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A novel multi-objective-derived heuristic-assisted reliable routing path selection scheme in vehicular ad hoc networks

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WIRELESS NETWORKS 2025年第4期31卷 3059-3077页

作者： Devi, S. Kalpana Thenmozhi, R. SRM Inst Sci & Technol Coll Engn & Technol Sch Comp Dept Comp Technol Kattankulathur 603203 Tamil Nadu India

An emerging Mobile Ad-Hoc Network (MANET) is the Vehicular ad-hoc Network (VANET), which is one of the best applications in the transportation system. A VANET should have a huge number of nodes, where the inter-node communication is critical, and it is provided securely, as practical applications solve critical life situations where human lives are at stake in VANETs. It is a decentralized and self-organized system that can be developed using the mobile vehicles, and communication between the vehicles is done by sending traffic-based valuable information. Mobile vehicles act as the source nodes because they are used to transmit and receive traffic-based information on the channel. Altgough the distance of data transmission between the vehicles is limited distance, it can change from one network topology to another using the mobility nature. In multi-hop VANET, message delivery at the destination place is very challenging. The proper path selection among the nodes is very important in VANET. The main hypothesis of the research work is to design a hybridized optimization approach for determining the optimal path between the source and destination vehicle based on the multi-objective functions including distance, link reliability, end-to-end delay, route throughput, Packet Delivery Ratio (PDR), and link duration for lossless packet transmission by reducing the routing overhead in the dynamic vehicular environment. The new hybrid algorithm named Hybrid Tug of War Flow Direction Optimization (HTWFDO) is developed by combining the two well-known algorithms and they are Tug of War Optimization (TWO) and Flow Direction Algorithm (FDA). The MATLAB 2020a simulation tool is utilized to perform the simulation experiment on the developed hybridized optimal path selection process. Based on the experiment, the proposed HTWFDO algorithm provided the throughput value is36.36%, 80%, 36.36%, and 80% increased over the existing algorithms at the node value of *** simulation results

关键词： Vehicular adhoc networks Routing Optimal path selection multi-objective function Hybrid tug of war flow direction optimization Link reliability End-to-end delay Route throughput Packet delivery ratio Link duration

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An innovative energy efficient routing protocol in MANET with hybridized osprey-fire hawk optimization algorithm to attain optimal routing constraints

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WIRELESS NETWORKS 2025年第3期31卷 2005-2026页

作者： Saravanan, N. Arunachalam, Rajesh Nisha, A. Sahaya Anselin Karthikayen, A. KSR Coll Engn Dept CSE IoT Tiruchengode 637215 Tamil Nadu India Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept Elect & Commun Engn Chennai 602105 Tamil Nadu India Sathyabama Inst Sci & Technol Dept Elect & Commun Engn Chennai 600119 Tamil Nadu India

A quickly deployable wireless, self-organizing, infrastructure-free network is Mobile Adhoc Networks (MANETs), they are particularly well suited for providing flawless communications during military surgeries, natural disasters, and crises without a radio infrastructure. Due to the changing dynamic topology and flexibility of the structures, security is the major concern in MANET. It is vulnerable to various attacks, including program modification, routing, and eavesdropping. When compared to Quality of Service (QoS) problems, the security problems on MANET are worse. Therefore, the best method to guarantee the security of MANET is intrusion tracking, it handles the network by recognizing violations. The efficacy and security of the MANET is increased by the intrusion detection approaches. The capacity of the cellular node to send packets is based on the overall system life, and it might also be altered by the power collapse of the node. For better navigation in MANET, the multi-paths and the routing protocol should be chosen carefully. Because of the constrained resources and changing dynamic topology, performing safe energy-efficient routing is difficult in MANET. Thus, it is highly crucial to resolve several challenges presented in the traditional routing techniques. So, a new routing technique for MANET is designed by considering the optimal routing constraints. Here, a new Hybridized Osprey and Fire Hawk Optimization Strategy (HO-FHOS) is employed to enhance the energy-efficient features in the routing process. The initiated routing protocol considers the route length in selecting the best route. Moreover, the optimal routing constraints such as distance, end-to-end delay, residual energy, link reliability, Packet Delivery Ratio, path loss, throughput, and route survival rate are achieved using the developed model (HO-FHOS). Hence, the implemented energy-efficient routing protocol secured a superior performance rate than the conventional energy-efficient routin

关键词： Mobile Adhoc Networks Energy efficient routing Hybridized osprey and fire hawk optimization strategy Optimal path selection multi-objective function

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multi-objective Evaluation Method for Efficient Water Energy Utilization in multistage Hydraulic Turbines With Ultrahigh Water Head and Low Flow Rate

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ENERGY SCIENCE & ENGINEERING 2025年第1期13卷 434-451页

作者： Zhang, Zichao Zhao, Sanya Li, Yanpin North China Univ Water Resources & Elect Power Engn Training Ctr Zhengzhou Henan Peoples R China North China Univ Water Resources & Elect Power Henan Fluid Machinery Engn Technol Res Ctr Zhengzhou Henan Peoples R China North China Univ Water Resources & Elect Power Coll Energy & Power Engn Zhengzhou Henan Peoples R China

In this article, a multi-objective comprehensive evaluation method is established by comprehensively considering the power and shaft diameter of a multistage hydraulic turbine with an ultrahigh water head and low flow rate to utilize water energy efficiently. Using this method, several schemes for calculating the runner's geometric parameters are attained through the scheme design of different maximum numbers of stages and rotational speeds under different operating conditions of water pressure and flow rate. The reasonable schemes are determined by the maximum value in the intersection of runner diameter value ranges, the blade inlet angle beta 1 >= 12 degrees and the blade inlet flow angle alpha 1 >= 6 degrees. Based on the multi-objective function of water energy utilization considering the comprehensive performance of the runner diameter and power, the design parameters and design stage numbers of the multistage hydraulic turbine with the optimal comprehensive performance of power and shaft diameter are obtained. This method is recommended for the design of ultra-low specific speed multistage hydraulic turbines with a specific speed of less than 50.

关键词： design stage number evaluation method for water-energy-efficient utilization multi-objective function multistage hydraulic turbine runner parameters

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A meta-heuristic approach-aided multi-objective strategy with optimal resource allocation via fault tolerant and priority-based scheduling for load balancing in cloud

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WIRELESS NETWORKS 2025年第3期31卷 2419-2441页

作者： Lokesh, Gudivada Baseer, K. K. Mohan Babu Univ Dept Comp Sci & Engn Tirupati 517102 Andhra Pradesh India VEMU Inst Technol Dept CSE Chittoor 517112 Andhra Pradesh India GITAM GITAM Sch Technol Dept Data Sci Bengaluru 560001 Karnataka India

Cloud computing has been referred to as a successive high-functionality computing sector in the past years for organizations and also individuals. Numerous major previous experiments on the cloud computing sector have existed but there are still specific problems with the distribution of workload in the system of cloud networks. Effective task allocation is complex due to the existence of various Virtual Machines (VMs) and resources. In these approaches, the CSPs must ensure better service delivery functionality, preventing complexities like under or overloaded hosts. These may increase the processing period or result in machine damage. The primary concept of the recommended mechanism is to develop load balancing in the cloud computing sector with optimal resource allocation. With the quick network utilization and also the traffic of data in the cloud sector, the intensity of the computation and the power of processing are improved. In order to decrease the pressure of the network and to enrich the efficacy of the computation the load balancing mechanism is significant. In the starting phase, the scheduling process is executed with the utilization of fault tolerance and a priority-based scheduling process. Then, the optimization of the resources in the scheduling is done with the Modified Random Parameter Dragonfly Algorithm. To further evaluate the load balancing model, the objective function is derived by makespan, average resource utilization, throughput, delay, success rate, and execution time. On the other hand, owing to the dynamic nature of the model, the server (resource) status is varied continuously. Thus, in order to assign the task to the VM resources or server and to efficiently balance the load in the cloud model, the current status of the server is predicted by the Attention-based Bilateral Long Short-term Term Memory (ABi-LSTM) model before resource allocation. From the result analysis, the throughput of the developed model is 95.5, and also the thro

关键词： Cloud computing Scheduling and resource optimization multi-objective function Load balancing Modified random parameter dragonfly algorithm Attention based bilateral long short term memory

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Research on topology optimization of liquid-cooled plates based on multi-level optimization

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2024年 155卷

作者： Xie, Liyao He, Zhaowei Zhao, Yulong Vulin, Domagoj Bhayo, Barkat Ali Hebei Univ Technol Sch Energy & Environm Engn Tianjin 300401 Peoples R China Univ Zagreb Fac Min Geol & Petr Engn Pierottijeva 6 Zagreb 10000 Croatia Lappeenranta Lahti Univ Technol LUT Sch Energy Syst Lappeenranta Finland

This paper employs topology optimization techniques to enhance the performance of liquid-cooled plates while investigating the optimization process and its outcomes. A multilevel optimization strategy is implemented to refine the accuracy and smoothness of the optimization process. The study demonstrates that expanding the range of penalty factors and refining the granularity of penalty factors can effectively enhance the capability of multilevel optimization in suppressing the formation of intermediate densities. Furthermore, a multi-objective function is utilized to strike a balance between the heat transfer efficiency and the hydraulic performance of the liquid-cooled plate. Ultimately, after considering aspects related to heat transfer and hydraulic performance, the research finds that compared to traditional straight-channel liquid-cooled plates, liquid-cooled plates featuring streamlined multi-branched flow channels not only increase the heat transfer area but also reduce pressure drop. As a result, this design improves the temperature uniformity of the liquid-cooled plate and enhances the velocity uniformity of the cooling fluid. At different inlet velocities, the topology-optimized liquidcooled plate exhibits a reduction in both effective thermal resistance and pumping power compared to the traditional straight-channel liquid-cooled plate.

关键词： Topology optimization Liquid-cooled plate multi-level optimization multi-objective function Thermal and hydraulic performance

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An enhanced deep learning-based disease detection model in wireless body area network with energy efficient routing protocol

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WIRELESS NETWORKS 2024年第4期30卷 2961-2986页

作者： Liya, B. S. Krishnamoorthy, R. Arun, S. Easwari Engn Coll Dept Comp Sci & Engn Chennai 600089 Tamil Nadu India Chennai Inst Technol Dept ECE Chennai 600069 Tamil Nadu India Chennai Inst Technol Ctr Adv Wireless Integrated Technol Chennai 600069 Tamil Nadu India Jerusalem Coll Engn Dept ECE Velachery Rd Chennai 600100 Tamil Nadu India

The group of connected small "Bio-sensor nodes (BSNs)" is employed in various parts of the human body that is called "Wireless body area networks (WBAN)". It helps to recognize health-related data and to monitor the readings of blood pressure, "Electro-Cardiogram (ECG)", heartbeat rate, "Electro-Myography (EMG)", and glucose levels in the blood of the human body to know the real-time health. Many applications and research areas use the WBAN, like sports, social welfare, medical field, and entertainment. For WBAN, the major backbone is the BSNs, generally known as "Sensor nodes (SNs)". Based on the small size of the SNs, they have basic resources. High energy is consumed when there is heavy data transmission. When all the energy is drained, that leads to the death of some SN. Routing is the data transfer method from the main source to the sink nodes. The minimum number of SNs is the efficient routing in the data transmission process, resulting in maximum energy consumption. Hence, an energy-efficient routing scheme is implemented with heuristic approaches to conserve more energy in the WBAN. To perform routing effectively, the Cluster Head (CH) needs to be selected initially. In this work, the optimal selection of the CH is carried out using a hybrid Red piranha and egret swarm algorithm (RPESA). Once the CH is optimally selected, the optimal routing is implemented using the RPESA algorithm. The data transmitted using this optimal routing scheme is then utilized for disease diagnosis using an Adaptive dilated cascaded recurrent neural network (ADC-RNN). The parameters in the ADC-RNN technique are optimally selected using the same RPESA algorithm. The classified disease outcome was obtained from ADC-RNN. The suggested heuristic-based energy-efficient routing approach for WBAN and the deep learning-based disease detection model was implemented, and its function was validated by differentiating it with other existing schemes.

关键词： Wireless body area network Energy efficient routing multi-objective function Red piranha and egret swarm algorithm Adaptive dilated cascaded recurrent neural network

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The optimum computational simulation of MHD natural convection for improved cooling efficiency and entropy performance inside Μ-shaped cabinet

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NUMERICAL HEAT TRANSFER PART A-APPLICATIONS 2024年第10期85卷 1633-1652页

作者： Azzawi, Itimad D. J. Al-Damook, Amer Univ Diyala Mech Engn Dept Baqubah Iraq Univ Anbar Renewable Energy Res Ctr Ramadi 31001 Iraq

The application of natural convection heat transfer within a novel Mu-shaped cabinet filled with single-phase pure water/metal foam is investigated numerically. Natural convection is modeled throughout the porous zone using the Local-Thermal-Equilibrium mode and Darcy-ForchheimerBrinkman law. A novel Mu-shaped cabinet with varies Mu ratio (0 <= Mu <= 0.8) and temperature difference (10 K <= Delta T <= 40 K) is applied at a constant porosity of epsilon = 0.85. Furthermore, the current research is conducted to analyze the response surface methodology (RSM) accompanied by a computational simulation for optimizing the multi-objective function of the Mshaped cabinet in terms of two computed responses: maximizing the Nusselt number ratio (NNR) and minimizing the entropy generation ratio (EGR). The optimization study considers the various pore per inch (10 <= PPI <= 50), Darcy number (10(-9) <= Da <= 10-1) and uniform magnetic fields (0 <= Ha <= 100). The results showed that the optimum working conditions consistent with the desired aim are achieved in the maximization of NNR by nearly 26.84 times and the minimization of EGR of 0.895 obtained at Ha = 100, Da = 10(-1) and PPI = 30. Thus, the current investigation is a unique application study of CFD and RSM which provides a helpful reference for the optimum design cooling efficiency and entropy performance of a novel Mu-shaped cabinet.

关键词： MHD natural convection augmentation multi-objective function porous Mu-shaped cabinet response surface methodology (RSM)

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Deep Learning-based Prioritized Packet Classification and Optimal Route Selection in Wireless multimedia Sensor Networks

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IETE JOURNAL OF RESEARCH 2024年第2期70卷 1519-1537页

作者： Chiwariro, Ronald Thangadurai, N. JAIN Deemed be Univ Fac Engn & Technol Dept Comp Sci & Engn Bangalore India Sankalchand Patel Univ Ctr Res & Innovat Dept Informat & Commun Technol Visnagar Gujarat India

Wireless multimedia sensor networks suffer network congestion due to increased traffic leading to data packet loss and increased energy consumption. Thus, it is essential to have a mechanism for priority-based packet classification to improve the performance and decrease the delay in real-time packets. This paper introduces priority-based packet classification using a word embedding mechanism to extract packet semantics and classification using the long short-term memory model that works based on the different characteristics of the packet header to decide the priority of each packet. Furthermore presents a hybrid meta-heuristic algorithm termed butterfly-based rider optimization algorithm, which considers the packet priority and other parameters in optimal route selection. This hybrid meta-heuristic algorithm is developed by merging rider optimization algorithm, and butterfly optimization algorithm. Finally, the experimental results validate the analytical result as well as the performance comparison between the proposed optimal route selection model and the conventional models.

关键词： Butterfly-based rider optimization algorithm Deep learning Hybrid meta-heuristic algorithm LSTM multi-objective function Network congestion Optimal route selection Prioritized packet classification Quality of Service RNN Wireless multimedia sensor networks

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multi-objective reward shaping for global and local trajectory planning of wing-in-ground crafts based on deep reinforcement learning

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AERONAUTICAL JOURNAL 2024年第1320期128卷 371-397页

作者： Hu, H. Li, D. Zhang, G. Zhang, Z. Dalian Univ Technol Sch Naval Architecture Engn State Key Lab Struct Anal Ind Equipment Dalian Peoples R China Beihang Univ Sch Aeronaut Sci & Engn Beijing Peoples R China Collaborat Innovat Ctr Adv Ship & Deep Sea Explora Shanghai Peoples R China

The control of a wing-in-ground craft (WIG) usually allows for many needs, like cruising, speed, survival and stealth. Various degrees of emphasis on these requirements result in different trajectories, but there has not been a way of integrating and quantifying them yet. Moreover, most previous studies on other vehicles' multi-objective trajectory is planned globally, lacking for local planning. For the multi-objective trajectory planning of WIGs, this paper proposes a multi-objective function in a polynomial form, in which each item represents an independent requirement and is adjusted by a linear or exponential weight. It uses the magnitude of weights to demonstrate how much attention is paid relatively to the corresponding demand. Trajectories of a virtual WIG model above the wave trough terrain are planned using reward shaping based on the introduced multi-objective function and deep reinforcement learning (DRL). Two conditions are considered globally and locally: a single scheme of weights is assigned to the whole environment, and two different schemes of weights are assigned to the two parts of the environment. Effectiveness of the multi-object reward function is analysed from the local and global perspectives. The reward function provides WIGs with a universal framework for adjusting the magnitude of weights, to meet different degrees of requirements on cruising, speed, stealth and survival, and helps WIGs guide an expected trajectory in engineering.

关键词： Wing-in-ground craft Trajectory planning multi-objective function Deep reinforcement learning Reward shaping

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Throughput and Outage Probability-Aware Intelligent Swarm-Based multi-Hop Selection in Vehicular Network

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CYBERNETICS AND SYSTEMS 2024年第1期55卷 157-183页

作者： Kiran, Uppula Kumar, Krishan Lovely Profess Univ Dept Elect & Commun Engn Jalandhar Punjab India Lovely Profess Univ Fac Sch Elect & Elect Engn Jalandhar Punjab India

Cooperation is an emerging paradigm for improving spatial differentiation in Vehicular Ad-Hoc Networks (VANETs). Hence, many network solutions are motivated through cooperative communications for boosting VANET efficiency regarding specific network constraints like energy efficiency, network capacity, and outage probability. The main intention of this paper is to design and develop an optimization model for selecting the minimum number of multi-hops between the source and destination for the cooperative VANET networks. The first phase has a first-time slot, where a signal is transmitted by the source to the cooperative nodes (its relays) and their equivalent destination. The main problem considered here is to optimally select the number of hops or relays that are adaptable for communication, to solve the multi-objective functions concerning the target throughput and outage probability. The adoption of new Dimension-based Cat Swarm Optimization (D-CSO) is the main contribution here to optimally select the multi-hops among source and destination. Through the performance evaluation, it is observed that the designed model has achieved networks-wide fairness performance and a good convergence rate.

关键词： Cooperative communication Dimension-based Cat Swarm Optimization multi-hop selection multi-objective function outage probability throughput Vehicular Ad-Hoc Networks

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