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Routing with Cooperative Nodes Using Improved Learning Approaches

Intelligent Automation & Soft Computing 2023年第3期35卷 2857-2874页

作者： R.Raja N.Satheesh J.Britto Dennis C.Raghavendra department of csit CVR College of EngineeringTelanganaIndia department of Computer Science and Engineering St.Martin’s Engineering CollegeSecunderabadTelanganaIndia department of Computer Science and Engineering Dhanalakshmi Srinivasan UniversityTrichyTamilnaduIndia csit department CVR College of EngineeringHyderabadIndia

In IoT,routing among the cooperative nodes plays an incredible role in fulﬁlling the network requirements and enhancing system performance.The eva-luation of optimal routing and related routing parameters over the deployed net-work environment is challenging.This research concentrates on modelling a memory-based routing model with Stacked Long Short Term Memory(s-LSTM)and Bi-directional Long Short Term Memory(b-LSTM).It is used to hold the routing information and random routing to attain superior performance.The pro-posed model is trained based on the searching and detection mechanisms to com-pute the packet delivery ratio(PDR),end-to-end(E2E)delay,throughput,etc.The anticipated s-LSTM and b-LSTM model intends to ensure Quality of Service(QoS)even in changing network topology.The performance of the proposed b-LSTM and s-LSTM is measured by comparing the signiﬁcance of the model with various prevailing approaches.Sometimes,the performance is measured with Mean Absolute Error(MAE)and Root Mean Square Error(RMSE)for mea-suring the error rate of the model.The prediction of error rate is made with Learn-ing-based Stochastic Gradient Descent(L-SGD).This gradual gradient descent intends to predict the maximal or minimal error through successive iterations.The simulation is performed in a MATLAB 2020a environment,and the model performance is evaluated with diverse approaches.The anticipated model intends to give superior performance in contrast to prevailing approaches.

关键词： Internet of Things(IoT) stacked long short term memory bi-directional long short term memory error rate stochastic gradient descent

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A Novel Metaheuristic Algorithm: The Team Competition and Cooperation Optimization Algorithm

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Computers, Materials & Continua 2022年第11期73卷 2879-2896页

作者： Tao Wu Xinyu Wu Jingjue Chen Xi Chen Amir Homayoon Ashrafzadeh School of Computer Science Chengdu University of Information TechnologyChengdu610225China School of Computer Science and Engineering Southwest Minzu UniversityChengdu610041China csit department School of ScienceRMIT UniversityMelbourne3058Australia

Metaheuristic algorithm is a generalization of heuristic algorithm that can be applied to almost all optimization problems.For optimization problems,metaheuristic algorithm is one of the methods to find its optimal solution or approximate solution under limited conditions.Most of the existing metaheuristic algorithms are designed for serial systems.Meanwhile,existing algorithms still have a lot of room for improvement in convergence speed,robustness,and performance.To address these issues,this paper proposes an easily parallelizable metaheuristic optimization algorithm called team competition and cooperation optimization(TCCO)inspired by the process of human team cooperation and competition.The proposed algorithm attempts to mathematically model human team cooperation and competition to promote the optimization process and find an approximate solution as close as possible to the optimal solution under limited conditions.In order to evaluate the performance of the proposed algorithm,this paper compares the solution accuracy and convergence speed of the TCCO algorithm with the Grasshopper Optimization Algorithm(GOA),Seagull Optimization Algorithm(SOA),Whale Optimization Algorithm(WOA)and Sparrow Search Algorithm(SSA).Experiment results of 30 test functions commonly used in the optimization field indicate that,compared with these current advanced metaheuristic algorithms,TCCO has strong competitiveness in both solution accuracy and convergence speed.

关键词： Optimization metaheuristic algorithm

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An Efficient Color-Image Encryption Method Using DNA Sequence and Chaos Cipher

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Computers, Materials & Continua 2023年第5期75卷 2641-2654页

作者： Ghofran Kh.Shraida Hameed A.Younis Taief Alaa Al-Amiedy Mohammed Anbar Hussain A.Younis Iznan H.Hasbullah department of Computer Science College of CSITUniversity of BasrahBasrahIraq National Advanced IPv6(NAv6)Centre Universiti Sains MalaysiaPenang11800Malaysia College of Education for Women University of Basrah BasrahIraq School of Computer Sciences Universiti Sains MalaysiaMindenPenang11800Malaysia

Nowadays,high-resolution images pose several challenges in the context of image encryption.The encryption of huge images’file sizes requires high computational resources.Traditional encryption techniques like,Data Encryption Standard(DES),and Advanced Encryption Standard(AES)are not only inefficient,but also less secure.Due to characteristics of chaos theory,such as periodicity,sensitivity to initial conditions and control parameters,and unpredictability.Hence,the characteristics of deoxyribonucleic acid(DNA),such as vast parallelism and large storage capacity,make it a promising field.This paper presents an efficient color image encryption method utilizing DNA encoding with two types of hyper-chaotic maps.The proposed encryption method comprises three steps.The first step initializes the conditions for generating Lorenz and Rossler hyper-chaotic maps using a plain image Secure Hash Algorithm(SHA-256/384).The second step performs a confusion procedure by scrambling the three components of the image(red,green,and blue)using Lorenz hyper-chaotic sequences.Finally,the third step combines three approaches to encrypt the scrambled components for diffusion:DNA encoding/decoding,addition operation between components,and XORing with Rossler hyper-chaotic sequences.The simulation results indicate that the suggested encryption algorithm satisfies the requirements of security.The entropy value of confusion and diffusion is 7.997,the key space is 2200,and the correlation coefficient is nearly zero.The efficacy of the proposed method has been verified through numerous evaluations,and the results show its resistance and effectiveness against several attacks,like statistical and brute-force attacks.Finally,the devised algorithm vanquishes other relevant color image encryption algorithms.

关键词： Color image encryption DNA encoding lorenz system rossler system SHA-2

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Crowdsourcing-Based Framework for Teaching Quality Evaluation and Feedback Using Linguistic 2-Tuple

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Computers, Materials & Continua 2018年第10期57卷 81-96页

作者： Tiejun Wang Tao Wu Amir Homayoon Ashrafzadeh Jia He department of Computer Science Chengdu University of Information and TechnologyChengdu610025China. csit department School of ScienceRMIT UniversityMelbourne3058Australia.

Crowdsourcing is widely used in various fields to collect goods and services from large participants.Evaluating teaching quality by collecting feedback from experts or students after class is not only delayed but also not accurate.In this paper,we present a crowdsourcing-based framework to evaluate teaching quality in the classroom using a weighted average operator to aggregate information from students’questionnaires described by linguistic 2-tuple terms.Then we define crowd grade based on similarity degree to distinguish contribution from different students and minimize the abnormal students’impact on the evaluation.The crowd grade would be updated at the end of each feedback so it can guarantee the evaluation accurately.Moreover,a simulated case is shown to illustrate how to apply this framework to assess teaching quality in the classroom.Finally,we developed a prototype and carried out some experiments on a series of real questionnaires and two sets of modified data.The results show that teachers can locate the weak points of teaching and furthermore to identify the abnormal students to improve the teaching quality.Meanwhile,our approach provides a strong tolerance for the abnormal student to make the evaluation more accurate.

关键词： Teaching quality evaluation crowdsourcing linguistic 2-tuple group decision making

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Multi-Criteria Fuzzy-Based Decision Making Algorithm to Optimize the VHO Performance in Hetnets

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Computers, Materials & Continua 2022年第1期70卷 323-341页

作者： A.Prithiviraj A.Maheswari D.Balamurugan Vinayakumar Ravi Moez Krichen Roobaea Alroobaea Saeed Rubaiee Sankar Sennan department of CSE Sona College of TechnologySalem636005India department of CSE Dr.M.G.R.Educational and Research InstituteChennai600095India Center for Artificial Intelligence PrinceMohammad Bin Fahd UniversityKhobarSaudi Arabia Faculty of csit Al-Baha UniversitySaudi Arabia ReDCAD laboratory University of SfaxTunisia department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia department of Industrial and Systems Engineering College of EngineeringUniversity of JeddahJaddahSaudi Arabia

Despite the seemingly exponential growth of mobile and wireless communication,this same technology aims to offer uninterrupted access to different wireless systems like Radio Communication,Bluetooth,and Wi-Fi to achieve better network connection which in turn gives the best quality of service(QoS).Many analysts have established many handover decision systems(HDS)to enable assured continuous mobility between various radio access technologies.Unbrokenmobility is one of themost significant problems considered in wireless communication networks.Each application needs a distinct QoS,so the network choice may shift appropriately.To achieve this objective and to choose the finest networks,it is important to select a best decision making algorithm that chooses the most effective network for every application that the user requires,dependent on QoS measures.Therefore,the main goal of the proposed system is to provide an enhanced vertical handover(VHO)decision making programby using aMulti-CriteriaFuzzy-Based algorithm to choose the best network.Enhanced Multi-Criteria algorithms and a Fuzzy-Based algorithm is implemented successfully for optimal network selection and also to minimize the probability of false handover.Furthermore,a double packet buffer is utilized to decrease the packet loss by 1.5%and to reduce the number of handovers up to 50%compared to the existing systems.In addition,the network setup has an optimized mobilitymanagement system to supervise the movement of the mobile nodes.

关键词： Vertical handover mobility management handover decision systems multi-criteria fuzzy logic QoS false handover

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Pan evaporation modeling in different agroclimatic zones using functional link artificial neural network

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Information Processing in Agriculture 2021年第1期8卷 134-147页

作者： Babita Majhi Diwakar Naidu department of csit Guru Ghasidas VishwavidyalayaCentral UniversityBilaspur 495009India BRSM College of Agricultural Engineering and Technology and Research Station Indira Gandhi Krishi VishwavidyalayaMungeliIndia

Pan evaporation is an important climatic variable for developing efficient water resource management strategies.In the past,many machine learning models are reported in the literature for pan evaporation modeling using the different combinationof available climatic variables.In order to develop a novel model with improved accuracy and reduced computational complexity,the functional link artificial neural network(FLANN)is chosen as an architecture to estimate daily pan evaporation in three agro-climatic zones(ACZs)of Chhattisgarh state in east-central India.Single neuron and single layer in its structure make it less complex as compared to other multilayer neural networks and neuro-fuzzy based hybrid models.Estimation results obtained with the FLANN model are compared with those obtained by multi-layer artificial neural networks(MLANN)and two empirical methods using the same raw data and corresponding features.Statistical indices like root mean square error(RMSE),mean absolute error(MAE)and efficiency factor(EF)is also computed to evaluate the model performance.It is demonstrated that pan evaporation estimates obtained with the proposed FLANN models provide an improved estimation of pan evaporation(RMSE=0.85 to 1.27 mm d^(-1),MAE=0.63 to 0.95 mm d^(-1) and EF=0.70 to 0.89)as compared to MLANN(RMSE=0.94 to 1.58 mm d^(-1),MAE=0.73 to 1.14 mm d^(-1) and EF=0.62 to 0.88)and empirical(RMSE=1.19 to 2.19 mm d^(-1),MAE=0.91 to 1.62 mm d^(-1) and EF=0.49 to 0.88)models in different ACZs.

关键词： Low complexity Pan evaporation estimation Functional link artificial neural network model Multi-layer artificial neural network model Empirical models

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Processing of 5083 Aluminum Alloy Reinforced with Alumina through Microwave Sintering

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Journal of Minerals and Materials Characterization and Engineering 2012年第11期11卷 1126-1131页

作者： Jagesvar Verma Anil Kumar Rituraj Chandrakar Rajesh Kumar department in Mechatronics Engineering at csit Durg India department of Mechanical Engineering at BIT Durg India department of Mechanical Engineering at csit Durg India department of Mechanical Engineering at SSIPMT Raipur India

Today, there is an increasing demand worldwide for the advanced materials in order to obtain the desired properties. This is because a single material generally cannot meet the requirement of harsh engineering environment that is why the need for composites arises. Metal matrix composite is an important class of materials with high potential for structural applications requiring high specific modulus, strength and toughness. Metal matrix composites with unique properties are growing every day and widely used in different industries because of their high mechanical properties and wear resistance.

关键词： Microstructure Powder Metallurgy Composite Materials

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A Novel Quantum-Behaved Particle Swarm Optimization Algorithm

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Computers, Materials & Continua 2020年第5期63卷 873-890页

作者： Tao Wu Lei Xie Xi Chen Amir Homayoon Ashrafzadeh Shu Zhang School of Computer Science Chengdu University of Information TechnologyChengdu610225China School of Computer Science and Technology Southwest Minzu UniversityChengdu610041China csit department School of ScienceRMIT UniversityMelbourne3058Australia department of Emergency Medicine West China HospitalSichuan UniversityChengdu610041China

The efficient management of ambulance routing for emergency requests is vital to save lives when a disaster occurs.Quantum-behaved Particle Swarm Optimization(QPSO)algorithm is a kind of metaheuristic algorithms applied to deal with the problem of scheduling.This paper analyzed the motion pattern of particles in a square potential well,given the position equation of the particles by solving the Schrödinger equation and proposed the Binary Correlation QPSO Algorithm Based on Square Potential Well(BC-QSPSO).In this novel algorithm,the intrinsic cognitive link between particles’experience information and group sharing information was created by using normal Copula function.After that,the control parameters chosen strategy gives through experiments.Finally,the simulation results of the test functions show that the improved algorithms outperform the original QPSO algorithm and due to the error gradient information will not be over utilized in square potential well,the particles are easy to jump out of the local optimum,the BC-QSPSO is more suitable to solve the functions with correlative variables.

关键词： Ambulance routing problem quantum-behaved particle swarm optimization square potential well convergence

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Design and implementation of Ad-Hoc collaborative proxying scheme for reducing network energy waste

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Digital Communications and Networks 2017年第2期3卷 118-128页

作者： Rafiullah Khan Sarmad Ullah Khan School of Electronics Electrical Engineering and Computer Science Queen's University Belfast ECIT/CSIT- Northern Ireland Science Park Queen's RoadQueen's lsland Belfast BT3 9DT United Kingdom Electrical Engineering department CECOS University of IT and Emerging Sciences Phase-6 Hayatabad Peshawar Pakistan

Network devices are equipped with low power states but they are rarely activated due to their inability of maintaining network connectivity. Recently, Network Connectivity Proxy (NCP) concept has been proposed in literature as an effective mechanism to exploit full potential of low power features on network devices by impersonating their virtual presence. However, the NCP concept faces several open issues and challenges especially related to proxying of TCP connections and majority of daily used proprietary closed-source applications. This paper presents a new approach for reducing network energy waste through intelligent collaboration among daily used devices (e.g., desktop computers, laptops, tablets, smartphones, etc). It guarantees to run applications on only and only one user device that is under active use at that specific moment. To reduce energy waste and allow idle devices to sleep, our approach also takes benefit from a light-weight home gateway proxy with very basic practically realizable functionalities. The proposed system not just reduces energy waste of fixed devices but also enables mobile devices to significantly improve their battery life. Our developed software prototypes allow devices to autonomously and seamlessly collaborate with each other without requiring any configuration or user input. Further, this paper also presents the basic performance evaluation of developed prototypes in real networking environments.

关键词： Green networking Energy efficiency Smartphone Home gateway proxy Power measurement Universal Plug & Play

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Analytical Comparison of Resource Search Algorithms in Non-DHT Mobile Peer-to-Peer Networks

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Computers, Materials & Continua 2021年第7期68卷 983-1001页

作者： Ajay Arunachalam Vinayakumar Ravi Moez Krichen Roobaea Alroobaea Jehad Saad Alqurni Centre for Applied Autonomous Sensor Systems(AASS) Örebro UniversityÖrebroSweden Center for Articial Intelligence Prince Mohammad Bin Fahd UniversityKhobarSaudi Arabia Faculty of csit Al-Baha UniversitySaudi Arabia ReDCAD LaboratoryUniversity of SfaxTunisia department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia department of Education Technologies College of EducationImam Abdulrahman Bin Faisal UniversitySaudi Arabia

One of the key challenges in ad-hoc networks is the resource discovery problem.How efciently&quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying question?Broadcasting is a basic technique in the Mobile Ad-hoc Networks(MANETs),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive ooding technique oods the network with query messages,while the random walk scheme operates by contacting subsets of each node’s neighbors at every step,thereby restricting the search space.Many earlier works have mainly focused on the simulation-based analysis of ooding technique,and its variants,in a wired network scenario.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of mobile P2P networks.In this article,we mathematically model different widely used existing search techniques,and compare with the proposed improved random walk method,a simple lightweight approach suitable for the non-DHT architecture.We provide analytical expressions to measure the performance of the different ooding-based search techniques,and our proposed technique.We analytically derive 3 relevant key performance measures,i.e.,the avg.number of steps needed to nd a resource,the probability of locating a resource,and the avg.number of messages generated during the entire search process.

关键词： Mathematical model MANET P2P networks P2P MANET unstructured search algorithms Peer-to-Peer ad-hoc ooding random walk resource discovery content discovery mobile peer-to-peer broadcast peer

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