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ATS:A Novel Time-Sharing CPU Scheduling Algorithm Based on Features Similarities

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Computers, materials & Continua 2022年第3期70卷 6271-6288页

作者： samih m.mostafa Sahar Ahmed Idris manjit Kaur Faculty of Computers and Information South Valley UniversityQena83523Egypt College of Industrial Engineering King Khalid UniversityAbhaSaudi Arabia School of Engineering and Applied Sciences Bennett UniversityGreater NoidaIndia

minimizing time cost in time-shared operating systems is considered basic and essential task,and it is the most significant goal for the researchers who interested in CPU scheduling *** time,turnaround time,and number of context switches are themost time cost criteria used to compare between CPU scheduling *** scheduling algorithms are divided into non-preemptive and ***(RR)algorithm is the most famous as it is the basis for all the algorithms used in *** this paper,the authors proposed a novel CPU scheduling algorithm based on *** proposed algorithm is called Adjustable Time Slice(ATS).It reduces the time cost by taking the advantage of the low overhead of RR *** addition,ATS favors short processes allowing them to run longer time than given to long *** specific characteristics of each process are;its CPU execution time,weight,time slice,and number of context *** clusters the processes in groups depending on these *** traditionalRRassigns fixed time slice for each *** the other hand,dynamic variants of RR assign time slice for each process differs from other *** essential difference between ATS and the other methods is that it gives a set of processes a specific time based on their similarities within the same *** authors compared between ATS with five popular scheduling algorithms on nine datasets of *** datasets used in the comparison vary in their *** evaluation was measured in term of time cost and the experiments showed that the proposed algorithm reduces the time cost.

关键词： Clustering CPU scheduling round robin average turnaround time average waiting time

A Perfect Knob to Scale Thread Pool on Runtime

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Computers, materials & Continua 2022年第7期72卷 1483-1493页

作者： Faisal Bahadur Arif Iqbal Umar Insaf Ullah Fahad Algarni muhammad Asghar Khan samih m.mostafa Department of Information Technology Hazara UniversityMansehra21300Pakistan Hamdard Institute of Engineering and Technology Islamabad CampusPakistan College of Computing and Information Technology The University of BishaBishaSaudi Arabia Faculty of Computers and Information South Valley UniversityQena83523Egypt

Scalability is one of the utmost nonfunctional requirement of server applications,because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable *** order to achieve scalability,thread pool system(TPS)has been used extensively as a middleware service in server *** size of thread pool is the most significant factor,that affects the overall performance of *** the optimal size of thread pool dynamically on runtime is a challenging *** most widely used and simple method to tackle this problem is to keep the size of thread pool equal to the request rate,i.e.,the frequencyoriented thread pool(FOTP).The FOTPs are the most widely used TPSs in the industry,because of the implementation simplicity,the negligible overhead and the capability to use in any ***,the frequency-based schemes only focused on one aspect of changes in the load,and that is the fluctuations in request *** request rate alone is an imperfect knob to scale thread ***,this paper presents a workload profiling based FOTP,that focuses on request size(service time of request)besides the request rate as a knob to scale thread pool on runtime,because we argue that the combination of both truly represents the load fluctuation in server-side *** evaluated the results of the proposed system against state of the art TPS of Oracle Corporation(by a client-server-based simulator)and concluded that our system outperformed in terms of both;the response times and throughput.

关键词： Scalability performance middleware workload profiling multithreading thread pool

An Optimal Framework for SDN Based on Deep Neural Network

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Computers, materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano samih m.mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

milestones of Wireless Communication Networks and Technology Prospect of Next Generation(6G)

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Computers, materials & Continua 2022年第6期71卷 4803-4818页

作者： mohammed H.Alsharif md.Sanwar Hossain Abu Jahid muhammad Asghar Khan Bong Jun Choi samih m.mostafa Department of Electrical Engineering College of Electronics and Information EngineeringSejong University209 Neungdong-roGwangjin-guSeoul05006Korea Department of Electrical and Electronic Engineering Bangladesh University of Business and TechnologyDhaka1216Bangladesh Department of Electrical&Computer Engineering University of OttawaOttawaON K1N 6N5Canada Department of Electrical Engineering Hamdard University KarachiIslamabad CampusIslamabad44000Pakistan School of Computer Science and Engineering&School of Electronic Engineering Soongsil UniversitySeoulKorea Faculty of Computers and Information South Valley UniversityQena83523Egypt Academy of Scientific Research and Technology Cairo11516Egypt

Since around 1980,a new generation of wireless technology has arisen approximately every 10 ***-generation(1G)and secondgeneration(2G)began with voice and eventually introduced more and more data in third-generation(3G)and became highly popular in the fourthgeneration(4G).To increase the data rate along with low latency and mass connectivity the fifth-generation(5G)networks are being installed from ***,the 5G technology will not be able to fulfill the data demand at the end of this ***,it is expected that 6G communication networks will rise,providing better services through the implementation of new enabling technologies and allowing users to connect everywhere.6G technology would not be confined to cellular communications networks,but would also comply with non-terrestrial communication system requirements,such as satellite *** ultimate objectives of this work are to address the major challenges of the evolution of cellular communication networks and to discourse the recent growth of the industry based on the key scopes of application and *** main areas of research topics are summarized into(i)major 6G wireless networkmilestones;(ii)key performance indicators;(iii)future new applications;and(iv)potential fields of research,challenges,and open issues.

关键词： Wireless networks beyond 5G 6G communications terahertz frequency terahertz communications holographic calls

mEC-IoT-Healthcare: Analysis and Prospects

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Computers, materials & Continua 2023年第6期75卷 6219-6250页

作者： Hongyuan Wang mohammed Dauwed Imran Khan Nor Samsiah Sani Hasmila Amirah Omar Hirofumi Amano samih m.mostafa College of Computer Science Guangdong University of Science and TechnologyDongGuan523083China Department of medical Instrumentation Techniques Engineering Dijlah University CollegeBaghdadIraq Department of Electrical Engineering University of Engineering&TechnologyPeshawar814Pakistan Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia43600BangiSelangorMalaysia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Physical sensors,intelligent sensors,and output recommenda-tions are all examples of smart health technology that can be used to monitor patients’health and change their *** health is an Internet-of-Things(IoT)-aware network and sensing infrastructure that provides real-time,intelligent,and ubiquitous healthcare *** of the rapid development of cloud computing,as well as related technologies such as fog computing,smart health research is progressively moving in the right ***,fog computing,IoT sensors,blockchain,privacy and security,and other related technologies have been the focus of smart health research in recent *** the moment,the focus in cloud and smart health research is on how to use the cloud to solve the problem of enormous health data and enhance service performance,including cloud storage,retrieval,and calculation of health big *** article reviews state-of-the-art edge computing methods that has shifted to the collection,transmission,and calculation of health data,which includes various sensors and wearable devices used to collect health data,various wireless sensor technologies,and how to process health data and improve edge performance,among other ***,the typical smart health application cases,blockchain’s application in smart health,and related privacy and security issues were reviewed,as well as future difficulties and potential for smart health *** comparative analysis provides a reference for the the mobile edge computing in healthcare systems.

关键词： IoT mobile-edge computing cloud computing e-health

Earthworm Optimization with Improved SqueezeNet Enabled Facial Expression Recognition model

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Computer Systems Science & Engineering 2023年第8期46卷 2247-2262页

作者： N.Sharmili Saud Yonbawi Sultan Alahmari E.Laxmi Lydia mohamad Khairi Ishak Hend Khalid Alkahtani Ayman Aljarbouh samih m.mostafa Computer Science and Engineering Department Gayatri Vidya Parishad College of Engineering for WomenVisakhapatnamAndhra PradeshIndia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Computer Science University of Central AsiaNaryn722600Kyrgyzstan Faculty of Computers and Information South Valley UniversityQena83523Egypt

Facial expression recognition(FER)remains a hot research area among computer vision researchers and still becomes a challenge because of high intraclass *** techniques for this problem depend on hand-crafted features,namely,LBP,SIFT,and HOG,along with that a classifier trained on a database of videos or *** execute perform well on image datasets captured in a controlled condition;however not perform well in the more challenging dataset,which has partial faces and image ***,many studies presented an endwise structure for facial expression recognition by utilizing DL ***,this study develops an earthworm optimization with an improved SqueezeNet-based FER(EWOISN-FER)*** presented EWOISN-FER model primarily applies the contrast-limited adaptive histogram equalization(CLAHE)technique as a pre-processing *** addition,the improved SqueezeNet model is exploited to derive an optimal set of feature vectors,and the hyperparameter tuning process is performed by the stochastic gradient boosting(SGB)***,EWO with sparse autoencoder(SAE)is employed for the FER process,and the EWO algorithm appropriately chooses the SAE ***-ranging experimental analysis is carried out to examine the performance of the proposed *** experimental outcomes indicate the supremacy of the presented EWOISN-FER technique.

关键词： Facial expression recognition deep learning computer vision earthworm optimization hyperparameter optimization

An Optimized Algorithm for CR-mImO Wireless Networks

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Computers, materials & Continua 2022年第4期71卷 697-715页

作者： Imran Khan Fahd N.Al-Wesabi marwa Obayya Anwer mustafa Hilal manar Ahmed Hamza mohammed Rizwanullah Fahad Ahmed Al-Zahrani Hirofumi Amano samih m.mostafa Department of Electrical Engineering University of Engineering&TechnologyPeshawarPakistan Department of Computer Science King Khalid UniversityMuhayel AseerKSA Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Computer Engineering Department Umm Al-Qura UniversityMecca24381Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

With the rapid development of wireless communication technology,the spectrum resources are increasingly strained which needs optimal *** radio(CR)is one of the key technologies to solve this *** sensing not only includes the precise detection of the communication signal of the primary user(PU),but also the precise identification of its modulation type,which can then determine the a priori information such as the PU’service category,so as to use this information to make the cognitive user(CU)aware to discover and use the idle spectrum more effectively,and improve the spectrum *** sensing is the primary feature and core part of *** sensing algorithms includes energy detection,cyclostationary feature detection,matched filter detection,and so *** energy detection algorithm has a simple structure and does not require prior knowledge of the PU transmitter signal,but it is easily affected by noise and the threshold is not easy to *** combination of multiple-input multiple-output(mImO)with CR improves the spectral efficiency and multipath fading *** best utilize the PU spectrum while minimizing the overall transmit power,an iterative technique based on semidefinite programming(SDP)and minimum mean squared error(mmSE)is ***,this article proposed a new method for max-min fairness *** compared to existing algorithms,the simulation results show that the proposed algorithms perform better in terms of total transmitted power and signal-tointerference plus noise ratio(SINR).Furthermore,the proposed algorithm effectively improved the system performance in terms of number of iterations,interference temperature threshold and balance SINR level which makes it superior over the conventional schemes.

关键词： Cognitive radio spectrum utilization bandwidth primary user

Hybrid multi-Strategy Aquila Optimization with Deep Learning Driven Crop Type Classification on Hyperspectral Images

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Computer Systems Science & Engineering 2023年第10期47卷 375-391页

作者： Sultan Alahmari Saud Yonbawi Suneetha Racharla ELaxmi Lydia mohamad Khairi Ishak Hend Khalid Alkahtani Ayman Aljarbouh samih m.mostafa King Abdulaziz City for Science and Technology P.O Box 6086Riyadh 11442Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of AImL Aditya Engineering CollegeSurempallemAndhra PradeshIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer Science University of Central AsiaNaryn722600Kyrgyzstan Faculty of Computers and Information South Valley UniversityQena83523Egypt

Hyperspectral imaging instruments could capture detailed spatial information and rich spectral signs of observed *** spatial information and spectral signatures of hyperspectral images(HSIs)present greater potential for detecting and classifying fine *** accurate classification of crop kinds utilizing hyperspectral remote sensing imaging(RSI)has become an indispensable application in the agricultural *** is significant for the prediction and growth monitoring of crop *** the deep learning(DL)techniques,Convolution Neural Network(CNN)was the best method for classifying HSI for their incredible local contextual modeling ability,enabling spectral and spatial feature *** article designs a Hybrid multi-Strategy Aquila Optimization with a Deep Learning-Driven Crop Type Classification(HmAODL-CTC)algorithm *** proposed HmAODL-CTC model mainly intends to categorize different types of crops on *** accomplish this,the presented HmAODL-CTC model initially carries out image preprocessing to improve image *** addition,the presented HmAODL-CTC model develops dilated convolutional neural network(CNN)for feature *** hyperparameter tuning of the dilated CNN model,the HmAO algorithm is ***,the presented HmAODL-CTC model uses an extreme learning machine(ELm)model for crop type classification.A comprehensive set of simulations were performed to illustrate the enhanced performance of the presented HmAODL-CTC *** comparison studies reported the improved performance of the presented HmAODL-CTC algorithm over other compared methods.

关键词： Crop type classification hyperspectral images agricultural monitoring deep learning metaheuristics

modeling of Sensor Enabled Irrigationmanagement for Intelligent Agriculture Using Hybrid Deep Belief Network

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Computer Systems Science & Engineering 2023年第8期46卷 2319-2335页

作者： Saud Yonbawi Sultan Alahmari B.R.S.S.Raju Chukka Hari Govinda Rao mohamad Khairi Ishak Hend Khalid Alkahtani JoséVarela-Aldás samih m.mostafa Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Aditya Engineering College Affiliated to JNTUK(Kakinada) SurampalemIndia Department of mBA Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11564Saudi Arabia SISAu Research Group Universidad Tecnológica IndoaméricaAmbato180103Ecuador Faculty of Computers and Information South Valley UniversityQena83523Egypt

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual *** the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart *** irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation *** learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an *** this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(mBWODBN-SIS)for intelligent *** mBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination ***,the mBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not *** mBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the mBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

关键词： Agriculture smart farming hyperparameter tuning artificial intelligence irrigation management sensors deep learning