Reliable Routing Research Articles

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

Electrothermal therapy for the in vivo elimination of circulating tumor cells by using a functionalized injection needle

The elimination of circulating tumor cells (CTCs) has recently emerged as a reliable route to inhibit metastasis of cancer. Despite some progress of photodynamic therapy and photothermal therapy (PTT), their unsatisfying efficacy or difficult operation has limited their clinical application. Herein, inspired by an immersion heater, an electrothermal therapy (ETT) strategy for the elimination of CTCs in the peripheral blood was proposed by using a functionalized injection needle. CTCs can be captured by the nanostructured surface of the injection needle and then killed in the energized state due to the temperature increase caused by electrothermal conversion. ETT not only avoids the irradiation through an external light source but also controls the temperature of the needle more easily and accurately than PTT. Thus, this study proposes a more applicable strategy for the elimination of CTCs.

Fault-tolerant partition resolvability of cycle with chord.

In the realm of connected networks, distance-based parameters, particularly the partition dimension of graphs, have extensive applications across various fields, including chemistry and computer science. A notable variant of the partition dimension is the fault-tolerant resolving partition, which is critical in computer science for networking, optimization, and navigation tasks. In networking, fault-tolerant partitioning ensures robust communication pathways even in the event of network failures or disruptions. In optimization, it aids in developing efficient algorithms capable of withstanding errors or changes in input data. In navigation systems, fault-tolerant partitioning supports reliable route planning and navigation services under uncertain or dynamic conditions. This paper focuses on the fault-tolerant partition dimension within the specific context of the cycle with chord graphs, exploring its properties and implications for enhancing the robustness and reliability of networked systems.

Synthesis of Oil-Soluble Polymer-Grafted Carbon Dots with Outstanding Colloidal Stability and Tribological Properties in Polyalphaolefin.

Herein, a series of polylauryl methacrylate-grafted CDs (CDs-PLMA-m, m denotes the reaction time in hours) with core-shell structure were synthesized via surface-initiated atom-transfer radical polymerization (SI-ATRP). Due to the good solubility of PLMA in hydrocarbons, all of the CDs-PLMA-m can be facilely dispersed in polyalphaolefin (PAO) to form pellucid colloidal dispersions. The reciprocating ball-on-plate sliding friction tests proved that the addition of 3.0 wt % CDs-PLMA-1 markedly lessened the wear and friction of PAO by 53.0 and 40.0%, respectively. The tribological performances of the CDs-PLMA-1 (3.0 wt %)/PAO dispersion did not attenuate sharply when the friction duration extended from 20 to 200 min or the applied load increased from 20 to 100 N, revealing the long lifetime and desirable load-carrying effect of CDs-PLMA-1. Based on the friction tests, the antifriction behavior of CDs-PLMA-1 was related to the synergies between the molecular lubrication of PLMA-1 brushes and the nanolubrication of CDs. Furthermore, the wear analyses disclosed the deposition of tribofilm composed of a lot of CDs-PLMA-1 and a spot of iron oxides, which provided oxidation resistance and an antiwear function. This study established a reliable route to the synthesis of oil-soluble polymer-grafted CDs, enabling high-efficiency lubrication of CDs in PAO.

Spiking Quantum Fire Hawk Network Based Reliable Scheduling for Lifetime Maximization of Wireless Sensor Network

ABSTRACTManaging energy consumption poses a substantial challenge within Wireless Sensor Networks (WSN) due to frequent communication among sensor nodes. A reliable scheduling framework presents a promising solution for maximizing WSN lifetime, minimizing energy consumption, and ensuring robust communication. Despite various proposed methods for reliable scheduling, energy consumption remains high. To address this, a spiking quantum fire hawk network‐based reliable scheduling in WSN is introduced. This research incorporates clustering, duty‐cycle management, and reliable routing to enhance energy efficiency. An improved Nutcracker Optimization‐based Cluster Head (CH) election and Spiking Quantum Fire Hawk Network duty cycling contribute to optimal CH selection and increased network lifetime. Additionally, a Link Quality‐based Energy Aware Proficient Trusted Routing Protocol (LQEAP‐TRP) minimizes data transmission delay, offering reliable routing. Finally, the data communication is done in the reliable route. The developed approach is executed in Network Simulator and validated with the existing protocols. The results of the simulations indicate that the proposed approach achieves a network lifetime of 99.34% and a packet delivery ratio of 99.95%.

Epoxidation of Chalcone Derivatives under Visible-Light Irradiation: An Organophotoredox Catalytic Approach

AbstractEpoxidation of α,β-unsaturated ketones under visible-light irradiation constitutes a significant chemical transformation with potential applications in the synthesis of epoxypropane derivatives. An organophotoredox catalytic system is herein reported to facilitate efficient aerobic epoxidation. This protocol enables the conversion of α,β-unsaturated ketones into their corresponding epoxy products with moderate to high yields under benign reaction conditions. The methodology demonstrates broad functional-group compatibility, providing a reliable and direct route to a variety of functionalized epoxypropane compounds. Additionally, the absence of heavy metals in this strategy renders it particularly suitable for the pharmaceutical industry, offering a new avenue for the synthesis of epichlorohydrin drugs.

DAR-DRL: A dynamic adaptive routing method based on deep reinforcement learning

Mobile-centric wireless networks offer users a diverse range of services and experiences. However, existing intelligent routing methods often struggle to make suitable routing decisions during dynamic network changes, significantly limiting transmission performance. This paper proposes a dynamic adaptive routing method based on Deep Reinforcement Learning (DAR-DRL) to effectively address these challenges. First, to accurately model network state information in complex and dynamically changing routing tasks, we introduce a link-aware graph learning model (LA-GNN) that efficiently senses network information of varying structures through a hierarchical aggregated message-passing neural network. Second, to ensure routing reliability in dynamic environments, we design a hop-by-hop routing strategy featuring a large acceptance domain and a reliability guarantee reward function. This mechanism adaptively avoids routing holes and loops across various network scenarios while enhancing the robustness of routing under dynamic conditions. Experimental results demonstrate that the proposed DAR-DRL method achieves the network routing task with shorter end-to-end delays, lower packet loss rates, and higher throughput compared to existing mainstream methods across common dynamic network scenarios, including cases with dynamic traffic variations, random link failures (small topology changes), and significant topology alterations.

Service Quality and Passenger Satisfaction on the Coastal Routes of Southwest Crete

The aim of this paper is to validate the correctness of the defining variables (categories) used by Sitzimis (2024a) to measure the quality of services provided on the coastal lines of southwest Crete. In this context it tries to determine both how much they affect the overall passenger satisfaction and which one is the most important. This research is both novel and distinct and could hopefully be expanded to include comparable coastal routes around the world and other means of transport. It is also expected to benefit shipowners, passengers, and policymakers by maintaining the level of services provided at a satisfactory level. Methodologically, we have used confirmatory factor analysis to determine the real factors affecting the quality of coastal services in southwest Crete. A non-parametric correlation test has been applied between the degree of satisfaction and the above factors. It has shown that there is a moderate positive correlation. We have tested through multiple regression both the extent to which these factors have an impact on passengers’ satisfaction and their relative significance. The resulting evaluation factors are "comfort, safety, land and on-board services", "pricing policy" and "route reliability". They have predicted 63.5% of passengers’ satisfaction variance and the first factor is the most significant. Their improvement is expected to stimulate the users’ satisfaction. Ιt appears that the five categories used by Sitzimis, and their hierarchical classification, have not been fully confirmed by the factor analysis.

Versatile synthesis of 2-functionalized dihydrothiazolo[2,3-b]quinazolines through regioselective electrophilic intramolecular heterocyclization of 3-alkenyl-2-thioxoquinazolin-4-ones

Electrophilic intramolecular heterocyclizations of 3-alkenyl-2-thioxoquinazolin-4-ones, induced by halogens, NBS, sulfuryl chloride, protic acids, selenium, or tellurium halides, proceed with high regioselectivity. This process leads to the formation of 2-functionalized dihydrothiazolo[2,3-b]quinazolines, showcasing the versatility and reliability of this synthetic route across various electrophilic reagents.

A Kelp Inspired High‐Power Density Triboelectric Nanogenerator with Stacking Structure for Multiple Directional Ocean Wave Energy Harvesting

AbstractOcean wave energy is one of the most promising green energies in the wild. However, it is still challenging to effectively collect wave energy due to its randomness and irregularity. In this work, a kelp inspired high‐power density triboelectric nanogenerator (K‐TENG) is presented for harvesting wave energy with characteristics in multiple directions. The proposed K‐TENG consists of a series of stacked leaf‐like units. The influence of configuration parameters, including pellet diameters, pellet numbers, unit sizes, oscillation frequency, swing amplitude, and wave directions on output performances of leaf‐like units, are extensively investigated. Experimental data indicates that a single leaf‐like unit can achieve a maximum output voltage of 623.14 V as well as a maximum current of 1.48 µA and realize energy harvesting from different wave directions. A K‐TENG composed of 15 leaf‐like units demonstrates a high‐power density of 18.77 W m−3 at a wave frequency of 2.5 Hz, which successfully powers a digital watch and 414 light‐emitting diodes (LEDs). This work is hoped to provide a simple and reliable route to effectively harvest ocean wave energy.

The Effect of Railway Projects Increasing Safety on the Frequency of Occurrences

This contribution is focused on the presentation of individual research results aimed at evaluating the socio-economic impacts associated with increasing the safety and reliability of the railway transport route. The goal of the research is to propose and subsequently verify an original approach for assessing the impact of the implementation of investment projects, including measures aimed at increasing the safety and reliability of railway transport routes, on the resulting number of occurrences that happen on the railway in the Czech Republic. The proposed procedure is based on several key documents. In addition to already existing national methodologies, these are mainly the database of occurrences managed by the Railway Administration of the Czech Republic, including approximately 1000 occurrences for each year of the evaluated period (2009–2018), and information on 33 projects on the railway transport route, where the effects of their implementation on the overall frequency of occurrences are examined events in the subject location. The output of the research is a methodical approach for assessing the impact of the implementation of projects aimed at increasing the safety and reliability of the railway transport route. We perceive the impact on the occurrences from the point of view of the frequency of their occurrence and from the point of view of the socio-economic impacts that are achieved as a result of the implementation of the projects. From the point of view of the frequency of occurrence, a reduction in its value of 4.63% was found. As part of the research, the impact on the occurrence of extraordinary events is also assessed in the context of the scope of the railway transport route, both with regard to the length of the reconstructed track and also with regard to traffic performance.

Концептуальні засади визначення ефективності виконання завдань і заходів державних цільових програм розвитку для підвищення ефективності управління автомобільними дорогами

Introduction. Effective functioning of road transport is only possible when the quantitative growth, quality level, and technical condition of roads meet the demands of road transport. This combination of road network characteristics can only be achieved with adequate funding to implement all planned works. Investments in road infrastructure can become a catalyst for economic recovery and growth, as they will improve logistics capabilities, reduce freight and passenger transportation costs, and enhance regional competitiveness. Problem Statement. In the first decades of independence, the road industry faced chronic underfunding, which negatively affected its development. The situation worsened with the full-scale military aggression of the Russian Federation in 2024. According to the World Bank's “Rapid Damage and Needs Assessment (RDNA3)” report, post-war recovery needs for public roads and bridges alone are estimated at around USD 28.8 billion. For the rapid and quality restoration and development of Ukraine, this issue is critically important, as the state of the roads affects transportation costs, prices, employment levels, and the overall pace of economic development. Furthermore, the full-scale invasion by the Russian Federation raises questions about ensuring reliable logistics routes, prompt transportation of humanitarian aid, and the country's defense capabilities.

Carbothermal Reduction-Assisted Synthesis of a Carbon-Supported Highly Dispersed PtSn Nanoalloy for the Oxygen Reduction Reaction.

Exploring high-performance and low-platinum-based electrocatalysts to accelerate the oxygen reduction reaction (ORR) at the air cathode of zinc-air batteries remains crucial. Herein, by combining electroless deposition and carbothermal reduction, a nitrogen-doped carbon-supported highly dispersed PtSn alloy nanocatalyst (PtSn/NC) was prepared for a high-efficiency ORR process. Electrochemical measurements show that PtSn/NC exhibits excellent electrocatalytic ORR activity with a half-wave potential of 0.850 V versus reversible hydrogen electrode (RHE), which is higher than that of commercial Pt/C (0.815 V). The PtSn/NC-based (20 μgPt cm-2) rechargeable Zn-air battery exhibited astonishing performance with a maximum power density of up to 150.1 mW cm-2, as well as excellent rate performance and charge/discharge stability. Physical characterization reveals that carbothermal reduction could compel the transformation of Sn oxide into metallic Sn, which then alloys with the deposited Pt atoms to form the PtSn nanoalloy, in which electrons are transferred from Sn atoms to neighboring Pt atoms, thereby improving the ability of Pt-based active sites to catalyze the ORR process in PtSn/NC by optimizing the unoccupied d-band of Pt atoms. This work provides a reliable and innovative route for the rational design of highly dispersed Pt-based alloy ORR electrocatalysts.

Estimation of travel time reduction for ice-breaking ships when considering ice information data

Abstract In light of the recent increase in polar shipping and potential future increase with continued climate change reliable routing in ice-covered waters becomes increasingly important for environmental, economic and safety concerns. Dependable route suggestions have the potential to reduce travel times through polar waters significantly. We apply the Anytime Repairing A* pathfinding algorithm to classified Copernicus Sentinel 1 radar images to estimate how much travel times can be reduced. For multiple example scenarios, it is quantified how much the travel time is reduced if a ship follows these suggestions compared to navigating without any ice information available exterior to the visual range (VR). It was found that having ice information available is most beneficial in complex ice situations, where it can reduce travel time by up to 34% for a VR of 2 km.

A multi-stage game framework for new route promotion: Behavioral strategy and dynamic evolution of shippers, carriers, and governments

New freight routes are being planned and emerging globally, but often rely on government subsidies to enhance their competitiveness during the initial promotional phase. This study proposes a multi-stage game framework to explore the influence mechanism of behavioral strategies among three stakeholders: shipper, carrier, and government. Based on the assessment of shippers’ route choice preferences, we examine the dynamic evolution of carriers’ and governments’ behavioral strategies in the practical context of bounded rationality and dynamic learning. We theoretically derive the evolutionary paths and stable outcomes of dynamic systems across eight scenarios encompassing all the possible practical values to be taken, which provide broader and more valuable decision support for new route promotion. Finally, the feasibility and validity of the proposed model are verified by the actual case of the New International Land-Sea Trade Corridor. The findings indicate that government subsidies are not always effective and provide a precise subsidy range that can incentivize carriers to switch to the new route. Moreover, the study clarifies the impact of key factors such as subsidy, tax, route reliability, transportation time, and time value of cargo on the promotion of new routes through numerical simulation, and provides feasible management recommendations for government and route operations.

A Reliable Multipath Intercluster Routing Protocol Based on Link Stability

A Reliable Multipath Intercluster Routing Protocol Based on Link Stability

Metal oxide particle electrodes for degradation of high concentration phenol wastewater via electrocatalytic advanced oxidation

High-concentration phenol wastewater is pollutant of concern that pose significant risks to human health and the environment. Three-dimensional electrocatalytic oxidation is one of the most promising wastewater treatment technologies because of its high treatment efficiency, low energy consumption and low secondary pollution. Lower-cost and higher-performance particles still faces great challenges. In this work, metal oxide particle electrodes were prepared using granular activated carbon (GAC) as a substrate to study the degradation of phenol by three-dimensional electrocatalytic oxidation. GAC particle electrodes loaded with different monometallic oxides (Mn, Fe, Co, Ce) and bimetallic oxides (Fe and Ce) were prepared by the impregnation method. The effectiveness of the particle electrodes in degrading phenol was greatly improved after active components loading. Among all monometallic oxide particle electrodes, the concentration degradation efficiency was in the order of Ce/GAC > Co/GAC >Mn/GAC > Fe/GAC, and the COD degradation efficiency was Ce/GAC > Fe/GAC > Co/GAC >Mn/GAC. After optimizing the loading metal type and loading amount, it was found that the 1.1% Fe-2.7% Ce/GAC particle electrode perform the best, with a phenol degradation efficiency of 95.48%, a COD degradation rate of 94.35%, an energy consumption of 0.75 kWh/kg COD. This lower-cost and higher-performance particle highlights a reliable route for solving the problem of particle electrode materials limiting the efficient treatment of phenol-containing wastewater.

SROR: A Secure and Reliable Opportunistic Routing for VANETs

In Vehicular Ad Hoc Networks (VANETs), high mobility of vehicles issues a huge challenge to the reliability and security of transmitting packets. Therefore, a Secure and Reliable Opportunistic Routing (SROR) is proposed in this paper. During construction of Candidate Forwarding Nodes (CFNs) set, the relative velocity, connectivity probability, and packet forwarding ratio are taken into consideration. The aim of SROR is to maximally improve the packet delivery ratio as well as reduce the end-to-end delay. The selection of a relay node from CFNs is formalized as a Markov Decision Process (MDP) optimization. The SROR algorithm extracts useful knowledge from historical behavior of nodes by interacting with the environment. This useful knowledge are utilized to select the relay node as well as to prevent the malicious nodes from forwarding packets. In addition, the influence of different learning rate and exploratory factor policy on rewards of agents are analyzed. The experimental results show that the performance of SROR outperforms the benchmarks in terms of the packet delivery ratio, end-to-end delay, and attack success ratio. As vehicle density ranges from 10 to 50 and percentage of malicious vehicles is fixed at 10%, the average of packet delivery ratio, end-to-end delay, and attack success ratio are 0.82, 0.26s, and 0.37, respectively, outperforming benchmark protocols.

ENIAO: Energy Aware Faulty Node Re-Placement Integrated With Duty Cycling and Improved Harmony Search Based Clustering through Adaptive Fish School Search Routing for WSN Optimization

In wireless sensor networks (WSNs), sensor nodes are constrained by resource constraints. The limited energy supply and susceptibility to failure greatly affect WSN lifespan, hindering long-term deployment. ENIAO is an Integrated cross-layer Optimized Routing Approach for WSNs that is fault-tolerant and energy-efficient. A bio-inspired clustering architecture and adaptive duty cycling are incorporated into ENIAO's routing optimization. In a clustering protocol, the network is partitioned, and paths are dynamically optimized within and between clusters. By optimizing active/sleep schedules, duty cycling optimizes energy efficiency. A variety of network conditions have been simulated to assess ENIAO's performance. Regarding fault tolerance and energy consumption, ENIAO significantly prolongs the network lifetime. As compared to benchmark protocols, it achieves higher throughput. As a result of the cross-layer design, ENIAO is automatically adapted to optimize energy usage and routing reliability. In the long run, large-scale IoT deployments are possible with ENIAO due to the integrated approach.

Solving the Robust Shortest Path Problem with Multimodal Transportation

This paper explores the challenges of finding robust shortest paths in multimodal transportation networks. With the increasing complexity and uncertainties in modern transportation systems, developing efficient and reliable routing strategies that can adapt to various disruptions and modal changes is essential. By incorporating practical constraints in parameter uncertainty, this paper establishes a robust shortest path mixed-integer programming model based on a multimodal transportation network under transportation time uncertainty. To solve robust shortest path problems with multimodal transportation, we propose a modified Dijkstra algorithm that integrates parameter uncertainty with multimodal transportation. The effectiveness of the proposed multimodal transportation shortest path algorithm is verified using empirical experiments on test sets of different scales and a comparison of the runtime using a commercial solver. The experimental results on the multimodal transportation networks demonstrate the effectiveness of our approach in providing robust and efficient routing solutions. The results demonstrate that the proposed method can generate optimal solutions to the robust shortest path problem in multimodal transportation under time uncertainty and has practical significance.