The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicl...The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.展开更多
To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and en...To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and environmental issues of ships,this study aims to improve the transportation efficiency of ships by providing a ship route induction method.Ship data from a certain bay during a defined period are collected,and an improved backpropagation neural network algorithm is used to forecast ship traffic.On the basis of the forecasted data and ship route induction objectives,dynamic programming of ship routes is performed.Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55%compared with statically induced routes.This method has promising engineering applications in improving ship navigation efficiency,promoting energy conservation,and reducing emissions.展开更多
DDeeaarr EEddiittoorr,,The encoding and retrieval of emotional memories demands intricate interplay within the limbic network,where the network state is subject to significant reconfiguration by learning-induced plast...DDeeaarr EEddiittoorr,,The encoding and retrieval of emotional memories demands intricate interplay within the limbic network,where the network state is subject to significant reconfiguration by learning-induced plasticity,behavioral state,and contextual information[1].展开更多
Reliable and efficient communication is essential for Unmanned Aerial Vehicle(UAV)networks,especially in dynamic and resource-constrained environments such as disaster management,surveillance,and environmental monitor...Reliable and efficient communication is essential for Unmanned Aerial Vehicle(UAV)networks,especially in dynamic and resource-constrained environments such as disaster management,surveillance,and environmental monitoring.Frequent topology changes,high mobility,and limited energy availability pose significant challenges to maintaining stable and high-performance routing.Traditional routing protocols,such as Ad hoc On-Demand Distance Vector(AODV),Load-Balanced Optimized Predictive Ad hoc Routing(LB-OPAR),and Destination-Sequenced Distance Vector(DSDV),often experience performance degradation under such conditions.To address these limitations,this study evaluates the effectiveness of Dynamic Adaptive Routing(DAR),a protocol designed to adapt routing decisions in real time based on network dynamics and resource constraints.The research utilizes the Network Simulator 3(NS-3)platform to conduct controlled simulations,measuring key performance indicators such as latency,Packet Delivery Ratio(PDR),energy consumption,and throughput.Comparative analysis reveals that DAR consistently outperforms conventional protocols,achieving a 20%-30% reduction in latency,a 25% decrease in energy consumption,and marked improvements in throughput and PDR.These results highlight DAR’s ability to maintain high communication reliability while optimizing resource usage in challenging operational scenarios.By providing empirical evidence of DAR’s advantages in highly dynamic UAV network environments,this study contributes to advancing adaptive routing strategies.The findings not only validate DAR’s robustness and scalability but also lay the groundwork for integrating artificial intelligence-driven decision-making and real-world UAV deployment.Future work will explore cross-layer optimization,multi-UAV coordination,and experimental validation in field trials,aiming to further enhance communication resilience and energy efficiency in next-generation aerial networks.展开更多
Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of d...Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.展开更多
With the rapid development of air transportation, network service ability has attracted a lot of attention in academe. Aiming to improve the throughput of the air route network （ARN）, we propose an effective local d...With the rapid development of air transportation, network service ability has attracted a lot of attention in academe. Aiming to improve the throughput of the air route network （ARN）, we propose an effective local dynamic routing strategy in this paper. Several factors, such as the rout- ing distance, the geographical distance and the real-time local traffic, are taken into consideration. When the ARN is in the normal free-flow state, the proposed strategy can recover the shortest path routing （SPR） strategy. When the ARN undergoes congestion, the proposed strategy changes the paths of flights based on the real-time local traffic information. The throughput of the Chinese air route network （CARN） is evaluated. Results confirm that the proposed strategy can significantly improve the throughput of CARN. Meanwhile, the increase in the average flying distance and time is tiny. Results also indicate the importance of the distance related factors in a routing strategy designed for the ARN.展开更多
The integration of the dynamic adaptive routing(DAR)algorithm in unmanned aerial vehicle(UAV)networks offers a significant advancement in addressing the challenges posed by next-generation communication systems like 6...The integration of the dynamic adaptive routing(DAR)algorithm in unmanned aerial vehicle(UAV)networks offers a significant advancement in addressing the challenges posed by next-generation communication systems like 6G.DAR’s innovative framework incorporates real-time path adjustments,energy-aware routing,and predictive models,optimizing reliability,latency,and energy efficiency in UAV operations.This study demonstrated DAR’s superior performance in dynamic,large-scale environments,proving its adaptability and scalability for real-time applications.As 6G networks evolve,challenges such as bandwidth demands,global spectrum management,security vulnerabilities,and financial feasibility become prominent.DAR aligns with these demands by offering robust solutions that enhance data transmission while ensuring network reliability.However,obstacles like global route optimization and signal interference in urban areas necessitate further refinement.Future directions should explore hybrid approaches,the integration of machine learning,and comprehensive real-world testing to maximize DAR’s capabilities.The findings underscore DAR’s pivotal role in enabling efficient and sustainable UAV communication systems,contributing to the broader landscape of wireless technology and laying a foundation for the seamless transition to 6G networks.展开更多
Malaria is a severe epidemic disease caused by Plasmodium falciparum.The parasite causes critical illness if persisted for longer durations and delay in precise treatment can lead to further complications.The automati...Malaria is a severe epidemic disease caused by Plasmodium falciparum.The parasite causes critical illness if persisted for longer durations and delay in precise treatment can lead to further complications.The automatic diagnostic model provides aid for medical practitioners to avail a fast and efficient diagnosis.Most of the existing work either utilizes a fully connected convolution neural network with successive pooling layers which causes loss of information in pixels.Further,convolutions can capture spatial invariances but,cannot capture rotational invariances.Hence to overcome these limitations,this research,develops an Imperative Dynamic routing mechanism with fully trained capsule networks for malaria classification.This model identifies the presence of malaria parasites by classifying thin blood smears containing samples of parasitized and healthy erythrocytes.The proposed model is compared and evaluated with novel machine vision models evolved over a decade such as VGG,ResNet,DenseNet,MobileNet.The problems in previous research are cautiously addressed and overhauled using the proposed capsule network by attaining the highest Area under the curve(AUC)and Specificity of 99.03%and 99.43%respectively for 20%test samples.To understand the underlying behavior of the proposed network various tests are conducted for variant shuffle patterns.The model is analyzed and assessed in distinct environments to depict its resilience and versatility.To provide greater generalization,the proposed network has been tested on thick blood smear images which surpassed with greater performance.展开更多
The challenge of keeping and getting new customers drives the development of new practices to meet the consumption needs of increasingly tends to micro-segmentation of product and consumer market. The new consumption ...The challenge of keeping and getting new customers drives the development of new practices to meet the consumption needs of increasingly tends to micro-segmentation of product and consumer market. The new consumption habits of brazilians brought new prospects for market. The objective of this paper is to develop of a dynamic vehicle routing system supported by the behavior of urban traffic in the city ofSao Paulo using Neuro Fuzzy Network. The methodology of this paper consists in the capture of relevant events that interfere with the flow of traffic of the city of Sao Paulo and implementation of a Fuzzy Neural Network trained with these events in order to foresee the traffic behavior. The system offers three labels of hierarchical routing, thus is possible to consider not only the basic factors of routing, but too external factors that directly influence on the flow of traffic and the disruption which may be avoided in large cities, through alternative routes （dynamic vehicle routing）. Predicting the behavior of traffic represents the strategic level routing, dynamic vehicle routing is the tactical level, and routing algorithms to the operational level. This paper will not be discussed the operational level.展开更多
The purpose of this research is to create a simulated environment for teaching algorithms,big data processing,and machine learning.The environment is similar to Google Maps,with the capacity of finding the fastest pat...The purpose of this research is to create a simulated environment for teaching algorithms,big data processing,and machine learning.The environment is similar to Google Maps,with the capacity of finding the fastest path between two points in dynamic traffic situations.However,the system is significantly simplified for educational purposes.Students can choose different traffic patterns and program a car to navigate through the traffic dynamically based on the changing traffic.The environments used in the project are Visual IoT/Robotics Programming Language Environment(VIPLE)and a traffic simulator developed in the Unity game engine.This paper focuses on creating realistic traffic data for the traffic simulator and implementing dynamic routing algorithms in VIPLE.The traffic data are generated from the recorded real traffic data published on the Arizona Maricopa County website.Based on the generated traffic data,VIPLE programs are developed to implement the traffic simulation with support for dynamic changing data.展开更多
In the current era,anyone can freely access the Internet thanks to the development of information and communication technology.The cloud is attracting attention due to its ability to meet continuous user demands for r...In the current era,anyone can freely access the Internet thanks to the development of information and communication technology.The cloud is attracting attention due to its ability to meet continuous user demands for resources.Additionally,Cloud is effective for systems with large data flow such as the Internet of Things(IoT)systems and Smart Cities.Nonetheless,the use of traditional networking technology in the cloud causes network traffic overload and network security problems.Therefore,the cloud requires efficient networking technology to solve the existing challenges.In this paper,we propose one-time password-based software-defined cloud architecture for secure dynamic routing to mitigating the above-mention issues.The proposed cloud architecture provides a secure data path through dynamic routing using One-Time Internet Protocol(OTIP)algorithm between each layer.On the network side,we use software-defined technology to provide efficient network management and data security.We introduce a software-defined cloud architecture that applies OTIP algorithms for secure dynamic routing.We conduct a comparative analysis between general IP communication and proposed OTIP communication architecture.It evaluates the performance of OTIP algorithms.Finally,we examine the proposed software-defined cloud architecture,including how to apply OTIP in secure dynamic routing according to the results of the comparative analysis.展开更多
Time and space complexity is themost critical problemof the current routing optimization algorithms for Software Defined Networking(SDN).To overcome this complexity,researchers use meta-heuristic techniques inside the...Time and space complexity is themost critical problemof the current routing optimization algorithms for Software Defined Networking(SDN).To overcome this complexity,researchers use meta-heuristic techniques inside the routing optimization algorithms in the OpenFlow(OF)based large scale SDNs.This paper proposes a hybrid meta-heuristic algorithm to optimize the dynamic routing problem for the large scale SDNs.Due to the dynamic nature of SDNs,the proposed algorithm uses amutation operator to overcome the memory-based problem of the ant colony algorithm.Besides,it uses the box-covering method and the k-means clustering method to divide the SDN network to overcome the problemof time and space complexity.The results of the proposed algorithm compared with the results of other similar algorithms and it shows that the proposed algorithm can handle the dynamic network changing,reduce the network congestion,the delay and running times and the packet loss rates.展开更多
Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equation...Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equations(HEDWE) for watershed rainfall-runoff routing, in which the full momentum equation is written as a quadratic equation with only one unknown variable Q, water depth is derived from the continuity equation using the two-step predictorcorrector method, and the discrete scheme is the explicit upwind scheme. The results of numerical tests showed the HEDWE approach has several major advantages. 1) It is a stable numerical method, even for an initially dry area. 2) Its computational efficiency is higher than 4.76E+05 times/s. 3) It can be used for overland flow, river flow, and combinations thereof. The primary disadvantages of the HEDWE approach are its unsuitability for rapidly varying flow, such as dam-break floods.展开更多
In order to overcome the adverse effects of Doppler wavelength shift on data transmission in the optical satellite networks,a dynamic routing and wavelength assignment algorithm based on crosslayer design( CL-DRWA) is...In order to overcome the adverse effects of Doppler wavelength shift on data transmission in the optical satellite networks,a dynamic routing and wavelength assignment algorithm based on crosslayer design( CL-DRWA) is introduced which can improve robustness of the network. Above all,a cross-layer optimization model is designed,which considers transmission delay and wavelength-continuity constraint,as well as Doppler wavelength shift. Then CL-DRWA is applied to solve this model,resulting in finding an optimal light path satisfying the above constraints for every connection request. In CL-DRWA,Bellman-Ford method is used to find an optimal route and a distributed relative capacity loss method is implemented to get an optimal wavelength assignment result on the optimal route. Moreover,compared with the dynamic routing and wavelength assignment algorithm based on minimum delay strategy( MD-DRWA),CL-DRWA can make an improvement of 5. 3% on the communication success probability. Meanwhile,CL-DRWA can meet the requirement of transmission delay for real-time services.展开更多
The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network.DT-DVTR in the snapshot-based connectionoriented routing strategy is one o...The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network.DT-DVTR in the snapshot-based connectionoriented routing strategy is one of the representative solutions,but it still has room for improvement in terms of routing stability.In this paper,we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules(MTCR-CR).The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL)construction solutions that meet the minimum number of topology changes to avoid route oscillations.The simulation results in Beidou-3 show that compared with DT-DVTR,MTCR-CR reduces the number of routing changes by about 92%,the number of path changes caused by routing changes is about38%,and the rerouting time is reduced by approximately 47%.At the same time,in order to show our algorithm more comprehensively,the same experimental index test was also carried out on the Globalstar satellite constellation.展开更多
In this paper,we study atomic dynamic routing games with multiple destinations.We first show that if the first-in–first-out(FIFO)principle is always fulfilled locally to regulate the congestion,then most probably we ...In this paper,we study atomic dynamic routing games with multiple destinations.We first show that if the first-in–first-out(FIFO)principle is always fulfilled locally to regulate the congestion,then most probably we cannot guarantee the existence of any reasonable approximate Nash equilibrium.By partly discarding the FIFO principle and introducing destination priorities in the regulation rules,we propose a new atomic routing model.In each such game,we prove that a pure strategy Nash equilibrium always exists and can be computed in polynomial time.In addition,the multicommodity routing game can be iteratively decomposed into a series of well-behaved single-destination routing games,which will provide a good characterization of all NEs of the original game.展开更多
Automatically extracting Drug-Drug Interactions (DDIs) from text is a crucial and challenging task, particularly when multiple medications are taken concurrently. In this study, we propose a novel approach, called Enh...Automatically extracting Drug-Drug Interactions (DDIs) from text is a crucial and challenging task, particularly when multiple medications are taken concurrently. In this study, we propose a novel approach, called Enhanced Attention-driven Dynamic Graph Convolutional Network (E-ADGCN), for DDI extraction. Our model combines the Attention-driven Dynamic Graph Convolutional Network (ADGCN) with a feature fusion method and multi-task learning framework. The ADGCN effectively utilizes entity information and dependency tree information from biomedical texts to extract DDIs. The feature fusion method integrates User-Generated Content (UGC) and molecular information with drug entity information from text through dynamic routing. By leveraging external resources, our approach maximizes the auxiliary effect and improves the accuracy of DDI extraction. We evaluate the E-ADGCN model on the extended DDIExtraction2013 dataset and achieve an F1-score of 81.45%. This research contributes to the advancement of automated methods for extracting valuable drug interaction information from textual sources, facilitating improved medication management and patient safety.展开更多
This study focuses on the application of dynamic route planning and augmented reality(AR)technology within interactive theme trail platforms.Taking the“Dongpo Travelogue”digital guide mini-program as a case study,it...This study focuses on the application of dynamic route planning and augmented reality(AR)technology within interactive theme trail platforms.Taking the“Dongpo Travelogue”digital guide mini-program as a case study,it employs empirical analysis to explore its impact on enhancing visitor engagement and cultural identification.Employing a combined quantitative and qualitative methodology,the study analyses the platform’s functional implementation in route planning,cultural narration,interactive games,and their impact on visitor experience.Findings indicate that the integration of dynamic route planning and AR technology significantly enhances visitor engagement and cultural identity,offering novel insights for the digital transformation of the cultural tourism industry.展开更多
Wireless Networked Control Systems (WNCS) are used to implement a control mechanism over a wireless network that is capable of carrying real-time traffic. This field has drawn enormous attention from current researche...Wireless Networked Control Systems (WNCS) are used to implement a control mechanism over a wireless network that is capable of carrying real-time traffic. This field has drawn enormous attention from current researchers because of its flexibility and robustness. However, designing efficient WNCS over Mobile Ad Hoc Networks (MANET) is still a challenging topic because of its less-predictable aspects, such as inconsistent delay, packet drop probability, and dynamic topology. This paper presents design guidelines for WNCS over MANET using the Network Simulator version 2, NS2 software. It investigates the impact of packet delay and packet drop under the AODV and DSR routing protocols. The simulation results have been compared to MATLAB results for validation. Keywords Adhoc On-Demand Distance Vector (AODV) routing - Dynamic Source routing (DSR) - Mobile Adhoc Networks (MANET) - Wireless Networked Control Systems (WNCS) Mohammad Shahidul Hasan received his BSc and first MSc in Computer Science from the University of Dhaka, Bangladesh. He obtained his 2nd MSc in Computer & Network Engineering from Sheffield Hallam University, Sheffield, UK. Currently he is pursuing his PhD under the Faculty of Computing, Engineering and Technology, Staffordshire University, Stafford, UK in Networked Control Systems over MANET.Chris Harding received his BSc in Computing Science and Masters by Research from Staffordshire University, UK. Currently he is pursuing his PhD in Wireless Networked Control Systems, specifically looking at NCS over MANETs, with research interests in this area concentrating on the network routing and effect of routing protocols on the NCS system.Hongnian Yu is Professor of Computer Science at Staffordshire University. He was a lecturer in Control and Systems Engineering at Yanshan University, China in 1985–1990, did his PhD in Robotics at King’s College London (1990–1994), was a research fellow in Manufacturing Systems at Sussex University (1994–1996), a lecturer in Artificial Intelligence at Liver-pool John Moore’s University (1996–1999), a lecturer in Control and Systems Engineering at the University of Exeter (1999–2002), and a Senior Lecturer in Computing at the University of Bradford (2002–2004). He now leads the Mobile Computing and Distributed Systems Research Group at Staffordshire University. He was a founding member of the Modeling Optimisation Scheduling and Intelligent Control research group at the University of Bradford. He has extensive research experience in neural networks, mobile computing, modeling, control of robot manipulators, and modeling, scheduling, planning, and simulations of large discrete event dynamic systems with applications to manufacturing systems, supply chains, transportation networks, and computer networks. He has published over 100 research papers focusing on the following: neural networks, computer networks, adaptive and robust control of robot manipulators, analysis and control of hybrid machines, control of timed delay systems, predictive control, manufacturing system modeling and scheduling, planning, and supply chains. He has held several research grants from EPSRC, the Royal Society, and the EU, as well as from industry. He was awarded the F.C. William Premium for his paper on adaptive and robust control of robot manipulators by the IEE Council in 1997. Professor Yu is an EPSRC college member, a member of IEEE, and a committee member of several conferences and journal editorial boards.Alison Griffiths has been a Senior Lecturer in Telecommunications at Staffordshire University since 2003. She was a lecturer in Computing at Staffordshire University in 2002–2003. She was a Research Associate on an EPSRC funded project whilst doing her PhD on the convergence of Mobile Computing and Telecommunications at Staffordshire University (1999–2003). The investigation consisted of the communication of different types of media (voice, video conferencing, web browsing, and downloading) over a common network, using a mobile device. Problems considered were the complications that occurred when a user moves, and consequently changes their end-point in the network during communication, with respect to the type of service the user is provided with (delays and losses). She obtained both her MEng and 1st Class BEng (Hons) from Staffordshire University in 1999 and 1998 respectively. She is now part of the Mobile Computing and Distributed Systems Research Group at Staffordshire University. She has published 8 research papers focusing on quality of service and access between cellular and IP packet switched networks. Future directions include mobile agents and control of mobile wireless ad-hoc networks. Her current research interests have extended to Wireless Networked Control Systems, specifically looking at NCS over MANETs, with research interests in this area concentrating on the network routing and effect of routing protocols on the NCS system.展开更多
Network security and energy consumption are deemed to be two important components of wireless and mobile ad hoc networks(WMANets).There are various routing attacks which harm Ad Hoc networks.This is because of the uns...Network security and energy consumption are deemed to be two important components of wireless and mobile ad hoc networks(WMANets).There are various routing attacks which harm Ad Hoc networks.This is because of the unsecure wireless communication,resource constrained capabilities and dynamic topology.In order to cope with these issues,Ad Hoc On-Demand Distance Vector(AODV)routing protocol can be used to remain the normal networks functionality and to adjust data transmission by defending the networks against black hole attacks.The proposed system,in this work,identifies the optimal route from sender to collector,prioritizing the number of jumps,the battery life,and security,which are fundamental prerequisites.Researches have proposed various plans for detecting the shortest route,as well as ensuring energy conversions and defense against threats and attacks.In this regard,the packet drop attack is one of the most destructive attack against WMANet communication and hence merits special attention.This type of attack may allow the attacker to take control of the attacked hubs,which may lost packets or transmitted information via a wrong route during the packets journey from a source hub to a target one.Hence,a new routing protocol method has been proposed in this study.It applies the concept of energy saving systems to conserve energy that is not required by the system.The proposed method for energy aware detection and prevention of packet drop attacks in mobile ad hoc networks is termed the Ad Hoc On-Demand and Distance Vector–Packet Drop Battling Mechanism(AODV–PDBM).展开更多
基金funded by the National Key Research and Development Program Project 2022YFB4300404.
文摘The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.
基金Supported by the National Key R&D Program of China project (2017YFC0805309)the National Natural Science Foundation of China (60602020)。
文摘To improve the efficiency of ship traffic in frequently traded sea areas and respond to the national“dual-carbon”strategy,a multi-objective ship route induction model is proposed.Considering the energy-saving and environmental issues of ships,this study aims to improve the transportation efficiency of ships by providing a ship route induction method.Ship data from a certain bay during a defined period are collected,and an improved backpropagation neural network algorithm is used to forecast ship traffic.On the basis of the forecasted data and ship route induction objectives,dynamic programming of ship routes is performed.Experimental results show that the routes planned using this induction method reduce the combined cost by 17.55%compared with statically induced routes.This method has promising engineering applications in improving ship navigation efficiency,promoting energy conservation,and reducing emissions.
基金supported by the National Natural Science Foundation of China(T2394531)the National Key R&D Program of China(2024YFF1206500)+1 种基金the Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)ZJ Lab,and the Shanghai Center for Brain Science and Brain-Inspired Technology,China.
文摘DDeeaarr EEddiittoorr,,The encoding and retrieval of emotional memories demands intricate interplay within the limbic network,where the network state is subject to significant reconfiguration by learning-induced plasticity,behavioral state,and contextual information[1].
文摘Reliable and efficient communication is essential for Unmanned Aerial Vehicle(UAV)networks,especially in dynamic and resource-constrained environments such as disaster management,surveillance,and environmental monitoring.Frequent topology changes,high mobility,and limited energy availability pose significant challenges to maintaining stable and high-performance routing.Traditional routing protocols,such as Ad hoc On-Demand Distance Vector(AODV),Load-Balanced Optimized Predictive Ad hoc Routing(LB-OPAR),and Destination-Sequenced Distance Vector(DSDV),often experience performance degradation under such conditions.To address these limitations,this study evaluates the effectiveness of Dynamic Adaptive Routing(DAR),a protocol designed to adapt routing decisions in real time based on network dynamics and resource constraints.The research utilizes the Network Simulator 3(NS-3)platform to conduct controlled simulations,measuring key performance indicators such as latency,Packet Delivery Ratio(PDR),energy consumption,and throughput.Comparative analysis reveals that DAR consistently outperforms conventional protocols,achieving a 20%-30% reduction in latency,a 25% decrease in energy consumption,and marked improvements in throughput and PDR.These results highlight DAR’s ability to maintain high communication reliability while optimizing resource usage in challenging operational scenarios.By providing empirical evidence of DAR’s advantages in highly dynamic UAV network environments,this study contributes to advancing adaptive routing strategies.The findings not only validate DAR’s robustness and scalability but also lay the groundwork for integrating artificial intelligence-driven decision-making and real-world UAV deployment.Future work will explore cross-layer optimization,multi-UAV coordination,and experimental validation in field trials,aiming to further enhance communication resilience and energy efficiency in next-generation aerial networks.
文摘Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.
基金supported by the National Basic Research Program of China(No.2011CB707000)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.61221061)
文摘With the rapid development of air transportation, network service ability has attracted a lot of attention in academe. Aiming to improve the throughput of the air route network （ARN）, we propose an effective local dynamic routing strategy in this paper. Several factors, such as the rout- ing distance, the geographical distance and the real-time local traffic, are taken into consideration. When the ARN is in the normal free-flow state, the proposed strategy can recover the shortest path routing （SPR） strategy. When the ARN undergoes congestion, the proposed strategy changes the paths of flights based on the real-time local traffic information. The throughput of the Chinese air route network （CARN） is evaluated. Results confirm that the proposed strategy can significantly improve the throughput of CARN. Meanwhile, the increase in the average flying distance and time is tiny. Results also indicate the importance of the distance related factors in a routing strategy designed for the ARN.
文摘The integration of the dynamic adaptive routing(DAR)algorithm in unmanned aerial vehicle(UAV)networks offers a significant advancement in addressing the challenges posed by next-generation communication systems like 6G.DAR’s innovative framework incorporates real-time path adjustments,energy-aware routing,and predictive models,optimizing reliability,latency,and energy efficiency in UAV operations.This study demonstrated DAR’s superior performance in dynamic,large-scale environments,proving its adaptability and scalability for real-time applications.As 6G networks evolve,challenges such as bandwidth demands,global spectrum management,security vulnerabilities,and financial feasibility become prominent.DAR aligns with these demands by offering robust solutions that enhance data transmission while ensuring network reliability.However,obstacles like global route optimization and signal interference in urban areas necessitate further refinement.Future directions should explore hybrid approaches,the integration of machine learning,and comprehensive real-world testing to maximize DAR’s capabilities.The findings underscore DAR’s pivotal role in enabling efficient and sustainable UAV communication systems,contributing to the broader landscape of wireless technology and laying a foundation for the seamless transition to 6G networks.
基金supported by the Jawaharlal Nehru Technological University Hyderabad,India under Grant Procs No.JNTUH/TEQIP-III/CRS/2019/CSE/13.the financial support provided by the J.N.T.University Hyderabad,India.
文摘Malaria is a severe epidemic disease caused by Plasmodium falciparum.The parasite causes critical illness if persisted for longer durations and delay in precise treatment can lead to further complications.The automatic diagnostic model provides aid for medical practitioners to avail a fast and efficient diagnosis.Most of the existing work either utilizes a fully connected convolution neural network with successive pooling layers which causes loss of information in pixels.Further,convolutions can capture spatial invariances but,cannot capture rotational invariances.Hence to overcome these limitations,this research,develops an Imperative Dynamic routing mechanism with fully trained capsule networks for malaria classification.This model identifies the presence of malaria parasites by classifying thin blood smears containing samples of parasitized and healthy erythrocytes.The proposed model is compared and evaluated with novel machine vision models evolved over a decade such as VGG,ResNet,DenseNet,MobileNet.The problems in previous research are cautiously addressed and overhauled using the proposed capsule network by attaining the highest Area under the curve(AUC)and Specificity of 99.03%and 99.43%respectively for 20%test samples.To understand the underlying behavior of the proposed network various tests are conducted for variant shuffle patterns.The model is analyzed and assessed in distinct environments to depict its resilience and versatility.To provide greater generalization,the proposed network has been tested on thick blood smear images which surpassed with greater performance.
文摘The challenge of keeping and getting new customers drives the development of new practices to meet the consumption needs of increasingly tends to micro-segmentation of product and consumer market. The new consumption habits of brazilians brought new prospects for market. The objective of this paper is to develop of a dynamic vehicle routing system supported by the behavior of urban traffic in the city ofSao Paulo using Neuro Fuzzy Network. The methodology of this paper consists in the capture of relevant events that interfere with the flow of traffic of the city of Sao Paulo and implementation of a Fuzzy Neural Network trained with these events in order to foresee the traffic behavior. The system offers three labels of hierarchical routing, thus is possible to consider not only the basic factors of routing, but too external factors that directly influence on the flow of traffic and the disruption which may be avoided in large cities, through alternative routes （dynamic vehicle routing）. Predicting the behavior of traffic represents the strategic level routing, dynamic vehicle routing is the tactical level, and routing algorithms to the operational level. This paper will not be discussed the operational level.
文摘The purpose of this research is to create a simulated environment for teaching algorithms,big data processing,and machine learning.The environment is similar to Google Maps,with the capacity of finding the fastest path between two points in dynamic traffic situations.However,the system is significantly simplified for educational purposes.Students can choose different traffic patterns and program a car to navigate through the traffic dynamically based on the changing traffic.The environments used in the project are Visual IoT/Robotics Programming Language Environment(VIPLE)and a traffic simulator developed in the Unity game engine.This paper focuses on creating realistic traffic data for the traffic simulator and implementing dynamic routing algorithms in VIPLE.The traffic data are generated from the recorded real traffic data published on the Arizona Maricopa County website.Based on the generated traffic data,VIPLE programs are developed to implement the traffic simulation with support for dynamic changing data.
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(NRF-2019R1A2B5B01070416)also supported by the Advanced Research Project funded by the SeoulTech(Seoul National University of Science and Technology).
文摘In the current era,anyone can freely access the Internet thanks to the development of information and communication technology.The cloud is attracting attention due to its ability to meet continuous user demands for resources.Additionally,Cloud is effective for systems with large data flow such as the Internet of Things(IoT)systems and Smart Cities.Nonetheless,the use of traditional networking technology in the cloud causes network traffic overload and network security problems.Therefore,the cloud requires efficient networking technology to solve the existing challenges.In this paper,we propose one-time password-based software-defined cloud architecture for secure dynamic routing to mitigating the above-mention issues.The proposed cloud architecture provides a secure data path through dynamic routing using One-Time Internet Protocol(OTIP)algorithm between each layer.On the network side,we use software-defined technology to provide efficient network management and data security.We introduce a software-defined cloud architecture that applies OTIP algorithms for secure dynamic routing.We conduct a comparative analysis between general IP communication and proposed OTIP communication architecture.It evaluates the performance of OTIP algorithms.Finally,we examine the proposed software-defined cloud architecture,including how to apply OTIP in secure dynamic routing according to the results of the comparative analysis.
文摘Time and space complexity is themost critical problemof the current routing optimization algorithms for Software Defined Networking(SDN).To overcome this complexity,researchers use meta-heuristic techniques inside the routing optimization algorithms in the OpenFlow(OF)based large scale SDNs.This paper proposes a hybrid meta-heuristic algorithm to optimize the dynamic routing problem for the large scale SDNs.Due to the dynamic nature of SDNs,the proposed algorithm uses amutation operator to overcome the memory-based problem of the ant colony algorithm.Besides,it uses the box-covering method and the k-means clustering method to divide the SDN network to overcome the problemof time and space complexity.The results of the proposed algorithm compared with the results of other similar algorithms and it shows that the proposed algorithm can handle the dynamic network changing,reduce the network congestion,the delay and running times and the packet loss rates.
基金funded by the National Natural Science Foundation of China (Grant No. 41501046)the Innovation Program of Guangdong Province, China (Grant No. 2016-14)
文摘Efficiency in solving the Saint-Venant equations for watershed rainfall-runoff routing is important in flood hydrology. This paper presents a high-efficiency numerical solution of one-dimensional dynamic wave equations(HEDWE) for watershed rainfall-runoff routing, in which the full momentum equation is written as a quadratic equation with only one unknown variable Q, water depth is derived from the continuity equation using the two-step predictorcorrector method, and the discrete scheme is the explicit upwind scheme. The results of numerical tests showed the HEDWE approach has several major advantages. 1) It is a stable numerical method, even for an initially dry area. 2) Its computational efficiency is higher than 4.76E+05 times/s. 3) It can be used for overland flow, river flow, and combinations thereof. The primary disadvantages of the HEDWE approach are its unsuitability for rapidly varying flow, such as dam-break floods.
基金Supported by the National Natural Science Foundation of China(No.61675033,61575026,61675232,61571440)the National High Technology Research and Development Program of China(No.2015AA015504)
文摘In order to overcome the adverse effects of Doppler wavelength shift on data transmission in the optical satellite networks,a dynamic routing and wavelength assignment algorithm based on crosslayer design( CL-DRWA) is introduced which can improve robustness of the network. Above all,a cross-layer optimization model is designed,which considers transmission delay and wavelength-continuity constraint,as well as Doppler wavelength shift. Then CL-DRWA is applied to solve this model,resulting in finding an optimal light path satisfying the above constraints for every connection request. In CL-DRWA,Bellman-Ford method is used to find an optimal route and a distributed relative capacity loss method is implemented to get an optimal wavelength assignment result on the optimal route. Moreover,compared with the dynamic routing and wavelength assignment algorithm based on minimum delay strategy( MD-DRWA),CL-DRWA can make an improvement of 5. 3% on the communication success probability. Meanwhile,CL-DRWA can meet the requirement of transmission delay for real-time services.
基金supported by the National Key Research and Development Program of China(No.2020YFB1806000)。
文摘The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network.DT-DVTR in the snapshot-based connectionoriented routing strategy is one of the representative solutions,but it still has room for improvement in terms of routing stability.In this paper,we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules(MTCR-CR).The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL)construction solutions that meet the minimum number of topology changes to avoid route oscillations.The simulation results in Beidou-3 show that compared with DT-DVTR,MTCR-CR reduces the number of routing changes by about 92%,the number of path changes caused by routing changes is about38%,and the rerouting time is reduced by approximately 47%.At the same time,in order to show our algorithm more comprehensively,the same experimental index test was also carried out on the Globalstar satellite constellation.
基金supported partly by National Key R&D Program of China(Nos.2021YFA1000300 and 2021YFA1000301)the National Natural Science Foundation of China(No.11971046).
文摘In this paper,we study atomic dynamic routing games with multiple destinations.We first show that if the first-in–first-out(FIFO)principle is always fulfilled locally to regulate the congestion,then most probably we cannot guarantee the existence of any reasonable approximate Nash equilibrium.By partly discarding the FIFO principle and introducing destination priorities in the regulation rules,we propose a new atomic routing model.In each such game,we prove that a pure strategy Nash equilibrium always exists and can be computed in polynomial time.In addition,the multicommodity routing game can be iteratively decomposed into a series of well-behaved single-destination routing games,which will provide a good characterization of all NEs of the original game.
基金supported by the National Natural Science Foundation of China(No.62476025)the Shaanxi Provincial Department of Science and Technology Projects(No.2013K06-39).
文摘Automatically extracting Drug-Drug Interactions (DDIs) from text is a crucial and challenging task, particularly when multiple medications are taken concurrently. In this study, we propose a novel approach, called Enhanced Attention-driven Dynamic Graph Convolutional Network (E-ADGCN), for DDI extraction. Our model combines the Attention-driven Dynamic Graph Convolutional Network (ADGCN) with a feature fusion method and multi-task learning framework. The ADGCN effectively utilizes entity information and dependency tree information from biomedical texts to extract DDIs. The feature fusion method integrates User-Generated Content (UGC) and molecular information with drug entity information from text through dynamic routing. By leveraging external resources, our approach maximizes the auxiliary effect and improves the accuracy of DDI extraction. We evaluate the E-ADGCN model on the extended DDIExtraction2013 dataset and achieve an F1-score of 81.45%. This research contributes to the advancement of automated methods for extracting valuable drug interaction information from textual sources, facilitating improved medication management and patient safety.
文摘This study focuses on the application of dynamic route planning and augmented reality(AR)technology within interactive theme trail platforms.Taking the“Dongpo Travelogue”digital guide mini-program as a case study,it employs empirical analysis to explore its impact on enhancing visitor engagement and cultural identification.Employing a combined quantitative and qualitative methodology,the study analyses the platform’s functional implementation in route planning,cultural narration,interactive games,and their impact on visitor experience.Findings indicate that the integration of dynamic route planning and AR technology significantly enhances visitor engagement and cultural identity,offering novel insights for the digital transformation of the cultural tourism industry.
文摘Wireless Networked Control Systems (WNCS) are used to implement a control mechanism over a wireless network that is capable of carrying real-time traffic. This field has drawn enormous attention from current researchers because of its flexibility and robustness. However, designing efficient WNCS over Mobile Ad Hoc Networks (MANET) is still a challenging topic because of its less-predictable aspects, such as inconsistent delay, packet drop probability, and dynamic topology. This paper presents design guidelines for WNCS over MANET using the Network Simulator version 2, NS2 software. It investigates the impact of packet delay and packet drop under the AODV and DSR routing protocols. The simulation results have been compared to MATLAB results for validation. Keywords Adhoc On-Demand Distance Vector (AODV) routing - Dynamic Source routing (DSR) - Mobile Adhoc Networks (MANET) - Wireless Networked Control Systems (WNCS) Mohammad Shahidul Hasan received his BSc and first MSc in Computer Science from the University of Dhaka, Bangladesh. He obtained his 2nd MSc in Computer & Network Engineering from Sheffield Hallam University, Sheffield, UK. Currently he is pursuing his PhD under the Faculty of Computing, Engineering and Technology, Staffordshire University, Stafford, UK in Networked Control Systems over MANET.Chris Harding received his BSc in Computing Science and Masters by Research from Staffordshire University, UK. Currently he is pursuing his PhD in Wireless Networked Control Systems, specifically looking at NCS over MANETs, with research interests in this area concentrating on the network routing and effect of routing protocols on the NCS system.Hongnian Yu is Professor of Computer Science at Staffordshire University. He was a lecturer in Control and Systems Engineering at Yanshan University, China in 1985–1990, did his PhD in Robotics at King’s College London (1990–1994), was a research fellow in Manufacturing Systems at Sussex University (1994–1996), a lecturer in Artificial Intelligence at Liver-pool John Moore’s University (1996–1999), a lecturer in Control and Systems Engineering at the University of Exeter (1999–2002), and a Senior Lecturer in Computing at the University of Bradford (2002–2004). He now leads the Mobile Computing and Distributed Systems Research Group at Staffordshire University. He was a founding member of the Modeling Optimisation Scheduling and Intelligent Control research group at the University of Bradford. He has extensive research experience in neural networks, mobile computing, modeling, control of robot manipulators, and modeling, scheduling, planning, and simulations of large discrete event dynamic systems with applications to manufacturing systems, supply chains, transportation networks, and computer networks. He has published over 100 research papers focusing on the following: neural networks, computer networks, adaptive and robust control of robot manipulators, analysis and control of hybrid machines, control of timed delay systems, predictive control, manufacturing system modeling and scheduling, planning, and supply chains. He has held several research grants from EPSRC, the Royal Society, and the EU, as well as from industry. He was awarded the F.C. William Premium for his paper on adaptive and robust control of robot manipulators by the IEE Council in 1997. Professor Yu is an EPSRC college member, a member of IEEE, and a committee member of several conferences and journal editorial boards.Alison Griffiths has been a Senior Lecturer in Telecommunications at Staffordshire University since 2003. She was a lecturer in Computing at Staffordshire University in 2002–2003. She was a Research Associate on an EPSRC funded project whilst doing her PhD on the convergence of Mobile Computing and Telecommunications at Staffordshire University (1999–2003). The investigation consisted of the communication of different types of media (voice, video conferencing, web browsing, and downloading) over a common network, using a mobile device. Problems considered were the complications that occurred when a user moves, and consequently changes their end-point in the network during communication, with respect to the type of service the user is provided with (delays and losses). She obtained both her MEng and 1st Class BEng (Hons) from Staffordshire University in 1999 and 1998 respectively. She is now part of the Mobile Computing and Distributed Systems Research Group at Staffordshire University. She has published 8 research papers focusing on quality of service and access between cellular and IP packet switched networks. Future directions include mobile agents and control of mobile wireless ad-hoc networks. Her current research interests have extended to Wireless Networked Control Systems, specifically looking at NCS over MANETs, with research interests in this area concentrating on the network routing and effect of routing protocols on the NCS system.
文摘Network security and energy consumption are deemed to be two important components of wireless and mobile ad hoc networks(WMANets).There are various routing attacks which harm Ad Hoc networks.This is because of the unsecure wireless communication,resource constrained capabilities and dynamic topology.In order to cope with these issues,Ad Hoc On-Demand Distance Vector(AODV)routing protocol can be used to remain the normal networks functionality and to adjust data transmission by defending the networks against black hole attacks.The proposed system,in this work,identifies the optimal route from sender to collector,prioritizing the number of jumps,the battery life,and security,which are fundamental prerequisites.Researches have proposed various plans for detecting the shortest route,as well as ensuring energy conversions and defense against threats and attacks.In this regard,the packet drop attack is one of the most destructive attack against WMANet communication and hence merits special attention.This type of attack may allow the attacker to take control of the attacked hubs,which may lost packets or transmitted information via a wrong route during the packets journey from a source hub to a target one.Hence,a new routing protocol method has been proposed in this study.It applies the concept of energy saving systems to conserve energy that is not required by the system.The proposed method for energy aware detection and prevention of packet drop attacks in mobile ad hoc networks is termed the Ad Hoc On-Demand and Distance Vector–Packet Drop Battling Mechanism(AODV–PDBM).
