithms. The effectiveness of our proposed solution strategies is rigorously assessed using a variety of metrics and subjected to comprehensive statistical testing. Furthermore, we validate the competence of our methodology by conducting a real-world case study, which includes sensitivity analysis of demand parameters and robustness analysis. Our findings confirm that our solution technique produces high-quality solutions. Notably, our approach optimizes route planning for delivery and pick-up phases, resulting in a significant 36.5% reduction in transportation time and a noteworthy 17.27% decrease in the overall system costs compared to existing conditions. Additionally, we observe a substantial 23.15% reduction in vehicle arrival times at cross-docks, contributing significantly to reduced product expenses.

Trust-Aware and Fuzzy Logic-Based Reliable Layering Routing Protocol for Underwater Acoustic Networks

Routing protocols based on trust mechanisms have been widely investigated for wireless sensor networks, and the works have achieved good results, while there are few works on trusted routing for underwater acoustic networks (UANs). However, trust-aware routing is the key to improving the packet delivery rate and the energy efficiency of UANs. Therefore, inspired by the theory of trust evaluation, a trust-aware and fuzzy logic-based reliable layering routing protocol (TAFLRLR) is proposed. In the TAFLRLR protocol, to avoid the problem of the void area and improve the transmission reliability, the candidate nodes of the next-hop forwarding nodes are determined according to the layers of neighbor nodes. Moreover, a fuzzy logic-based trust evaluation mechanism (FLTEM) is provided, which employs the fuzzy comprehensive evaluation decision model to calculate the comprehensive trust value for underwater sensor nodes. Further, the node density of a candidate node and its comprehensive trust value are taken as the input of a fuzzy control system and the forwarding probability (FP) of the node is taken as the output, and the candidate node with the highest FP is selected as the best forwarding node. Simulation results illustrate the superiority and effectiveness of the TAFLRLR protocol in terms of energy efficiency, routing reliability, and transmission reliability.

K-means online-learning routing protocol (K-MORP) for unmanned aerial vehicles (UAV) adhoc networks

Unmanned Aerial Vehicles (UAVs) have become a hot topic due to their flexible architecture adopted in many wireless technologies. In UAV ad hoc networks, traditional routing protocols with a fixed topology are ineffective due to dynamic mobility and unstable paths. Therefore, the mobility patterns of UAVs challenge efficient and reliable routing in UAV networks. Traditional routing algorithms are often based on assumptions of static nodes and predetermined network topologies. Which are not suitable for the dynamic and unpredictable nature of UAV mobility patterns. To address this problem, this paper introduces a K-means online learning routing protocol (KMORP) scheme employing a Markov mobility model for UAV ad hoc networks. Initially, the proposed method utilizes a 3D Gauss Markov mobility model to accurately estimate UAV positions, while K-means online learning is adopted for dynamic clustering and load balancing. Designed for real-time data processing, KMORP is well suited for UAV ad hoc networks, quickly adapting to network environmental changes such as UAV mobility, interference, and signal degradation to ensure efficient data transmission and communication. This is achieved while reducing the overall communication overhead and increasing the packet delivery ratio(PDR%). In the routing phase, the proposed scheme employs inter-cluster forwarding nodes to transmit messages among different clusters. Extensive simulations demonstrate the performance of the proposed KMORP, showing a 38% better PDR compared to OLSR and over 50% less end-to-end(E2E) delay compared to typical K-Means. Furthermore, the proposed KMORP exhibited an average throughput of 955 kbps, showing a substantial improvement in network performance. The results underscore that the proposed KMORP outperforms existing techniques in terms of PDR, E2E delay, and throughput.

Reliable and Secure Congestion Aware Routing Protocol for Wireless Sensor Network

Reliable and Secure Congestion Aware Routing Protocol for Wireless Sensor Network

A Trust and Node Capability Model for Reliable and Secure MANET Communication

The Mobile Ad-hoc Network (MANET) is a rapidly deployable network. That is valuable for industrial and domestic applications due to flexible, mobile, and wireless communication. But the network is constrained with resources and security. In this paper, we are presenting a node capability based trusted routing named TNC-AODV for MANET. It is a hybrid approach for maintaining route reliability and security. The model is composed of the property of node capability and Trust. The Node capability is defined by the quality of service parameters like remaining energy, available bandwidth, buffer length, and mobility pattern. The aim is to ensure the discovery of reliable routes. Additionally, the trust is implemented by using a local and global trust for securing the network. The TNC-AODV is implemented through modification of AODV routing. That routing technique has been tested on three security threats namely Black-hole, wormhole, and DOS flooding attack. The simulation has been carried out using the NS2 simulator. The experimental results demonstrate that TNC-AODV provides security against attacks. Additionally, improve the packet delivery ratio, and throughput. Finally, the possible and feasible future extension of the work has also been proposed.

A Reliable Network Routing Protocol Design with an Intelligent Mobile Sink and Energy Efficiency over Wireless Sensor Network

This is crucial for the successful operation of a Wireless Sensor Network, frequently called as WSN as each of the sensor nodes in the network's structure are in charge of transmitting the information from its original source to its final destination. Several researchers have developed a Mobile sink in an effort to enhance transmission quality. Although it has been shown to be beneficial, the network's overall reliability is compromised by the much more energy-intensive operation of the nodes. In this research, we offer a routing strategy that makes use of cluster and source portability to drastically reduce power usage. We have given this protocol its name: the Intelligent Mobile Sink Assisted Routing Protocol (IMSARP). To get started, we divide an entire sensor environment into regions, and within each of them, members cast proportional votes to choose who will serve as the Cluster-Head (CH). To determine how to choose the most efficient choice, nodes in the network evaluate the power consumption of all feasible routes. The proposed IMSARP method uses a cluster-based paradigm to construct a mobile-sink routing protocol. The standard quantity of energy within all the clusters serves as what drives the sink's motion. The outcomes section of this research proves the legitimacy and maintains the credibility of the proposed system by presenting the results, which include throughput, delay reduction, energy efficiency, and data transfer rate.

Performance Evaluation of Routing Protocols for Vehicle Re-Routing in ITS-based Vehicular Networks

This study aims to assess the performance of routing protocols in Intelligent Transportation System (ITS)-based vehicular networks, specifically in accident and highway scenarios. The effective management of traffic flow in these situations is crucial for ensuring the safety and smooth operation of vehicular networks. Therefore, it is imperative to evaluate routing protocols to identify the most suitable one for these scenarios. The evaluation considers various commonly used routing protocols in vehicular networks, including Ad hoc On-Demand Distance Vector (AODV), Ad hoc On-Demand Multipath Distance Vector (AOMDV), and Destination-Sequenced Distance Vector (DSDV). The evaluation is based on several performance metrics, such as packet delivery ratio, end-to-end delay, network throughput, normalized routing load, and routing overhead. These metrics provide insights into the effectiveness and efficiency of the routing protocols in handling re-routing in accident and highway scenarios. The research is divided into two modules, Module I and Module II, to evaluate the effectiveness of routing protocols in these distinct scenarios using the NS2 simulation tool. The simulation results are analyzed and compared to determine the performance of the routing protocols in each module. The findings indicate that AODV consistently achieves the highest throughput, packet delivery ratio, and lowest end-to-end delay, routing overhead, and normalized routing load, followed by AOMDV and then DSDV. The findings of this study contribute to the understanding of the strengths and weaknesses of different routing protocols in accident and highway scenarios. This knowledge can assist in the development of more efficient and reliable routing protocols for vehicular networks.

The Subcalcaneal Fat Pad: An Innovative Space for Passage of the Pedicle in Free Flap Reconstruction of Lateral Heel Defects.

Soft-tissue defects of the lateral heel remain a challenge for reconstructive surgeons. Although a reliable vascular supply for free flap anastomosis is available anteriorly from the anterior tibial vessels and medially from the posterior tibial vessels, the vascular anatomy of the lateral side lacks suitable donor vessels for free flap anastomoses. Although the pedicle can be passed either ventrally beneath the skin or dorsally between the Achilles tendon and calcaneus, these passages are hardly applicable for lateral heel defects. We identified the space between the plantar surface of the calcaneus and the plantar aponeurosis as an innovative approach for reconstruction. Therefore, we propose the subcalcaneal fat pad as an alternative and reliable route for the passage of the flap pedicle to the posterior tibial vessels in free flap reconstruction of soft-tissue defects in the lateral calcaneal region. Consequently, the vascular pedicle can be safely anastomosed to the posterior tibial vessels. This approach provides a new option for recipient vessels in free flap reconstruction.

Evaluating the Advantages and Challenges of Mobile Ad-Hoc Networks

Mobile Ad-Hoc Networks (MANETs) are decentralized assemblies of mobile nodes, including smartphones, laptops, iPads, and PDAs, that operate autonomously, contrasting with conventional wireless networks. These networks dynamically adapt their topology and routing tables as nodes join or leave, ensuring a seamless data packet transmission. This article aims to provide a comprehensive overview of MANETs, elucidating their advantages, challenges, and diverse applications. Unlike traditional networks that require a centralized administrator, MANETs enable mobile nodes to exchange data packets solely through wireless links. However, the volatile topologies and limited resources challenge establishing a power-efficient and secure routing system. This study introduces a reliable routing mechanism considering network power consumption and node reputation. Utilizing a Krill Herd-based Grasshopper Optimization Algorithm (KH-GOA), in conjunction with a reputation model, the proposed system establishes a trustworthy route between the origin and destination nodes. The reputation model considers node mobility, actual capabilities, historical performance, and peer reviews. Upon evaluating these reputation metrics, the KH-GOA method is employed, amalgamating the Krill Herd (KH) and Grasshopper Optimization Algorithm (GOA) techniques. The proposed KH-GOA-based routing protocol considers multi-objective criteria like reputation, power efficiency, distance, and latency for optimal route selection.

Development of a molecularly imprinted photoelectrochemical sensor for enhanced detection of ciprofloxacin in milk

In this work, a molecularly imprinted polymer (MIP)-based photoelectrochemical (PEC) sensor for the detection of ciprofloxacin (CIP) was constructed. Carbon-modified ZnO (ZnO/C) nanocomposite with adjustable zinc content was prepared by a carbonaceous method, facilitating visible light absorption and electron transition. The structure, morphology, and surface chemistry of ZnO/C were well characterized. The MIP membrane was formed by electropolymerizing, with ZnO/C nanocomposite, o-phenylenediamine (C6H4(NH3)2,o-PD), and CIP as highly efficient photoactive materials, functional monomer, and template, respectively. The PEC properties of different photoactive electrodes were measured and analyzed. The MIP-based PEC sensor showed excellent sensitivity and selectivity towards CIP, displaying a broad linear range from 0.01 nM to 1000 nM, a low detection limit of 8.41 pM, and satisfied recovery rates within 96.8%103.2%. The sensor exhibited reliable reproducibility and stability, with a relative standard deviation (RSD) of 2.48% for the CIP in milk. The constructed MIP-based PEC sensor not only provides a powerful and reliable route for the detection of CIP, but also can be extended to detect other antibiotics in food and natural environment.

Electrospun Highly Aligned IGZO Nanofiber Arrays with Low‐Thermal‐Budget for Challenging Transistor and Integrated Electronics

AbstractMetal oxide field‐effect transistors (MOFETs) represent a promising technology for applications in existing but alsoemerging large‐area electronics. Simultaneously, the rise of 1D nanomaterials with unique properties, represented by nanofibers (NFs), has also energized research. Thus, developing 1D nanofiber networks (NFNs) to act as the potential building blocks for use in fundamental elements of transistors is considered to be a promising approach torealize high‐performance 1D electronics. However, high processing temperatures and disordered nanofiber distribution represent two remaining technical challenges. Here, electrospun highly aligned IGZO (a‐IGZO) nanofiber arrays with low‐thermal‐budget of 350 °C and impressive device characteristics are achieved, including a μFE of 5.63 cm2 V–1 s–1 and superior on/off current ratio of ≈107. When ALD‐derived high‐k HfAlOx thin films are employed as gate dielectrics, the source/drain voltage (VDS) can be substantially reduced by ten times to a range of only 03 V, along with a three times improvement in mobility to a respectable value of 15.9 cm2 V–1 s–1. Successful integrations of logic operation, sensor, and flexible devices implies the potential prospect of a‐IGZO NFN FETs in multifunctional electronics. The strategy for combining cryogenic processes and parallel arrays provides a feasible and reliable route in building future low‐power, high‐performance flexible electronics.

3R: A reliable multi agent reinforcement learning based routing protocol for wireless medical sensor networks

Interest in the Wireless Medical Sensor Network (WMSN) is rapidly gaining attention thanks to recent advances in semiconductors and wireless communication. However, by virtue of the sensitive medical applications and the stringent resource constraints, there is a need to develop a routing protocol to fulfill WMSN requirements in terms of delivery reliability, attack resiliency, computational overhead, and energy efficiency. This paper proposes 3R, a reliable multi agent reinforcement learning routing protocol for WMSN. 3R uses a novel resource-conservative Reinforcement Learning (RL) model to reduce the computational overhead, along with two updating methods to speed up the algorithm convergence. The reward function is re-defined as a punishment, combining the proposed trust management system to defend against well-known dropping attacks. Furthermore, an energy model is integrated with the reward function to enhance the network lifetime and balance energy consumption across the network. The proposed energy model only uses local information to avoid the resource burdens and the security concerns of exchanging energy information. Experimental results prove the lightweightness, attacks resiliency and energy efficiency of 3R, making it a potential routing candidate for WMSN.

The Importance of Lapis Lazuli Corridor for Afghanistan

Lapis lazuli corridor is one of the most important and new transit routes which Afghanistan connects to central Asia countries and other countries. Lapis Lazuli corridor has a historical background and was part of the Silk Road through which the lapis lazuli of Afghanistan (from Badakhshan) was exported over 2000 years ago to the Caucasus, Russia, the Balkans, Europe, and North Africa, especially to the eastern civilizations along the ancient Silk Road. The lapis lazuli trade route connects Afghanistan and South Asia countries with Europe by roads and rails. It is considered one of the shortest and most reliable transit routes for Afghanistan where it has named a landlocked country, in order to get connected to Europe. The importance of this route is that to emerge as an economic corridor for inclusive development by which Afghanistan will be connected to Europe, Turkmenistan, Azerbaijan, Georgia and Turkey and then to Europe. It will connect Afghanistan through land and sea with developed and economic zones of central Asia and European countries, where it will provide more opportunities for Afghanistan to trade it’s all kind of products to other nations. In addition, it will be discussed the importance of this transit route for Afghanistan as a new economic policy of Afghanistan which conducted by Afghan government to connect this country with Central Asia countries and Europe. The main object of this essay covers the socio-cultural significances of the lapis lazuli route for Afghanistan and other nations which located on this way. Moreover, I will find out the cultural and social importance of lapis lazuli corridor in this essay to know its geographical location and its other important issues from articles and journals which discuss about the lapis lazuli corridor as a new economic way for Afghanistan.

Peli-Remo Optimization Algorithm for Reliable routing in MANET: K-means node clustering process and CNN based Energy Prediction

MANET, an ad hoc wireless network is made up of several nodes connected, governed by certain rules for packet movement from one node point to another. The structure of communication may be designed using a variety of protocols. For an ad hoc network, routing protocols are used to manage the connections. It must manage several issues, including supporting mobile devices and reducing overhead when nodes only have access to a portion of the resources. In order to improve the communication, this article suggests an effective MANET cluster-based routing paradigm for multimedia communication. The clustering process is started using the K-means clustering method. The Deep Convolutional Neural Network (DCNN) model will first predict the node energy. The cluster head will be chosen using the Hybrid Remora with Pelicon Optimization technique (HRPOA), that integrates the Remora optimization technique and the Pelican optimization algorithm. Further, reliable retransmission will increase the communication's reliability.

Reliable route planning and time savings in real-world urban intermodal transportation networks: Evidence from Hamburg, Germany

Reliable route planning and time savings in real-world urban intermodal transportation networks: Evidence from Hamburg, Germany

Cluster control technology of transmission line intelligent inspection drones based on 5G communication

Abstract This paper firstly analyzes the network topology model of the UAV cluster network and wireless 5G communication channel model by modeling and briefly analyzes the idea of topology movement control for flying self-organized networks. Then, a cluster-based structure and reinforcement learning clustered routing protocol is proposed for the problem of easy breakage of routing forwarding paths caused by smart inspection of transmission lines based on UAV clusters for 5G communication. Finally, a cluster structure-based precedence routing protocol is designed, an adaptive routing protocol based on location and link quality Q-learning is used between clusters, and fast and reliable routing is achieved by combining the routing table maintained by itself. The simulation results show that ARP-L-Q (average end-to-end delay 4.22, average packet loss rate 88.09%, average packet rate 2.37, average control overhead 2.52) protocol performs better than GPSR and GACB protocols, and the experiment verifies that ARP-L-Q protocol can better achieve the high dynamic reconfiguration, high stability and reliability, and low communication delay of UAV cluster-based 5G communication network. Characteristics and requirements. This study has application prospects in both civil emergency and military mobile communication and has certain military significance, theoretical value and application value for thus promoting UAV innovation.

Advances in Phytonanotechnology: A Plant-Mediated Green Synthesis of Metal Nanoparticles Using Phyllanthus Plant Extracts and Their Antimicrobial and Anticancer Applications.

Nanoparticles and nanotechnology developments continue to advance the livelihood of humankind. However, health challenges due to microorganisms and cancerous cells continue to threaten many people's lives globally. Therefore, new technological interventions are of great importance. The phytochemicals present in medicinal plants are suggested as biocompatible, cost-effective, and regenerative sources that can be utilized for the green synthesis of nanoparticles. Different plant extracts with various phytochemical constituents can form nanoparticles with specific shapes, sizes, and optical properties. This review focuses on advances in green nanotechnology and provides details on reliable synthetic routes toward medically and biocompatible relevant metallic nanoparticles. We cover a wide range of applications that use phytonanoparticles with an in-depth look at what makes these materials interesting. The study also provides details of the literature on the interventions made in phytonanotechnology for the production of plant-mediated synthesis and capped metallic nanoparticles and their applications in various industries. It was observed that a variety of plants have been well studied, and detailed findings have been reported; however, the study of Phyllanthus is still in its early stages, and more needs to be uncovered.

Fr-Aro: Secure interference aware fuzzy based clustering and hybrid optimization driven data routing in VANETs

Vehicular ad hoc network (VANET) is composed of a group of nodes or vehicles that enable communication with other connected vehicles despite a lack of infrastructure. To design a reliable routing protocol is a major challenge for ensuring effective data communication among vehicles. This research develops a fuzzy logic concept to cluster the nodes and a Cluster Head is selected based on the fitness constraints. Thereafter, the optimal path used to route the data packets are selected using the proposed Fr-ARO based on the fitness, like energy consumption, delay, distance, Signal-to-Interference Ratio (SIR), entropy-weighted model, and trust factors. Some of the trust parameters considered for the routing mechanism are direct trust, indirect trust, historical trust, recent trust, and availability factor. Moreover, the optimal path is computed by the developed Fr-ARO algorithm that is devised through the incorporation of Aquila Optimizer (AO) with Remora Optimization Algorithm (ROA). The proposed model attains higher performance with the metrics, like energy, trust, distance, and SIR of 0.5744 J, 0.6123, 3.062 m, and 38.4674.