Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these netw...Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.展开更多
The Internet of Things(IoT)is gaining attention because of its broad applicability,especially by integrating smart devices for massive communication during sensing tasks.IoT-assisted Wireless Sensor Networks(WSN)are s...The Internet of Things(IoT)is gaining attention because of its broad applicability,especially by integrating smart devices for massive communication during sensing tasks.IoT-assisted Wireless Sensor Networks(WSN)are suitable for various applications like industrial monitoring,agriculture,and transportation.In this regard,routing is challenging to nd an efcient path using smart devices for transmitting the packets towards big data repositories while ensuring efcient energy utilization.This paper presents the Robust Cluster Based Routing Protocol(RCBRP)to identify the routing paths where less energy is consumed to enhances the network lifespan.The scheme is presented in six phases to explore ow and communication.We propose the two algorithms:(i)energy-efcient clustering and routing algorithm and (ii)distance and energy consumption calculation algorithm.The scheme consumes less energy and balances the load by clustering the smart devices.Our work is validated through extensive simulation using Matlab.Results elucidate the dominance of the proposed scheme is compared to counterparts in terms of energy consumption,the number of packets received at BS and the number of active and dead nodes.In the future,we shall consider edge computing to analyze the performance of robust clustering.展开更多
Internet of Things(IoT)is a recent paradigm to improve human lifestyle.Nowadays,number devices are connected to the Internet drastically.Thus,the people can control and monitor the physical things in real-time without...Internet of Things(IoT)is a recent paradigm to improve human lifestyle.Nowadays,number devices are connected to the Internet drastically.Thus,the people can control and monitor the physical things in real-time without delay.The IoT plays a vital role in all kind of fields in our world such as agriculture,livestock,transport,and healthcare,grid system,connected home,elderly people carrying system,cypher physical system,retail,and intelligent systems.In IoT energy conservation is a challenging task,as the devices are made up of low-cost and low-power sensing devices and local processing.IoT networks have significant challenges in two areas:network lifespan and energy usage.Therefore,the clustering is a right choice to prolong the energy in the network.In LEACH clustering protocol,sometimes the same node acts as CH again and again probabilistically.To overcome these issues,this paper proposes the Energy-Aware Cluster-based Routing(EACRLEACH)protocol in WSN based IoT.The Cluster Head(CH)selection is a crucial task in clustering protocol inWSN based IoT.In EACR-LEACH,the CH is selected by using the routing metrics,Residual Energy(RER),Number of Neighbors(NoN),Distance between Sensor Node and Sink(Distance)and Number of Time Node Act as CH(NTNACH).An extensive simulation is conducted on MATLAB 2019a.The accomplishment of EACR-LEACH is compared to LEACH and SE-LEACH.The proposed EACR-LEACH protocol extends the network’s lifetime by 4%-8%and boosts throughput by 16%–24%.展开更多
Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combinin...Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.展开更多
The Routing Protocol for Low-power and Lossy Networks(RPL)is widely used in Internet of Things(IoT)systems,where devices usually have very limited resources.However,RPL still faces several problems,such as high energy...The Routing Protocol for Low-power and Lossy Networks(RPL)is widely used in Internet of Things(IoT)systems,where devices usually have very limited resources.However,RPL still faces several problems,such as high energy usage,unstable links,and inefficient routing decisions,which reduce the overall network performance and lifetime.In this work,we introduce TABURPL,an improved routing method that applies Tabu Search(TS)to optimize the parent selection process.The method uses a combined cost function that considers Residual Energy,Transmission Energy,Distance to the Sink,Hop Count,Expected Transmission Count(ETX),and Link Stability Rate(LSR).Simulation results show that TABURPL improves link stability,lowers energy consumption,and increases the packet delivery ratio compared with standard RPL and other existing approaches.These results indicate that Tabu Search can handle the complex trade-offs in IoT routing and can provide a more reliable solution for extending the network lifetime.展开更多
With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used ...With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used to improve efficiency.This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand.New customers appear in the delivery process at any time and are periodically optimized according to time slices.Then,we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem.The classical ant colony algorithm uses spatial distance to select nodes,while TS-ACO considers the impact of both temporal and spatial distance on node selection.Meanwhile,we adopt Cordeau’s Multi-Depot Vehicle Routing Problem with Time Windows(MDVRPTW)dataset to evaluate the performance of our system.According to the experimental results,TS-ACO,which considers spatial and temporal distance,is more effective than the classical ACO,which only considers spatial distance.展开更多
Mega low Earth orbit(LEO)satellite networks serve as effective complements to terrestrial networks.However,the dual mobility of users and LEO satellites makes inter-satellite handovers more frequent for users.Moreover...Mega low Earth orbit(LEO)satellite networks serve as effective complements to terrestrial networks.However,the dual mobility of users and LEO satellites makes inter-satellite handovers more frequent for users.Moreover,there are both ascending and descending segments in widely deployed walker-delta constellations.Even if the locations of users do not change,when the access satellites of the communicating parties are not in the same ascending or descending segment,the end-to-end latency between them will increase.To address this challenge,the self-decision handover(SDH)strategy and the joint decision handover(JDH)strategy are proposed,and they both incorporate the routing hops as a crucial handover criterion to minimize the end-to-end latency.In addition,the shortest route hop-count algorithm is designed to assist in the handover decision-making process.Simulations demonstrate that the proposed handover strategies outperform the traditional handover strategies in terms of the number of handovers and end-to-end latency.展开更多
Wireless sensor networks（WSNs） are emerging as essential and popular ways of providing pervasive computing environments for various applications. Unbalanced energy consumption is an inherent problem in WSNs, charact...Wireless sensor networks（WSNs） are emerging as essential and popular ways of providing pervasive computing environments for various applications. Unbalanced energy consumption is an inherent problem in WSNs, characterized by multi-hop routing and a many-to-one traffic pattern. This uneven energy dissipation can significantly reduce network lifetime. In multi-hop sensor networks, information obtained by the monitoring nodes need to be routed to the sinks, the energy consumption rate per unit information transmission depends on the choice of the next hop node. In an energy-aware routing approach, most proposed algorithms aim at minimizing the total energy consumption or maximizing network lifetime. In this paper, we propose a novel energy aware hierarchical cluster-based（NEAHC） routing protocol with two goals： minimizing the total energy consumption and ensuring fairness of energy consumption between nodes. We model the relay node choosing problem as a nonlinear programming problem and use the property of convex function to find the optimal solution. We also evaluate the proposed algorithm via simulations at the end of this paper.展开更多
The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industria...The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart agriculture.Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes.This paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks.The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies.The protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base station.The performance of the proposed protocol is evaluated through the network simulator NS3.40.For different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network lifetime.For 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.展开更多
Low Energy Adaptive Clustering Hierarchy(LEACH)is a routing algorithm in agricultural wireless multimedia sensor networks(WMSNs)that includes two kinds of improved protocol,LEACH_D and LEACH_E.In this study,obstacles ...Low Energy Adaptive Clustering Hierarchy(LEACH)is a routing algorithm in agricultural wireless multimedia sensor networks(WMSNs)that includes two kinds of improved protocol,LEACH_D and LEACH_E.In this study,obstacles were overcome in widely used protocols.An improved algorithm was proposed to solve existing problems,such as energy source restriction,communication distance,and energy of the nodes.The optimal number of clusters was calculated by the first-order radio model of the improved algorithm to determine the percentage of the cluster heads in the network.High energy and the near sink nodes were chosen as cluster heads based on the residual energy of the nodes and the distance between the nodes to the sink node.At the same time,the K-means clustering analysis method was used for equally assigning the nodes to several clusters in the network.Both simulation and the verification results showed that the survival number of the proposed algorithm LEACH-ED increased by 66%.Moreover,the network load was high and network lifetime was longer.The mathematical model between the average voltage of nodes(y)and the running time(x)was concluded in the equation y=−0.0643x+4.3694,and the correlation coefficient was R2=0.9977.The research results can provide a foundation and method for the design and simulation of the routing algorithm in agricultural WMSNs.展开更多
Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are fac...Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network topologies.These challenges are coped with by designing advanced routing protocols.In this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes.Our method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and latency.Theproposed protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue overflow.It also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized.Compared to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).展开更多
Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To sa...Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.展开更多
Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current so...Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current solutions face numerous challenges in continuously ensuring trustworthy routing,fulfilling diverse requirements,achieving reasonable resource allocation,and safeguarding against malicious behaviors of network operators.We propose CrowdRouting,a novel cross-domain routing scheme based on crowdsourcing,dedicated to establishing sustained trust in cross-domain routing,comprehensively considering and fulfilling various customized routing requirements,while ensuring reasonable resource allocation and effectively curbing malicious behavior of network operators.Concretely,CrowdRouting employs blockchain technology to verify the trustworthiness of border routers in different network domains,thereby establishing sustainable and trustworthy crossdomain routing based on sustained trust in these routers.In addition,CrowdRouting ingeniously integrates a crowdsourcing mechanism into the auction for routing,achieving fair and impartial allocation of routing rights by flexibly embedding various customized routing requirements into each auction phase.Moreover,CrowdRouting leverages incentive mechanisms and routing settlement to encourage network domains to actively participate in cross-domain routing,thereby promoting optimal resource allocation and efficient utilization.Furthermore,CrowdRouting introduces a supervisory agency(e.g.,undercover agent)to effectively suppress the malicious behavior of network operators through the game and interaction between the agent and the network operators.Through comprehensive experimental evaluations and comparisons with existing works,we demonstrate that CrowdRouting excels in providing trustworthy and fine-grained customized routing services,stimulating active participation in cross-domain routing,inhibiting malicious operator behavior,and maintaining reasonable resource allocation,all of which outperform baseline schemes.展开更多
This paper systematically reviews the latest research developments in Vehicle Routing Problems(VRP).It examines classical VRP models and their classifications across different dimensions,including load capacity,operat...This paper systematically reviews the latest research developments in Vehicle Routing Problems(VRP).It examines classical VRP models and their classifications across different dimensions,including load capacity,operational characteristics,optimization objectives,vehicle types,and time constraints.Based on literature retrieval results from the Web of Science database,the paper analyzes the current state and trends in VRP research,providing detailed explanations of VRP models and algorithms applied to various scenarios in recent years.Additionally,the article discusses limitations in existing research and provides perspectives on future development trends in VRP research.This review offers researchers in the VRP field a comprehensive overview while identifying future research directions.展开更多
This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocatio...This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.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
As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in mult...As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.展开更多
This study addresses the Unmanned Aerial Vehicle routing problems with profits,which requires balancing mission profit,path efficiency,and battery health under complex constraints,particularly the nonlinear degradatio...This study addresses the Unmanned Aerial Vehicle routing problems with profits,which requires balancing mission profit,path efficiency,and battery health under complex constraints,particularly the nonlinear degradation of batteries.This paper proposes an enhanced memetic algorithm by integrating adaptive local search and a dynamic population management mechanism.The algorithm employs a hybrid initialization strategy to generate high-quality initial solutions.It incorporates an improved linear crossover operator to preserve beneficial path characteristics and introduces dynamically probability-controlled local search to optimize solution quality.To enhance global exploration capability,a population screening mechanism based on solution similarity and a population restart strategy simulating biological mass extinction are designed.Extensive experiments conducted on standard Tsiligirides's and Chao's datasets demonstrate the algorithm's robust performance across scenarios ranging from 21 to 66 nodes and time constraints spanning 5 to 130 minutes.The algorithm attains 95%accuracy relative to maximum total score within 30 iterations,surpassing 99%accuracy after 100 iterations.Its comprehensive performance significantly surpasses that of traditional heuristic methods.The proposed method provides an efficient and robust solution for Unmanned Aerial Vehicle routing planning under intricate constraints.展开更多
Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,com...Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,communicating in a distributed dynamic environment,face several security challenges,with trust being one of the most important issues in inter-domain routing.Existing research,which performs trust evaluation when exchanging routing information to suppress malicious routing behavior,cannot meet the scalability requirements of BGP nodes.In this paper,we propose a blockchain-based trust model for inter-domain routing.Our model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the blockchain.The BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective alliance.We incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing service.We forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing behavior.We use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust model.Compared with the classical trust model,our trust model not only saves more storage overhead,but also provides higher security,especially reducing the impact of collusion attacks.展开更多
The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the...The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the selection of appropriate routing protocols, which is crucial for maintaining high Quality of Service (QoS). The Internet Engineering Task Force’s Routing Over Low Power and Lossy Networks (IETF ROLL) working group developed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) to meet these needs. While the initial RPL standard focused on single-metric route selection, ongoing research explores enhancing RPL by incorporating multiple routing metrics and developing new Objective Functions (OFs). This paper introduces a novel Objective Function (OF), the Reliable and Secure Objective Function (RSOF), designed to enhance the reliability and trustworthiness of parent selection at both the node and link levels within IoT and RPL routing protocols. The RSOF employs an adaptive parent node selection mechanism that incorporates multiple metrics, including Residual Energy (RE), Expected Transmission Count (ETX), Extended RPL Node Trustworthiness (ERNT), and a novel metric that measures node failure rate (NFR). In this mechanism, nodes with a high NFR are excluded from the parent selection process to improve network reliability and stability. The proposed RSOF was evaluated using random and grid topologies in the Cooja Simulator, with tests conducted across small, medium, and large-scale networks to examine the impact of varying node densities. The simulation results indicate a significant improvement in network performance, particularly in terms of average latency, packet acknowledgment ratio (PAR), packet delivery ratio (PDR), and Control Message Overhead (CMO), compared to the standard Minimum Rank with Hysteresis Objective Function (MRHOF).展开更多
文摘Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.
文摘The Internet of Things(IoT)is gaining attention because of its broad applicability,especially by integrating smart devices for massive communication during sensing tasks.IoT-assisted Wireless Sensor Networks(WSN)are suitable for various applications like industrial monitoring,agriculture,and transportation.In this regard,routing is challenging to nd an efcient path using smart devices for transmitting the packets towards big data repositories while ensuring efcient energy utilization.This paper presents the Robust Cluster Based Routing Protocol(RCBRP)to identify the routing paths where less energy is consumed to enhances the network lifespan.The scheme is presented in six phases to explore ow and communication.We propose the two algorithms:(i)energy-efcient clustering and routing algorithm and (ii)distance and energy consumption calculation algorithm.The scheme consumes less energy and balances the load by clustering the smart devices.Our work is validated through extensive simulation using Matlab.Results elucidate the dominance of the proposed scheme is compared to counterparts in terms of energy consumption,the number of packets received at BS and the number of active and dead nodes.In the future,we shall consider edge computing to analyze the performance of robust clustering.
基金We deeply acknowledge Taif University for supporting this study through Taif University Researchers Supporting Project Number(TURSP-2020/313),Taif University,Taif,Saudi Arabia.
文摘Internet of Things(IoT)is a recent paradigm to improve human lifestyle.Nowadays,number devices are connected to the Internet drastically.Thus,the people can control and monitor the physical things in real-time without delay.The IoT plays a vital role in all kind of fields in our world such as agriculture,livestock,transport,and healthcare,grid system,connected home,elderly people carrying system,cypher physical system,retail,and intelligent systems.In IoT energy conservation is a challenging task,as the devices are made up of low-cost and low-power sensing devices and local processing.IoT networks have significant challenges in two areas:network lifespan and energy usage.Therefore,the clustering is a right choice to prolong the energy in the network.In LEACH clustering protocol,sometimes the same node acts as CH again and again probabilistically.To overcome these issues,this paper proposes the Energy-Aware Cluster-based Routing(EACRLEACH)protocol in WSN based IoT.The Cluster Head(CH)selection is a crucial task in clustering protocol inWSN based IoT.In EACR-LEACH,the CH is selected by using the routing metrics,Residual Energy(RER),Number of Neighbors(NoN),Distance between Sensor Node and Sink(Distance)and Number of Time Node Act as CH(NTNACH).An extensive simulation is conducted on MATLAB 2019a.The accomplishment of EACR-LEACH is compared to LEACH and SE-LEACH.The proposed EACR-LEACH protocol extends the network’s lifetime by 4%-8%and boosts throughput by 16%–24%.
文摘Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.
文摘The Routing Protocol for Low-power and Lossy Networks(RPL)is widely used in Internet of Things(IoT)systems,where devices usually have very limited resources.However,RPL still faces several problems,such as high energy usage,unstable links,and inefficient routing decisions,which reduce the overall network performance and lifetime.In this work,we introduce TABURPL,an improved routing method that applies Tabu Search(TS)to optimize the parent selection process.The method uses a combined cost function that considers Residual Energy,Transmission Energy,Distance to the Sink,Hop Count,Expected Transmission Count(ETX),and Link Stability Rate(LSR).Simulation results show that TABURPL improves link stability,lowers energy consumption,and increases the packet delivery ratio compared with standard RPL and other existing approaches.These results indicate that Tabu Search can handle the complex trade-offs in IoT routing and can provide a more reliable solution for extending the network lifetime.
基金supported by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology.
文摘With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used to improve efficiency.This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand.New customers appear in the delivery process at any time and are periodically optimized according to time slices.Then,we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem.The classical ant colony algorithm uses spatial distance to select nodes,while TS-ACO considers the impact of both temporal and spatial distance on node selection.Meanwhile,we adopt Cordeau’s Multi-Depot Vehicle Routing Problem with Time Windows(MDVRPTW)dataset to evaluate the performance of our system.According to the experimental results,TS-ACO,which considers spatial and temporal distance,is more effective than the classical ACO,which only considers spatial distance.
基金supported by the State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster(MS01240103)the National Natural Science Foundation of China(62071146,62431009)+2 种基金the National 2011 Collaborative Innovation Center of Wireless Communication Technologies(2242022k60006)the Research Project Fund of Songjiang Laboratory(SL20230104)Heilongjiang Province Postdoctoral General Foundation(LBH-Z22133)。
文摘Mega low Earth orbit(LEO)satellite networks serve as effective complements to terrestrial networks.However,the dual mobility of users and LEO satellites makes inter-satellite handovers more frequent for users.Moreover,there are both ascending and descending segments in widely deployed walker-delta constellations.Even if the locations of users do not change,when the access satellites of the communicating parties are not in the same ascending or descending segment,the end-to-end latency between them will increase.To address this challenge,the self-decision handover(SDH)strategy and the joint decision handover(JDH)strategy are proposed,and they both incorporate the routing hops as a crucial handover criterion to minimize the end-to-end latency.In addition,the shortest route hop-count algorithm is designed to assist in the handover decision-making process.Simulations demonstrate that the proposed handover strategies outperform the traditional handover strategies in terms of the number of handovers and end-to-end latency.
基金supported by the National Youth Science Fund Project(61501052,61501047)the Fundamental Research Funds for the Central Universities of China(2015RC05)
文摘Wireless sensor networks（WSNs） are emerging as essential and popular ways of providing pervasive computing environments for various applications. Unbalanced energy consumption is an inherent problem in WSNs, characterized by multi-hop routing and a many-to-one traffic pattern. This uneven energy dissipation can significantly reduce network lifetime. In multi-hop sensor networks, information obtained by the monitoring nodes need to be routed to the sinks, the energy consumption rate per unit information transmission depends on the choice of the next hop node. In an energy-aware routing approach, most proposed algorithms aim at minimizing the total energy consumption or maximizing network lifetime. In this paper, we propose a novel energy aware hierarchical cluster-based（NEAHC） routing protocol with two goals： minimizing the total energy consumption and ensuring fairness of energy consumption between nodes. We model the relay node choosing problem as a nonlinear programming problem and use the property of convex function to find the optimal solution. We also evaluate the proposed algorithm via simulations at the end of this paper.
基金This work was supported by the Basic Science Research Program through the NationalResearch Foundation ofKorea(NRF)funded by the Ministry of Education under Grant RS-2023-00237300 and Korea Institute of Planning and Evaluation for Technology in Food,Agriculture and Forestry(IPET)through the Agriculture and Food Convergence Technologies Program for Research Manpower Development,funded by Ministry of Agriculture,Food and Rural Affairs(MAFRA)(Project No.RS-2024-00397026).
文摘The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications,such as remote health monitoring,industrial monitoring,transportation,and smart agriculture.Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes.This paper presents a traffic-aware,cluster-based,and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks.The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies.The protocol considers multi-criteria attributes,i.e.,energy,traffic load,and distance parameters to select the next hop for data delivery towards the base station.The performance of the proposed protocol is evaluated through the network simulator NS3.40.For different traffic rates,number of nodes,and different packet sizes,the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio,energy consumption,end-to-end delay,and network lifetime.For 100 nodes,the proposed protocol achieved a 13%improvement in packet delivery ratio,10 ms improvement in delay,and 10 mJ improvement in average energy consumption over LoRaWAN.
基金Project on the Integration of Industry,Education and Research of Henan Province(Grant No.142107000055,162107000026)Scientific and Technological Project of Henan Province(Grant No.152102210190,162102210202)+2 种基金Natural Science Foundation of Henan Educational Committee(Grant No.14B416004,14A416002 and 13A416264)Key Project of Henan Tobacco Company(HYKJ201316)Innovation Ability Foundation of Natural Science(Grant No.2013ZCX002)of Henan University of Science and Technology.
文摘Low Energy Adaptive Clustering Hierarchy(LEACH)is a routing algorithm in agricultural wireless multimedia sensor networks(WMSNs)that includes two kinds of improved protocol,LEACH_D and LEACH_E.In this study,obstacles were overcome in widely used protocols.An improved algorithm was proposed to solve existing problems,such as energy source restriction,communication distance,and energy of the nodes.The optimal number of clusters was calculated by the first-order radio model of the improved algorithm to determine the percentage of the cluster heads in the network.High energy and the near sink nodes were chosen as cluster heads based on the residual energy of the nodes and the distance between the nodes to the sink node.At the same time,the K-means clustering analysis method was used for equally assigning the nodes to several clusters in the network.Both simulation and the verification results showed that the survival number of the proposed algorithm LEACH-ED increased by 66%.Moreover,the network load was high and network lifetime was longer.The mathematical model between the average voltage of nodes(y)and the running time(x)was concluded in the equation y=−0.0643x+4.3694,and the correlation coefficient was R2=0.9977.The research results can provide a foundation and method for the design and simulation of the routing algorithm in agricultural WMSNs.
文摘Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network topologies.These challenges are coped with by designing advanced routing protocols.In this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes.Our method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and latency.Theproposed protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue overflow.It also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized.Compared to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).
基金National Key Research and Development Program(2021YFB2900604)。
文摘Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.
基金supported in part by the National Natural Science Foundation of China under Grant U23A20300 and 62072351in part by the Key Research Project of Shaanxi Natural Science Foundation under Grant 2023-JC-ZD-35+1 种基金in part by the Concept Verification Funding of Hangzhou Institute of Technology of Xidian University under Grant GNYZ2024XX007in part by the 111 Project under Grant B16037.
文摘Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current solutions face numerous challenges in continuously ensuring trustworthy routing,fulfilling diverse requirements,achieving reasonable resource allocation,and safeguarding against malicious behaviors of network operators.We propose CrowdRouting,a novel cross-domain routing scheme based on crowdsourcing,dedicated to establishing sustained trust in cross-domain routing,comprehensively considering and fulfilling various customized routing requirements,while ensuring reasonable resource allocation and effectively curbing malicious behavior of network operators.Concretely,CrowdRouting employs blockchain technology to verify the trustworthiness of border routers in different network domains,thereby establishing sustainable and trustworthy crossdomain routing based on sustained trust in these routers.In addition,CrowdRouting ingeniously integrates a crowdsourcing mechanism into the auction for routing,achieving fair and impartial allocation of routing rights by flexibly embedding various customized routing requirements into each auction phase.Moreover,CrowdRouting leverages incentive mechanisms and routing settlement to encourage network domains to actively participate in cross-domain routing,thereby promoting optimal resource allocation and efficient utilization.Furthermore,CrowdRouting introduces a supervisory agency(e.g.,undercover agent)to effectively suppress the malicious behavior of network operators through the game and interaction between the agent and the network operators.Through comprehensive experimental evaluations and comparisons with existing works,we demonstrate that CrowdRouting excels in providing trustworthy and fine-grained customized routing services,stimulating active participation in cross-domain routing,inhibiting malicious operator behavior,and maintaining reasonable resource allocation,all of which outperform baseline schemes.
文摘This paper systematically reviews the latest research developments in Vehicle Routing Problems(VRP).It examines classical VRP models and their classifications across different dimensions,including load capacity,operational characteristics,optimization objectives,vehicle types,and time constraints.Based on literature retrieval results from the Web of Science database,the paper analyzes the current state and trends in VRP research,providing detailed explanations of VRP models and algorithms applied to various scenarios in recent years.Additionally,the article discusses limitations in existing research and provides perspectives on future development trends in VRP research.This review offers researchers in the VRP field a comprehensive overview while identifying future research directions.
文摘This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.
基金This research was supported by ESIEA Paris through internal research resources provided by esieaLab LDR.
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.
文摘As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.
基金funded by Ministry of Education,grant number 2024120910911.
文摘This study addresses the Unmanned Aerial Vehicle routing problems with profits,which requires balancing mission profit,path efficiency,and battery health under complex constraints,particularly the nonlinear degradation of batteries.This paper proposes an enhanced memetic algorithm by integrating adaptive local search and a dynamic population management mechanism.The algorithm employs a hybrid initialization strategy to generate high-quality initial solutions.It incorporates an improved linear crossover operator to preserve beneficial path characteristics and introduces dynamically probability-controlled local search to optimize solution quality.To enhance global exploration capability,a population screening mechanism based on solution similarity and a population restart strategy simulating biological mass extinction are designed.Extensive experiments conducted on standard Tsiligirides's and Chao's datasets demonstrate the algorithm's robust performance across scenarios ranging from 21 to 66 nodes and time constraints spanning 5 to 130 minutes.The algorithm attains 95%accuracy relative to maximum total score within 30 iterations,surpassing 99%accuracy after 100 iterations.Its comprehensive performance significantly surpasses that of traditional heuristic methods.The proposed method provides an efficient and robust solution for Unmanned Aerial Vehicle routing planning under intricate constraints.
基金funded by the National Natural Science Foundation of China,grant numbers(62272007,62001007)the Natural Science Foundation of Beijing,grant numbers(4234083,4212018)The authors also extend their appreciation to King Khalid University for funding this work through the Large Group Project under grant number RGP.2/373/45.
文摘Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,communicating in a distributed dynamic environment,face several security challenges,with trust being one of the most important issues in inter-domain routing.Existing research,which performs trust evaluation when exchanging routing information to suppress malicious routing behavior,cannot meet the scalability requirements of BGP nodes.In this paper,we propose a blockchain-based trust model for inter-domain routing.Our model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the blockchain.The BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective alliance.We incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing service.We forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing behavior.We use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust model.Compared with the classical trust model,our trust model not only saves more storage overhead,but also provides higher security,especially reducing the impact of collusion attacks.
文摘The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the selection of appropriate routing protocols, which is crucial for maintaining high Quality of Service (QoS). The Internet Engineering Task Force’s Routing Over Low Power and Lossy Networks (IETF ROLL) working group developed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) to meet these needs. While the initial RPL standard focused on single-metric route selection, ongoing research explores enhancing RPL by incorporating multiple routing metrics and developing new Objective Functions (OFs). This paper introduces a novel Objective Function (OF), the Reliable and Secure Objective Function (RSOF), designed to enhance the reliability and trustworthiness of parent selection at both the node and link levels within IoT and RPL routing protocols. The RSOF employs an adaptive parent node selection mechanism that incorporates multiple metrics, including Residual Energy (RE), Expected Transmission Count (ETX), Extended RPL Node Trustworthiness (ERNT), and a novel metric that measures node failure rate (NFR). In this mechanism, nodes with a high NFR are excluded from the parent selection process to improve network reliability and stability. The proposed RSOF was evaluated using random and grid topologies in the Cooja Simulator, with tests conducted across small, medium, and large-scale networks to examine the impact of varying node densities. The simulation results indicate a significant improvement in network performance, particularly in terms of average latency, packet acknowledgment ratio (PAR), packet delivery ratio (PDR), and Control Message Overhead (CMO), compared to the standard Minimum Rank with Hysteresis Objective Function (MRHOF).
