Reliable Routing Research Articles

Iris: Towards Intelligent Reliable Routing for Software Defined Satellite Networks

Iris: Towards Intelligent Reliable Routing for Software Defined Satellite Networks

Deterministic Scheduling and Reliable Routing for Smart Ocean Services in Maritime Internet of Things: A Cross-Layer Approach

Deterministic Scheduling and Reliable Routing for Smart Ocean Services in Maritime Internet of Things: A Cross-Layer Approach

Hybrid optimisation-based reliable routing with traffic management and congestion control

Hybrid optimisation-based reliable routing with traffic management and congestion control

Reliable Routing for V2X Networks: A Joint Perspective of Trust-Prediction and Attack-Resistance

Reliable Routing for V2X Networks: A Joint Perspective of Trust-Prediction and Attack-Resistance

Mechanism study and preparing (hetero)arylidene malononitriles through a greener and scalable catalytic strategy

One of the important concerns in the field of catalysis is to find a reliable route to reduce the transition energies to reach the corresponding product. The mechanism of Knoevenagel condensation of 2-chlorobenzaldehyde and malononitrile in the presence of imidazole, an organocatalyst, is investigated through control experiments. In this study, the interactions and intermediates in synthesizing 2-chlorobenzylidenemahmonitrile (CS) are studied by FTIR and NMR analyses. First, a screen activity of seven nitrogen-based organocatalysts for preparing 2-chlorobenzylidenemahmonitrile (CS) was conducted in ethanol, an eco-friendly medium. The conversion of 100 % and excellent yields were obtained in a short reaction time. The products could be crystallized directly from the reaction solution. After separating pure products, the residue solution was employed directly in the next run without any concentration, activation, purification, or separation. Then, the generality and substrate scope of the new strategy were investigated in the presence of imidazole as a selected nitrogen-based organocatalyst. In addition, the scale-up synthesis of 2-chlorobenzylidenemahmonitrile (CS) was carried out, afforded crystalline products with 95 ± 2 % yield in five consecutive runs. Energy efficiency, cost saving, greener conditions, the use of catalytic loading organocatalyst and its high recyclability, prevention of waste, and recycling extractant by a rotary evaporator for non-crystallized products, demonstrate the newly developed metal-free and halogen-free catalytic methodology as a more sustainable process for the synthesis of (hetero-)arylidene malononitriles in the laboratory and industrial scale.

Improved Reinforcement Learning for Reliable Routing in Medical Wireless Sensor Networks

Improved Reinforcement Learning for Reliable Routing in Medical Wireless Sensor Networks

A facile solid state synthesis route to tantalum oxynitride, β-TaON

Tantalum oxynitride is a prospective pigment and has attracted considerable recent attention as a photocatalyst for the overall splitting of water under visible light irradiation. Conventionally, TaON is synthesised by the thermal ammonolysis of Ta2O5, a process which remains challenging to scale up. The use of ammonia/water or ammonia/oxygen within a narrow temperature window is required to produce high purity TaON material; otherwise Ta3N5 forms as the favoured ammonolysis product. It would be highly beneficial to develop a reliable, simpler and reproducible synthesis route to TaON without the use of gaseous ammonia under such complex conditions. This paper describes a facile synthesis route to monoclinic β-TaON (space group P21/c) using Ta3N5 itself as a solid state nitrogen source. After 6 h of reaction at 900 °C under vacuum followed by post-synthesis calcination at 580 °C for 30 min, the bright yellow oxynitride is produced as spherical particles ca. 80 nm in diameter with a direct band gap of 2.9 eV.

Developing a reliable route protocol for mobile self-organization networks

Mobile ad hoc networks (MANETs), which correspond to a novel wireless technology, are widely used in Internet of Things (IoT) systems such as drones, wireless sensor networks, and military or disaster relief communication. From the perspective of communication and data collection, the success rate of collaborations between nodes in mobile ad hoc networks and reliability of data collection mainly depend on whether the nodes in the network operate normally, namely, according to the established network rules. However, mobile ad hoc networks are vulnerable to attacks targeting transmission channels and nodes owing to their dynamic evolution, openness, and distributed characteristics. Therefore, during the network operation, it is necessary to classify and detect the behavior and characteristics of each node. However, most existing research only analyzes and considers responses against a single or small number of attacks. To address these issues, this article first systematically analyzed and classified common active attacks in MANETs. Then, a node trust model was proposed based on the characteristics of various attacks; subsequently, a new secure routing protocol, namely, TC-AODV, was proposed. This protocol has minimal effect on the original communication dynamics and can effectively deal with Packet drop, wormhole, Session hijacking, and other main attacks in MANETs. The NS3 simulation results show that the proposed routing protocol attains good transmission performance, can effectively identify various attacks and bypass malicious nodes, and securely complete the communication process.

IMPLEMENTATION OF RT / RW NET HOTSPOT NETWORK WITH MIKROTIK-BASED VOUCHER SYSTEM AT UNITEX BOGOR HOUSING

Technological developments are currently growing very rapidly, especially the use of computer networks. The use of the internet is increasing because it makes it easier for everyone to dig up existing information from the internet world, internet access has become a basic need for society. One effective way to provide internet access to the public is through the RT/RW Net network. However, there are still several obstacles in managing the RT/RW Net network in the Unitex housing complex in Bogor City, such as use that is not well controlled, many users who are not interested and do not have the right to use hotspot facilities by knowing the password for the Wi-Fi network in the housing complex. Unitex. To overcome these obstacles, the author proposes implementing an RT/RW Net network with a MikroTik-based voucher system. MikroTik is a network device that has reliable routing, switching and wireless capabilities. By utilizing MikroTik, RT/RW Net network managers can better manage and control internet access for users. By implementing the hotspot voucher login web page system provided by the Hotspot Server on the Mikrotik Router, to provide authentication features for users who will use the Hotspot/Wi-Fi network. So registered users are required to enter their username and password on the web login page provided by Mikrotik to be able to access the internet via the RT/RW Net Hotspot network. The research methods used in this research are observation, questionnaires, and literature studies, as well as the Network Development Life Cycle (NDLC) Method which is used to analyze needs in implementing the Rt/Rw Net Hotspot Network in the Unitex housing complex in the city of Bogor

Cu Tailoring Pt Enables Branched-Structured Electrocatalysts with High Concave Surface Curvature Toward Efficient Methanol Oxidation.

Surface engineering offers opportunities for the design and synthesis of Pt-based alloyed electrocatalysts with high mass activity and resistance to CO poisoning, which is of great significance for methanol electrooxidation. Surface curvature regulation may endow electrocatalysts with enhanced atomic utilization and abundance of unsaturated atoms; however, a reliable synthetic route for controlled construction of tailorable curved surface is still lacking. Here, a colloidal-chemical method to synthesize two types of PtCu branched-structured electrocatalysts, where the concave curvature can be customized is reported. These studies show that, among various synthesis parameters, the concentration of CuCl2·2H2O precursor is the key factor in manipulating the reaction kinetics and determining the concave surface curvature. Significantly, PtCu branched nanocrystals with long and sharp arms (PtCu BNCs-L), featuring a high concave surface curvature, exhibit remarkable activity and stability toward MOR, which is mainly attributed to advanced features of a highly concave surface and the synergistically bifunctional effect from introduced oxophilic Cu metal. In situ Raman spectroscopy and CO stripping test demonstrates weakened CO adsorption and accelerated CO removal on PtCu BNCs-L. This work highlights the importance of surface curvature, opening up an appealing route for the design and synthesis of advanced electrocatalysts with well-defined surface configurations.

Energy Management and Networking for Sensor-based Transmission Line State Monitoring

The transmission line condition monitoring sensor network is large in scale and difficult to maintain. Its long-chain network topology differs from general wireless sensor networks, so it is necessary to develop a self-organizing sensor network with self-energy harvesting. In this regard, a three-layer network model is designed. Three types of node models are constructed. The sensor nodes implement round-robin sleep/wake and energy management mechanisms, powered by self-harvested energy. Additionally, reliable routing between nodes is established. Simulation results show that the developed simulation model is suitable for the application of transmission line condition monitoring. The expected functions of each module have been realized, and the stable and reliable transmission of perceived data of key components of transmission lines has been achieved, thereby providing technical and data basis for the deployment of practical networks.

Energy aware reliable routing model for sensor network enabled internet of things environment

Wireless sensor networks (WSNs), which are facilitated by the internet of things (IoTs), can be difficult to improve the lifespan of the network target area. Although the hotspot issue (i.e., the cluster head closest to the base station fails quickly) is mitigated by the clustered-based routing technique, it still has an important effect on the network's lifespan and target area. However, improper distribution of load between cluster heads has been shown to negatively impact network lifespan efficiency, so even though unequal clusters have been utilized successfully to tackle the hotspot issue, further work is needed. This study provides an energy-aware reliable routing (EARR) model for resolving the hotspot as well as load balancing issues simultaneously. To extend the lifespan of the network, the EARR model effectively minimizes energy consumption by the cluster heads using enhanced multi-objective optimization parameters. Further, EARR provides improved routing optimization metrics to improve data delivery with energy efficiency, less delay, and packet loss. The results of the experiments demonstrate that the EARR model provides excellent throughput and lifespan efficiency with low delay and communication overhead.

Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method

Reliable and Scalable Routing Under Hybrid SDVN Architecture: A Graph Learning Based Method

REER-H: A Reliable Energy Efficient Routing Protocol for Maritime Intelligent Transportation Systems

REER-H: A Reliable Energy Efficient Routing Protocol for Maritime Intelligent Transportation Systems

Cycle‐Consistent Generative Adversarial Network and Crypto Hash Signature Token‐based Block chain Technology for Data Aggregation with Secured Routing in Wireless Sensor Networks

SummaryA fundamental component of Wireless Sensor Networks (WSN) is routing, because it is responsible for data transmission to the base stations (BS). Routing attacks are attacks that have the ability to interfere with the operation of WSN. A reliable routing system is needed for guaranteeing routing security including WSN effectiveness. Many studies have been conducted to improve trust among routing nodes, cryptographic algorithms and centralized routing decisions. Nevertheless, most of the routing techniques are not practical because it is challenging to detect suspicious actions of routing nodes. Generally, there is lack of reliable technique for preventing malicious node attacks. Therefore in this manuscript, Cycle‐Consistent Generative Adversarial Network (CCGAN) optimized with Ebola Optimization Search Algorithm (EOSA) and Crypto Hash Signature (CHS) Token‐based Block chain (BC) Technology for Data Aggregation with Secured Routing in Wireless Sensor Networks (SR‐CCGAN‐EOSA‐BDA‐WSN) is proposed for data aggregation with secured optimum routing in WSN. The proposed methodology uses a Proof of Authority (PoA) method in the block chain network to authenticate the process of node transmission. A Cycle‐Consistent Generative Adversarial Network optimized with the Ebola optimization algorithm methodology (CCGAN‐EOSA) is used to select the validation group required for proofing and select the proper next hop as a forwarding node proficient of securely and easily transmitting messages. The performance metrics, like delay, average latency with energy consumption, block chain token transactions throughput is analyzed. The performance of SR‐CCGAN‐EOSA‐BDAWSN proposed method provides 76.26%, 65.57%, and 42.9% lesser delay under 30% spiteful routing environment; 73.06% are compared with existing methods.

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.