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Hybrid Grey Wolf and Dipper Throated Optim.zation in Network Intrusion Detection System.

Com.uters, m.terials & Continua 2023年第2期74卷 2695-2709页

作者： Reem.Alkanhel Doaa Sam. Khafaga El-sayed m.El-kenawy Abdelaziz A.Abdelham.d Abdelham.ed Ibrahim.Rashid Am.n m.stafa Abotaleb B.m.El-den Departm.nt of Inform.tion Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Com.uter Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Com.unications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Departm.nt of Com.uter Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Departm.nt of Com.uter Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Com.uter Engineering and Control System. Departm.nt Faculty of EngineeringMansoura UniversityMansoura35516Egypt Departm.nt of Com.uter Science University of Engineering and TechnologyTaxilaPakistan Departm.nt of System.Program.ing South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a m.dern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks m.y be vulnerable to several routing ***’s why a network intrusion detection system.NIDS)is needed to guard against routing assaults on RPL-based IoT *** im.alance between the false and valid attacks in the training set degrades the perform.nce of m.chine learning em.loyed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on m.taheuristic optim.zation applied to locality-sensitive hashing and synthetic m.nority oversam.ling technique(LSH-Sm.TE).The proposed optim.zation approach is based on a new hybrid between the grey wolf and dipper throated optim.zation *** prove the effectiveness of the proposed approach,a set of experim.nts were conducted to evaluate the perform.nce of NIDS for three cases,nam.ly,detection without dataset balancing,detection with Sm.TE balancing,and detection with the proposed optim.zed LSHSOm.E *** results showed that the proposed approach outperform. the other approaches and could boost the detection *** addition,a statistical analysis is perform.d to study the significance and stability of the proposed *** conducted experim.nts include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 Cm.,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： m.taheuristics grey wolf optim.zation dipper throated optim.zation dataset balancing locality sensitive hashing Sm.TE

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m.taheuristic Optim.zation for m.bile Robot Navigation Based on Path Planning

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Com.uters, m.terials & Continua 2022年第11期73卷 2241-2255页

作者： El-sayed m.El-kenawy Zeeshan Shafi Khan Abdelham.ed Ibrahim.Bandar Abdullah Aloyaydi Hesham.Arafat Ali Ali E.Takieldeen Departm.nt of Com.unications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Com.uter Science Departm.nt College of Engineering and Computer ScienceMustaqbal UniversityBuraidahSaudi Arabia Com.uter Engineering and Control System. Departm.nt Faculty of EngineeringMansoura UniversityMansoura35516Egypt Departm.nt of m.chanical Engineering Qassim UniversityBuraidah51452Saudi Arabia

Recently,the path planning problem.m.y be considered one of the m.st interesting researched topics in autonom.us *** is why finding a safe path in a cluttered environm.nt for a m.bile robot is a significant requisite.A prom.sing route planning for m.bile robots on one side saves tim. and,on the other side,reduces the wear and tear on the robot,saving the capital *** route planning m.thods for the m.bile robot have been developed and *** to our best knowledge,no m.thod offers an optim.m.solution am.ng the existing *** Swarm.Optim.zation(PSO),a num.rical optim.zation m.thod based on the m.bility of virtual particles in a m.ltidim.nsional space,is considered one of the best algorithm. for route planning under constantly changing environm.ntal *** the researchers,reactive m.thods are increasingly com.on and extensively used for the training of neural networks in order to have efficient route planning for m.bile *** paper proposes a PSO Weighted Grey Wolf Optim.zation(PSOWGWO)*** is a hybrid algorithm.based on enhanced Grey Wolf Optim.zation(GWO)with *** order to m.asure the statistical efficiency of the proposed algorithm.Wilcoxon rank-sum.and ANOVA statistical tests are *** experim.ntal results dem.nstrate a 25%to 45%enhancem.nt in term. of Area Under Curve(AUC).m.reover,superior perform.nce in term. of data size,path planning tim.,and accuracy is dem.nstrated over other state-of-the-art techniques.

关键词： m.bile robot swarm.optim.zation robot route planning neural networks

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Weight Prediction Using the Hybrid Stacked-LSTm.Food Selection m.del

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Com.uter System. Science & Engineering 2023年第7期46卷 765-781页

作者： Ahm.d m.Elshewey m.hm.ud Y.Sham. Zahraa Tarek m.ham.d m.gahed El-sayed m.El-kenawy m.ham.d A.El-dosuky Faculty of Com.uters and Inform.tion Computer Science DepartmentSuez UniversitySuezEgypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt Faculty of Com.uters and Inform.tion Computer Science DepartmentMansoura University35561Egypt Faculty of Physical Education Track and Field Competitions DepartmentArish UniversityEgypt Delta Higher Institute of Engineering and Technology Mansoura35111Egypt Departm.nt of Com.uter Science Arab East CollegesRiyadh13544Saudi Arabia

Food choice m.tives(i.e.,m.od,health,natural content,convenience,sensory appeal,price,fam.liarities,ethical concerns,and weight control)have an im.ortant role in transform.ng the current food system.to ensure the healthiness of people and the sustainability of the *** from.several dom.ins have presented several m.dels addressing issues influencing food choice over the ***,a m.ltidisciplinary approach is required to better understand how various aspects interact with one another during the decision-m.king *** this paper,four Deep Learning(DL)m.dels and one m.chine Learning(m.)m.del are utilized to predict the weight in pounds based on food *** Long Short-Term.m.m.ry(LSTm.m.del,stacked-LSTm.m.del,Conventional Neural Network(CNN)m.del,and CNN-LSTm.m.del are the used deep learning *** the applied m. m.del is the K-Nearest Neighbor(KNN)*** efficiency of the proposed m.del was determ.ned based on the error rate obtained from.the experim.ntal *** findings indicated that m.an Absolute Error(m.E)is 0.0087,the m.an Square Error(m.E)is 0.00011,the m.dian Absolute Error(m.dAE)is 0.006,the Root m.an Square Error(Rm.E)is 0.011,and the m.an Absolute Percentage Error(m.PE)is ***,the results dem.nstrated that the stacked LSTm.achieved im.roved results com.ared with the LSTm.CNN,CNN-LSTm.and KNN regressor.

关键词： Weight prediction m.chine learning deep learning LSTm CNN KNN

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Effects of graphene oxide/TiO_(2) nanocom.osite,graphene oxide nanosheets and Cedr extraction solution on IFT reduction and ultim.te oil recovery from.a carbonate rock

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Petroleum 2022年第4期8卷 476-482页

作者： Am.n Garm.oudi m.hdi Kheirollahi sayed Am.rhosein m.usavi m.slem.Fattahi Elaheh Ham.d m.hvelati Departm.nt of Petroleum.Engineering Abadan Faculty of Petroleum EngineeringPetroleum University of Technology(PUT)AbadanIran Departm.nt of Chem.cal Engineering Abadan Faculty of Petroleum EngineeringPetroleum University of Technology(PUT)AbadanIran Departm.nt of Basic Sciences Abadan Faculty of Petroleum EngineeringPetroleum University of Technology(PUT)AbadanIran

Increasing the num.er of depleted reservoirs and global dem.nd for energy have left us with low alternative but to use new ways to extract m.re *** different m.terial used for tertiary oil recovery,surfactant injection has proved very prom.sing solutions,such as interfacial tension reduction and wettability *** any harm.to the environm.nt and m.anwhile being econom.cally feasible,natural surfactants have been attracted researchers in recent *** extraction which is produced from.Zizyphus Spina Christi leaves has shown som. beneficial characteristics like IFT reduction and wettability ***,the am.unt of IFT reduction is not considerable,so we decided to augm.nt its effectiveness by adding two different *** this investigation,three concentrations(0.01,0.05 and 0.1 wt%)of both graphene oxide(GO)nanosheet and GO/TiO_(2) nanocom.osite was added to Cedr extraction solution to study their potential on IFT reduction and im.roving the ultim.te oil *** concentration of 0.05 wt percent showed the lowest IFT in both *** this concentration,the IFT of GO/TiO_(2)-augm.nted solution and GO-augm.nted solution were m.asured of 10.5 and 12.3 m./m.*** the bare Cedr solution showed 23.8 m./m.at its critical m.celle *** coreflooding tests were also perform.d at the aforem.ntioned *** oil recovery reached to 65%of original oil volum. in GO/TiO_(2)-augm.nted solution,com.ared to 56% in GO-augm.nted solution case and 40%in bare Cedr solution *** Electron m.croscopy im.ges were also taken from.the rock sam.les exposed to nanofluids to investigate any severe harm.to the *** showed low tendency of both particles to adsorb on rock surface and plug large pores.

关键词： Cedr extraction Coreflooding GO nanosheet GO-TiO_(2)nanocom.osite IFT reduction Enhanced oil recovery

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Wind Power Prediction Based on m.chine Learning and Deep Learning m.dels

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Com.uters, m.terials & Continua 2023年第1期74卷 715-732页

作者： Zahraa Tarek m.hm.ud Y.Sham. Ahm.d m.Elshewey El-sayed m.El-kenawy Abdelham.ed Ibrahim.Abdelaziz A.Abdelham.d m.ham.d A.El-dosuky Faculty of Com.uters and Inform.tion Computer Science DepartmentMansoura UniversityMansoura35561Egypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt Faculty of Com.uters and Inform.tion Computer Science DepartmentSuez UniversitySuezEgypt Departm.nt of Com.unications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Com.uter Engineering and Control System. Departm.nt Faculty of EngineeringMansoura UniversityMansoura35516Egypt Departm.nt of Com.uter Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Departm.nt of Com.uter Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Departm.nt of Com.uter Science Arab East CollegesRiyadh13544Saudi Arabia

Wind power is one of the sustainable ways to generate renewable *** recent years,som. countries have set renewables to m.et future energy needs,with the prim.ry goal of reducing em.ssions and prom.ting sustainable growth,prim.rily the use of wind and solar *** achieve the prediction of wind power generation,several deep and m.chine learning m.dels are constructed in this article as base *** regression m.dels are Deep neural network(DNN),k-nearest neighbor(KNN)regressor,long short-term.m.m.ry(LSTm.,averaging m.del,random.forest(RF)regressor,bagging regressor,and gradient boosting(GB)*** addition,data cleaning and data preprocessing were perform.d to the *** dataset used in this study includes 4 features and 50530 *** accurately predict the wind power values,we propose in this paper a new optim.zation technique based on stochastic fractal search and particle swarm.optim.zation(SFSPSO)to optim.ze the param.ters of LSTm.*** evaluation criteria were utilized to estim.te the efficiency of the regression m.dels,nam.ly,m.an absolute error(m.E),Nash Sutcliffe Efficiency(NSE),m.an square error(m.E),coefficient of determ.nation(R2),root m.an squared error(Rm.E).The experim.ntal results illustrated that the proposed optim.zation of LSTm.using SFS-PSO m.del achieved the best results with R2 equals 99.99%in predicting the wind power values.

关键词： Prediction of wind power data preprocessing perform.nce evaluation

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Network Intrusion Detection Based on Feature Selection and Hybrid m.taheuristic Optim.zation

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Com.uters, m.terials & Continua 2023年第2期74卷 2677-2693页

作者： Reem.Alkanhel El-sayed m.El-kenawy Abdelaziz A.Abdelham.d Abdelham.ed Ibrahim.m.nal Abdullah Alohali m.stafa Abotaleb Doaa Sam. Khafaga Departm.nt of Inform.tion Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Com.unications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Departm.nt of Com.uter Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Departm.nt of Com.uter Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Com.uter Engineering and Control System. Departm.nt Faculty of EngineeringMansoura UniversityMansoura35516Egypt Inform.tion System. Departm.nt College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of System.Program.ing South Ural State UniversityChelyabinsk454080Russia Departm.nt of Com.uter Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Applications of internet-of-things(IoT)are increasingly being used in m.ny facets of our daily life,which results in an enorm.us volum. of *** com.uting and fog com.uting,two of the m.st com.on technologies used in IoT applications,have led to m.jor security *** are on the rise as a result of the usage of these technologies since present security m.asures are *** artificial intelligence(AI)based security solutions,such as intrusion detection system.(IDS),have been proposed in recent *** technologies that require data preprocessing and m.chine learning algorithm.perform.nce augm.ntation require the use of feature selection(FS)techniques to increase classification accuracy by m.nim.zing the num.er of features *** the other hand,m.taheuristic optim.zation algorithm. have been widely used in feature selection in recent *** this paper,we proposed a hybrid optim.zation algorithm.for feature selection in *** proposed algorithm.is based on grey wolf(GW),and dipper throated optim.zation(DTO)algorithm. and is referred to as *** proposed algorithm.has a better balance between the exploration and exploitation steps of the optim.zation process and thus could achieve better *** the em.loyed IoT-IDS dataset,the perform.nce of the proposed GWDTO algorithm.was assessed using a set of evaluation m.trics and com.ared to other optim.zation approaches in 2678 Cm.,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is perform.d to assess the stability and effectiveness of the proposed *** results confirm.d the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.

关键词： Feature selection grey wolf optim.zation dipper throated optim.zation intrusion detection internet-of-things(IoT)

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Deep Learning m.thods Used in Rem.te Sensing Im.ges: A Review

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Journal of Environm.ntal & Earth Sciences 2023年第1期5卷 33-64页

作者： Ekram.m.Rewhel Jianqiang Li Am.l A.Ham.d Hatem.m.Keshk Am.ra S.m.hm.ud sayed A.sayed Ehab Sam.r Hind H.Zeyada sayed A.m.ham.d m.rwa S.m.ustafa Aym.n H.Nasr Ashraf K.Helm. School of Software Engineering Beijing University of Science and TechnologyBeijing100083China Data Reception Analysis and Receiving Station DivisionNational Authority for Remote Sensing and Space ScienceCairo1564Egypt

Undeniably,Deep Learning(DL)has rapidly eroded traditional m.chine learning in Rem.te Sensing(RS)and geoscience dom.ins with applications such as scene understanding,m.terial identification,extrem. weather detection,oil spill identification,am.ng m.ny *** m.chine learning algorithm. are given less and less attention in the era of big ***,a substantial am.unt of work aim.d at developing im.ge classification approaches based on the DL m.del’s success in com.uter *** num.er of relevant articles has nearly doubled every year since *** in rem.te sensing technology,as well as the rapidly expanding volum. of publicly available satellite im.gery on a worldwide scale,have opened up the possibilities for a wide range of m.dern ***,there are som. challenges related to the availability of annotated data,the com.lex nature of data,and m.del param.terization,which strongly im.act *** this article,a com.rehensive review of the literature encom.assing a broad spectrum.of pioneer work in rem.te sensing im.ge classification is presented including network architectures(vintage Convolutional Neural Network,CNN;Fully Convolutional Networks,FCN;encoder-decoder,recurrent networks;attention m.dels,and generative adversarial m.dels).The characteristics,capabilities,and lim.tations of current DL m.dels were exam.ned,and potential research directions were discussed.

关键词： Deep Learning(DL) Satellite im.ging Im.ge classification Segm.ntation and object detection

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Influence of preceding crop and tillage system.on forage yield and quality of selected sum.er grass and legum. forage crops under arid conditions

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Journal of Integrative Agriculture 2022年第11期21卷 3329-3344页

作者： Hend H.m.HASSAN El-sayed E.A.EL-SOBKY Elsayed m.NSOUR Ahm.d S.m.El-KHOLY m.ham.d F.AWAD Hayat ULLAH Avishek DATTA Forage Crops Research Departm.nt Field Crops Research InstituteAgricultural Research CenterGiza 12619Egypt Agronom. Departm.nt Faculty of AgricultureZagazig UniversityZagazig 44519Egypt Departm.nt of Biology College of ScienceTaif UniversityTaif 21944Saudi Arabia Agricultural System. and Engineering Department of FoodAgriculture and BioresourcesSchool of EnvironmentResources and DevelopmentAsian Institute of TechnologyKlong LuangPathum Thani 12120Thailand

Am.ng the crop production factors,preceding crop and tillage m.nagem.nt affect the sustainable use of soil resources and ultim.tely crop growth and *** study aim.d at investigating the im.act of preceding winter crops(grass or legum.)and different tillage system. on forage yield,quality and nutritive values of three sum.er grass(Sudan grass,pearl m.llet and teosinte)and two legum. forage crops(cowpea and guar)under arid *** results exhibited that growing forage crops after legum.s(as berseem.clover)produced the highest fresh and dry forage yields and quality attributes com.ared with grasses(as wheat)with the exception of crude fiber content,which was ***,tillage practices showed positive im.act on forage yields and quality *** m.xim.m.forage yields and quality param.ters were recorded under conventional tillage(CT)practice com.ared with reduced tillage(RT)and no-tillage(NT)*** the evaluated crops,the highest yields of fresh forage,dry forage,crude fiber,crude protein and total digestible nutrient were exhibited by grass forage crops(Sudan grass,pearl m.llet and teosinte),whereas the highest crude protein content and the digestible energy values were produced by legum. forage crops(cowpea and guar).The m.xim.m.fresh forage,dry forage,crude fiber,crude protein,total digestible nutrient and digestible crude protein yields were produced by pearl m.llet followed by Sudan grass under CT and RT after berseem.*** highest net return was recorded by sowing pearl m.llet after berseem.clover and applying CT followed by RT practices,which could be recom.ended for the com.ercial ***,it could be assum.d that the com.ination of growing grass forage crops after legum. crops under CT or RT system. could enhance forage crop yield and quality with an im.rovem.nt in soil properties for sustainable agriculture with low cost and the highest net incom..

关键词： soil tillage preceding crop forage quality nutritive values net return

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Dipper Throated Algorithm.for Feature Selection and Classification in Electrocardiogram

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Com.uter System. Science & Engineering 2023年第5期45卷 1469-1482页

作者： Doaa Sam. Khafaga Am.l Ali Alhussan Abdelaziz A.Abdelham.d Abdelham.ed Ibrahim.m.ham.d Saber El-sayed m.El-kenawy Departm.nt of Com.uter Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Com.uter Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Departm.nt of Com.uter Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Com.uter Engineering and Control System. Departm.nt Faculty of EngineeringMansoura UniversityMansoura35516Egypt Electronics and Com.unications Engineering Departm.nt Faculty of EngineeringDelta University for Science and TechnologyMansouraEgypt Departm.nt of Com.unications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Arrhythm.a has been classified using a variety of *** of the dynam.c nature of electrocardiogram.ECG)data,traditional handcrafted approaches are difficult to execute,m.king the m.chine learning(m.)solutions m.re *** with cardiac arrhythm.as can benefit from.com.etent m.nitoring to save their *** arrhythm.a classification and prediction have greatly im.roved in recent *** are a category of conditions in which the heart's electrical activity is abnorm.lly rapid or *** year,it is one of the m.in reasons of m.rtality for both m.n and wom.n,*** the classification of arrhythm.as,this work proposes a novel technique based on optim.zed feature selection and optim.zed K-nearest neighbors(KNN)*** proposed m.thod m.kes advantage of the UCI repository,which has a 279-attribute high-dim.nsional cardiac arrhythm.a *** proposed approach is based on dividing cardiac arrhythm.a patients into 16 groups based on the electrocardiography dataset’s *** purpose is to design an efficient intelligent system.em.loying the dipper throated optim.zation m.thod to categorize cardiac arrhythm.a *** m.thod of com.rehensive arrhythm.a classification outperform. earlier m.thods presented in the *** achieved classification accuracy using the proposed approach is 99.8%.

关键词： Feature selection electrocardiogram m.taheuristics dipper throated algorithm

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m.deling and Perform.nce Analysis of Spiral Fishbone Network Using NS-2

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Journal of Com.uter and Com.unications 2022年第3期10卷 125-140页

作者： Pronab Biswas m. m.ruf Islam.sayed Asaduzzam.n Nazrul Islam.m. Raihan Departm.nt of Software Engineering Daffodil International University Dhaka Bangladesh Departm.nt of Inform.tion and Com.unication Technology Mawlana Bhashani Science and Technology University Tangail Bangladesh Departm.nt of Com.uter Science and Engineering North Western University Khulna Bangladesh

In this research, we have projected and carried out a novel fishbone network that shows better perform.nce in the term.of m.nim.zing the packet delay with respect to sink speed. Previous study im.lies that sector angle affects greatly on designing fishbone network. Finite Set of nodes arranges to sense the physical condition of any system.is called wireless sensor. Our designed fishbone network can be potentially applied for a wireless sensing system.to form.late a whole network. The network is a novel design which has been finalized by com.aring sector angle. Analysis takes place by varying packet delay according to sink speed. Future analysis takes place for Quality of Service (QoS) and Quality of Experience (QoE). Latency of Packet and its size is the m.asurem.nt criteria of any network or service is called Quality of Service (QoS). On the other hand the user experience of using the designed network is called Quality of Experience (QoE). Our designed network has been analyzed in TCP Tracer to find out the latency or packet delay for different users. The user data has been shorted and equated am.ng them.for latency with different no of packets. Our proposed spiral fishbone network shows better QoS and QoE. In future m.re nodes can be added to design extended fishbone network for wireless.

关键词： Fishbone Network Network m.delling Perform.nce Analysis NS-2

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