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Metaheuristic Resource Allocation Strategy for Cluster Based 6G Industrial Applications

Computers, Materials & Continua 2022年第4期71卷 667-681页

作者： Anwer Mustafa Hilal Lamia Osman Widaa Fahd N.Al-Wesabi Mohammad Medani Manar Ahmed Hamza Mesfer Al Duhayyim Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

The emergence of Beyond 5G(B5G)and 6G networks translated personal and industrial operations highly effective,reliable,and gainful by speeding up the growth of next generation Internet of Things(IoT).Industrial equipment in 6G encompasses a huge number of wireless sensors,responsible for collecting massive quantities of *** the same time,6G network can take real-world intelligent decisions and implement automated equipment *** the inclusion of different technologies into the system increased its energy consumption for which appropriate measures need to be *** has become mandatory for optimal resource allocation in 6G-enabled industrial *** this scenario,the current research paper introduces a new metaheuristic resource allocation strategy for clusterbased 6G industrial applications,named MRAS-CBIA *** technique aims at accomplishing energy efficiency and optimal resource allocation in 6G-enabled industrial *** proposed MRAS-CBIR technique involves three major ***,Weighted Clustering Technique(WCT)is employed to elect the optimal Cluster Heads(CHs)or coordinating agents with the help of three parameters namely,residual energy,distance,and node ***,Decision Tree-based Location Prediction(DTLP)mechanism is applied to determine the exact location of Management Agent(MA).Finally,Fuzzy C-means with Tunicate Swarm Algorithm(FCMTSA)is used for optimal resource allocation in 6G industrial *** performance of the proposed MRAS-CBIA technique was validated and the results were examined under different *** resultant experimental values highlighted the superior performance of MRAS-CBIR technique over existing state-of-the-art methods.

关键词： 6G industrial internet of things energy efficiency resource allocation metaheuristics

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Modeling of Combined Economic and Emission Dispatch Using Improved Sand Cat Optimization Algorithm

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Computers, Materials & Continua 2023年第6期75卷 6145-6160页

作者： Fadwa Alrowais Jaber S.Alzahrani Radwa Marzouk Abdullah Mohamed Gouse Pasha Mohammed Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Combined Economic and Emission Dispatch(CEED)task forms multi-objective optimization problems to be resolved to minimize emission and fuel *** disadvantage of the conventional method is its incapability to avoid falling in local optimal,particularly when handling nonlinear and complex *** have recently received considerable attention due to their enhanced capacity to prevent local optimal solutions in addressing all the optimization problems as a black ***,this paper focuses on the design of an improved sand cat optimization algorithm based CEED(ISCOA-CEED)*** ISCOA-CEED technique majorly concen-trates on reducing fuel costs and the emission of generation ***,the presented ISCOA-CEED technique transforms the equality constraints of the CEED issue into inequality ***,the improved sand cat optimization algorithm(ISCOA)is derived from the integration of tra-ditional SCOA with the Levy Flight(LF)*** last,the ISCOA-CEED technique is applied to solve a series of 6 and 11 generators in the CEED *** experimental validation of the ISCOA-CEED technique ensured the enhanced performance of the presented ISCOA-CEED technique over other recent approaches.

关键词： Economic and emission dispatch multi-objective optimization metaheuristics fuel cost minimization sand cat optimization

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Sea Turtle Foraging Optimization-Based Controller Placement with Blockchain-Assisted Intrusion Detection in Software-Defined Networks

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Computers, Materials & Continua 2023年第6期75卷 4735-4752页

作者： Sultan Alkhliwi Department of Computer Science Faculty of ScienceNorthern Border UniversityArarSaudi Arabia

Software-defined networking(SDN)algorithms are gaining increas-ing interest and are making networks flexible and *** basic idea of SDN is to move the control planes to more than one server’s named controllers and limit the data planes to numerous sending network components,enabling flexible and dynamic network management.A distinctive characteristic of SDN is that it can logically centralize the control plane by utilizing many physical *** deployment of the controller—that is,the controller placement problem(CPP)—becomes a vital model *** the advancements of blockchain technology,data integrity between nodes can be enhanced with no requirement for a trusted third *** the lat-est developments in blockchain technology,this article designs a novel sea turtle foraging optimization algorithm for the controller placement problem(STFOA-CPP)with blockchain-based intrusion detection in an SDN *** major intention of the STFOA-CPP technique is the maximization of lifetime,network connectivity,and load balancing with the minimization of *** addition,the STFOA-CPP technique is based on the sea turtles’food-searching characteristics of tracking the odour path of dimethyl sulphide(DMS)released from food ***,the presented STFOA-CPP technique can adapt with the controller’s count mandated and the shift to controller mapping to variable network ***,the blockchain can inspect the data integrity,determine significantly malicious input,and improve the robust nature of developing a trust relationship between sev-eral nodes in the *** demonstrate the improved performance of the STFOA-CPP algorithm,a wide-ranging experimental analysis was carried *** extensive comparison study highlighted the improved outcomes of the STFOA-CPP technique over other recent approaches.

关键词： Software-defined networking NP hard problem metaheuristics controller placement problem objective function

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An Effective Signcryption with Optimization Algorithm for IoT-enabled Secure Data Transmission

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Computers, Materials & Continua 2022年第11期73卷 4017-4031页

作者： A.Chinnappa C.Vijayakumaran Department of Computing Technologies School of ComputingSRM Institute of Science and TechnologyKattankulathur603203TamilnaduIndia

Internet of Things(IoT)allows several low resources and controlled devices to interconnect,calculate processes and make decisions in the communication *** the heterogeneous environment for IoT devices,several challenging issues such as energy,storage,efficiency,and *** design of encryption techniques enables the transmission of the data in the IoT environment in a secured *** proper selection of optimal keys helps to boost the encryption *** this motivation,the study presents a signcryption with quantum chaotic krill herd algorithm for secured data transmission(SCQCKH-SDT)in IoT *** proposed SCQCKHSDT technique aims to effectively encrypts the data by the use of optimal keys generated by the CQKH *** proposed SCQCKH-SDT technique initially employs the signcryption technique for the encryption of *** order to optimize the secrecy,the optimal key generation process is carried out using Chaotic Krill Herd(CQKH)*** CQKH algorithm incorporates the concept of quantum computing and chaotic theory into the traditional KH *** performance validation of the SCQCKH-SDT technique is performed using benchmark *** extensive comparative analysis reported the superior performance of the SCQCKH-SDT technique over the recent approaches.

关键词： Security Internet of Things encryption optimal key generation metaheuristics

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Binary Fruit Fly Swarm Algorithms for the Set Covering Problem

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Computers, Materials & Continua 2022年第6期71卷 4295-4318页

作者： Broderick Crawford Ricardo Soto Hanns de la Fuente Mella Claudio Elortegui Wenceslao Palma Claudio Torres-Rojas Claudia Vasconcellos-Gaete Marcelo Becerra Javier Pena Sanjay Misra Pontificia Universidad Católica de Valparaíso Valparaíso2362807Chile LERIA Universitéd’AngersAngers49000France Department of Computer Science and Communication Ostfold University CollegeHaldenNorway

Currently,the industry is experiencing an exponential increase in dealing with binary-based combinatorial *** this sense,metaheuristics have been a common trend in the field in order to design approaches to solve them ***,a well-known strategy consists in the use of algorithms based on discrete swarms transformed to perform in binary *** the No Free Lunch theorem,we are interested in testing the performance of the Fruit Fly Algorithm,this is a bio-inspired metaheuristic for deducing global optimization in continuous spaces,based on the foraging behavior of the fruit fly,which usually has much better sensory perception of smell and vision than any other *** the other hand,the Set Coverage Problem is a well-known NP-hard problem with many practical applications,including production line balancing,utility installation,and crew scheduling in railroad and mass transit *** this paper,we propose different binarization methods for the Fruit Fly Algorithm,using Sshaped and V-shaped transfer functions and various discretization methods to make the algorithm work in a binary search *** are motivated with this approach,because in this way we can deliver to future researchers interested in this area,a way to be able to work with continuous metaheuristics in binary *** new approach was tested on benchmark instances of the Set Coverage Problem and the computational results show that the proposed algorithm is robust enough to produce good results with low computational cost.

关键词： Set covering problem fruit fly swarm algorithm metaheuristics binarization methods combinatorial optimization problem

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Intelligent Deep Learning Enabled Wild Forest Fire Detection System

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Computer Systems Science & Engineering 2023年第2期44卷 1485-1498页

作者： Ahmed S.Almasoud Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia

The latest advancements in computer vision and deep learning(DL)techniques pave the way to design novel tools for the detection and monitoring of forestﬁ*** this view,this paper presents an intelligent wild forestﬁre detec-tion and alarming system using deep learning(IWFFDA-DL)*** pro-posed IWFFDA-DL technique aims to identify forestﬁres at earlier stages through integrated *** proposed IWFFDA-DL system includes an Inte-grated sensor system(ISS)combining an array of sensors that acts as the major input source that helps to forecast theﬁ***,the attention based convolution neural network with bidirectional long short term memory(ACNN-BLSTM)model is applied to examine and identify the existence of *** hyperpara-meter tuning of the ACNN-BLSTM model,the bacterial foraging optimization(BFO)algorithm is employed and thereby enhances the detection ***,when theﬁre is detected,the Global System for Mobiles(GSM)modem transmits messages to the authorities to take required *** extensive set of simulations were performed and the results are investigated interms of several *** obtained results highlight the betterment of the IWFFDA-DL techni-que interms of various measures.

关键词： Forestﬁre deep learning intelligent models metaheuristics integrated sensor system hyperparameter tuning

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Deep Learning Enabled Computer Aided Diagnosis Model for Lung Cancer using Biomedical CT Images

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Computers, Materials & Continua 2022年第10期73卷 1437-1448页

作者： Mohammad Alamgeer Hanan Abdullah Mengash Radwa Marzouk Mohamed K Nour Anwer Mustafa Hilal Abdelwahed Motwakel Abu Sarwar Zamani Mohammed Rizwanullah Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Early detection of lung cancer can help for improving the survival rate of the *** imaging tools such as computed tomography(CT)image was utilized to the proper identification and positioning of lung *** recently developed deep learning(DL)models can be employed for the effectual identification and classification of *** article introduces novel deep learning enabled CAD technique for lung cancer using biomedical CT image,named DLCADLC-BCT *** proposed DLCADLC-BCT technique intends for detecting and classifying lung cancer using CT *** proposed DLCADLC-BCT technique initially uses gray level co-occurrence matrix(GLCM)model for feature ***,long short term memory(LSTM)model was applied for classifying the existence of lung cancer in the CT ***,moth swarm optimization(MSO)algorithm is employed to optimally choose the hyperparameters of the LSTM model such as learning rate,batch size,and epoch *** demonstrating the improved classifier results of the DLCADLC-BCT approach,a set of simulations were executed on benchmark dataset and the outcomes exhibited the supremacy of the DLCADLC-BCT technique over the recent approaches.

关键词： Biomedical images lung cancer deep learning machine learning metaheuristics hyperparameter tuning

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Energy Efficient QoS Aware Cluster Based Multihop Routing Protocol for WSN

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Computer Systems Science & Engineering 2022年第6期41卷 1173-1189页

作者： M.S.Maharajan T.Abirami Department of Computer Science and Engineering GRT Institute of Engineering and TechnologyTiruttani631209India Department of Information Technology Kongu Engineering CollegeErode638060India

Wireless sensor networks (WSN) have become a hot research areaowing to the unique characteristics and applicability in diverse application *** and routing techniques can be considered as an NP hard optimizationproblem, which can be addressed by metaheuristic optimization algorithms. Withthis motivation, this study presents a chaotic sandpiper optimization algorithmbased clustering with groundwater flow optimization based routing technique(CSPOC-GFLR). The goal of the CSOC-GFLR technique is to cluster the sensornodes in WSN and elect an optimal set of routes with an intention of achievingenergy efficiency and maximizing network lifetime. The CSPOC algorithm isderived by incorporating the concepts of chaos theory to boost the global optimization capability of the SPOC algorithm. The CSPOC technique elects an optimum set of cluster heads (CH) whereas the other sensors are allocated to thenearer CH. Extensive experimentation portrayed the promising performance ofthe CSPOC-GFLR technique by achieving reduced energy utilization, improvedlifetime, and prolonged stability over the existing techniques.

关键词： Clustering routing wireless sensor networks energy efficiency network lifetime metaheuristics

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Artificial Intelligence Based Sentiment Analysis for Health Crisis Management in Smart Cities

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Computers, Materials & Continua 2022年第4期71卷 143-157页

作者： Anwer Mustafa Hilal Badria Sulaiman Alfurhood Fahd N.Al-Wesabi Manar Ahmed Hamza Mesfer Al Duhayyim Huda G.Iskandar Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Natural and Applied Sciences College of Community-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaMalaysia

Smart city promotes the unification of conventional urban infrastructure and information technology (IT) to improve the quality of living andsustainable urban services in the city. To accomplish this, smart cities necessitate collaboration among the public as well as private sectors to install ITplatforms to collect and examine massive quantities of data. At the same time,it is essential to design effective artificial intelligence (AI) based tools to handlehealthcare crisis situations in smart cities. To offer proficient services to peopleduring healthcare crisis time, the authorities need to look closer towardsthem. Sentiment analysis (SA) in social networking can provide valuableinformation regarding public opinion towards government actions. With thismotivation, this paper presents a new AI based SA tool for healthcare crisismanagement (AISA-HCM) in smart cities. The AISA-HCM technique aimsto determine the emotions of the people during the healthcare crisis time, suchas COVID-19. The proposed AISA-HCM technique involves distinct operations such as pre-processing, feature extraction, and classification. Besides,brain storm optimization (BSO) with deep belief network (DBN), called BSODBN model is employed for feature extraction. Moreover, beetle antennasearch with extreme learning machine (BAS-ELM) method was utilized forclassifying the sentiments as to various classes. The use of BSO and BASalgorithms helps to effectively modify the parameters involved in the DBNand ELM models respectively. The performance validation of the AISA-HCMtechnique takes place using Twitter data and the outcomes are examinedwith respect to various measures. The experimental outcomes highlighted theenhanced performance of the AISA-HCM technique over the recent state ofart SA approaches with the maximum precision of 0.89, recall of 0.88, Fmeasure of 0.89, and accuracy of 0.94.

关键词： Smart city sentiment analysis artificial intelligence healthcare management metaheuristics deep learning parameter tuning

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Modified Harris Hawks Optimization Based Test Case Prioritization for Software Testing

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Computers, Materials & Continua 2022年第7期72卷 1951-1965页

作者： Manar Ahmed Hamza Abdelzahir Abdelmaboud Souad Larabi-Marie-Sainte Haya Mesfer Alshahrani Mesfer Al Duhayyim Hamza Awad Ibrahim Mohammed Rizwanullah Ishfaq Yaseen Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Department of Information Systems College of Science and ArtsKing Khalid UniversityMahayil Asir62529Saudi Arabia Department of Computer Science College of Computer and Information SciencesPrince Sultan UniversityP.O.Box No.66833Rafha StreetRiyadh11586Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz University16278Saudi Arabia College of Computer at Al-Gunfudah Umm Al-Qura UniversityAl-Gunfudah24382Saudi Arabia

Generally,software testing is considered as a proficient technique to achieve improvement in quality and reliability of the ***,the quality of test cases has a considerable influence on fault revealing capability of software testing *** Case Prioritization(TCP)remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected(APFD)and time spent upon execution *** ismainly intended to design a collection of test cases that can accomplish early optimization using preferred *** studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection rate during software *** this aspect,the current study designs aModified Harris Hawks Optimization based TCP(MHHO-TCP)technique for software *** aim of the proposed MHHO-TCP technique is to maximize APFD and minimize the overall execution *** addition,MHHO algorithm is designed to boost the exploration and exploitation abilities of conventional HHO *** order to validate the enhanced efficiency of MHHO-TCP technique,a wide range of simulations was conducted on different benchmark programs and the results were examined under several *** experimental outcomes highlight the improved efficiency of MHHO-TCP technique over recent approaches under different measures.

关键词： Software testing harris hawks optimization test case prioritization apfd execution time metaheuristics

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