A New Task Scheduling Algorithm Based on Improved Genetic Algorithm
|
|
- Dorcas Clemence Clarke
- 8 years ago
- Views:
Transcription
1 A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment 1 Congcong Xong, 2 Long Feng, 3 Lxan Chen *1 College of Computer Scence and Informaton Engneerng, Tanjn Unversty of Scence & Technology, Tanjn , Chna, E-mal: xongcc@tust.edu.cn 2 College of Computer Scence and Informaton Engneerng, Tanjn Unversty of Scence & Technology, Tanjn , Chna, E-mal:fenglong0826@163.com 3 Informatzaton Constructon and Management Offce, Tanjn Unversty of Scence & Technology, Tanjn , Chna, E-mal: clx@tust.edu.cn Abstract Task schedulng and resource allocaton are two core technques n cloud computng. In order to use resource effcently n heterogeneous envronment, the paper presents an new task schedulng algorthm based on Genetc Algorthm (GA). The model consders four aspects of the task schedulng: task fnshed tme, task expenses, bandwdth and relablty n cloud computng envronment. And the optmal target of the model s to acheve mn-tme, mn-cost, max-bandwdth and max-relablty. Besdes, the new algorthm adopts rule-bound crossover and mutaton operaton to mprove ndvdual qualty. The results of smulaton experments valdate that compared wth the exstng GA, the new GA ntroduced the Qualty of Servce (QoS) can reflect users satsfacton of the schedulng results n the round and solve the task schedulng problems n cloud computng envronment effectvely. 1. Introducton Keywords: Genetc Algorthm (GA), cloud computng, task schedulng There are lots of computer resource n the cloud envronment, ncludng CPU, memory, bandwdth and so on. And the method to schedule tasks effectvely has become one hotspot n the feld of computer scence. The task scheduler n cloud computng envronment s to determne a proper assgnment of resources to the tasks of jobs to complete all the jobs receved from users. Untl now, researchers have proposed some statc, dynamc and mxed forms of resource schedulng strategy n cloud computng envronment, such as: FIFO (Frst In and Frst Out) and ts smple extensons, ISH[1], ETF[1], GA-based task schedulng and so on[2-5]. The frst two algorthms are smple and belong to the statc strategy, but usually wth poor performances. Because the resources pool quotas and job queues are partly depended on artfcal settngs. However, GA-based task schedulng algorthms belong to heurstc ntellgent algorthm, whle there are always some problems such as low convergence, one-sded target and so on. Consderng the shortage of the exstng task schedulng algorthms n cloud computng, a new task schedulng based on mproved genetc algorthm s presented. The well-dstrbuted strategy, whch makes ndvduals dstrbute unformly n the soluton space by usng the chromosome matchng rate when the ntal populaton s generated, s proposed to avod the premature convergence effectvely. And the Qualty of Servce (QoS) s ntroduced to mprove the ftness functon, whch can not only fnd the correspondng relaton between the task and the vrtual machne quckly and effectvely, but also can reflect users satsfacton on the schedulng results. 2. Task schedulng There are many smlartes as well as dfferences on resource schedulng between n cloud computng and other envronments. The most remarkable dfference s the object of schedulng. The objects of tradtonal resource schedulng are the threads and tasks runnng on entty resources whch belong to the fne graned schedulng. But the objects of schedulng n the cloud envronment are vrtual machnes whch belong to the coarse graned schedulng. There are lots of computaton resources, store resources and other resources n cloud computng Advances n nformaton Scences and Servce Scences(AISS) Volume5, Number3, Feb 2013 do: /AISS.vol5.ssue3.5 32
2 A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen envronment. The task schedulng algorthm not only needs to be congruent wth the deadlne of the jobs, but also concern the users expectatons on the bandwdth and cost of the resources. So, the task schedulng n cloud computng envronment should be a mult-objectve schedulng. Mapreduce model dvdes jobs nto several nterdependent tasks after users submt jobs nto the cloud computng envronment. The execute process of tasks can be represented by a Drected Acyclc Graph (DAG) whch s shown n Fgure 1.The nodes are the tasks to be executed. The drected edges show the dependent relatonshps of the tasks. T4 T1 T5 T2 T8 T6 T3 T7 Fgure 1. An example of a DAG The task schedulng n cloud computng envronment s to execute N nterdependent tasks T { T1, T2,, TN } on M resources ( P { P1, P2,, PM } ) effcently, and the result of t should satsfy users expectatons. Expected Tme to Compute (ETC) matrx ETC [, represents the expected computaton tme of the task on the resource j. If the task T cannot execute on the resource P j, ETC [,. The total fnsh tme of the task T could be obtaned from Equaton 1. ETF M s mn ETC[, (1) j j1 Then the total executon tme of all the tasks could be expressed as follows: Where, 1,2,, N j 1,2,, M N tme maxetf (2). Network transmsson decded by bandwdth has a sgnfcant effect on those applcatons whch communcate wth others frequently or contan a large amount of nformaton. Gven that BW s the bandwdth of the resource, then the total used bandwdth of all the tasks can be wm defned as follows: 1 Execute _ bw TaskNum( J m ) TaskTatal ( m) ln BW TaskTotal ( m1) wm (3) Prce constrant s one of the most normal QoS constrants at present. Snce the charge of resources s measured by unt, the task T could be defned as: 33
3 A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen EC [, / qc 1 cpu/ num q2c mem/ MB q3c stor/ MB q4c bw Mbps (4) where C s the unt prce of resources, and P s the number of resources. Then, the total prce of all the tasks could be obtaned from Equaton 5. N M j 1 1 cost mnec[, (5) Assumng that Fal [ s the breakdown rate of resources obtaned by resource montor system. The user expected functon about the completon rate can be obtaned by Equaton 6. succ (1 Fal[, ) N 1 DEFINITION 1 The executon of a task s sad to acheve user satsfacton when the resource consumpton of the task s near to the value users have expected. s the real resource consumpton of the task. s the resource consumpton of the task whch s the user expectaton value. Formally, the user satsfacton functon could be expressed as: W ln AR / ER (7) Where s a balance constant, and 0 1. The value of user satsfacton functon s 0, when AR s equal to ER, whch ndcates the schedulng result has acheve users satsfacton. And fw 0, t means the real resource consumpton of the task exceeds users expectatons. Whle f W 0, the result s totally contrary to the former one. Gven the user expected cost Expect_cost, user expected computaton tme Expect_tme, user expected bandwdth Expect_bw and set user expected completon rate Expect_succ whch are set by users. A weghted objectve functon can be used as the ftness functon whch s defned as: (6) f tme bw cost succ 1ln 2 ln 3 ln 4 ln (8) Expect_ tme Expect _ bw Expect_cost Expect_ succ where ndcates the weght of the QoS constrant and As varous applcatons may requre dfferent QoS, weght coeffcent vectors can be set dfferently to satsfy ther demands. 3. Genetc algorthm Genetc Algorthm (GA) n partcular became popular through the work of John Holland n the early 1970s [6]. GA generates solutons to optmzaton problems usng technques nspred by natural evoluton [7]. And t becomes a wdely used global optmzaton algorthm n many felds wth ts remarkable characterstcs of hgh-effcency, stablty, sutablty for parallel processng [8]. There are always some problems such as premature convergence n the Basc Genetc Algorthm (BGA). Several algorthms and methods have been proposed to solve the task 34
4 A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen schedulng problems. Most of them, however, only unlaterally consder reducng the completon tme and the average completon tme, such as [2,9-11] or reflectng users ntegrated requrements on the network bandwdth, prce and so on. Therefore, researches focusng on all of the aspects are needed. Accordng to the basc algorthm dea of GA and characterstcs of task schedulng n cloud computng envronment, a new optmzaton method based on the BGA for solvng the above-mentoned problems s presented. The mproved algorthm can avod the premature convergence effectvely by usng the chromosome matchng rate. In addton, consderng the defnton of QoS, ts ftness functon can take users expectatons ncludng the servce response tme, network bandwdth, task expenses and relablty as the standard to measure the schedulng results Encodng of chromosomes Bnary encodng and float encodng are the most common types of encodng. Consderng the dvson of jobs n cloud computng envronment, ths paper adopts an ndrect encodng type: resource-task encodng. The total number of all the tasks s the length of each chromosome. The value of each gene s the resource number at the same locus. For example,gven the length of each chromosome 10 and the value range of each gene s from 1 to 3. The chromosome {2,3,1,2,3,2,1,2,2,1} means that the frst task s carred out on the second vrtual machne (resource), and the second task s carred out on the thrd vrtual machne, and so on. Therefore, three tasks have been sent to the frst vrtual machne to be executed: T 3, T 7 and T 10.Fve tasks have been sent to the second vrtual machne and two to the thrd vrtual machne Intal populaton generatng The ntal populaton has great nfluence on convergence of GA. The populaton sze s usually set to be between 50 and 160.Gven the populaton sze S, the length of each chromosome N, then the ntal populaton s generated randomly Ftness functon Durng each successve generaton, ndvdual solutons are selected through a ftness functon. It measures the qualty of the represented soluton. So, the ftness functon s a crucal part of GAs. The ftness functon s always desgned to be a one-sded target functon n the tradtonal GA, whch s not sutable for cloud computng.the satsfacton of the servce n cloud computng envronment can be measured by Qualty of Servce (QoS). Consderng the commercal objectve of cloud computng and QoS model, the ftness functon can be set as Equaton Operators Selecton Operaton The objectve of selecton operaton s to make the better solutons have a hgher probablty to be transmtted to the next generaton. The value of selecton rate can be defned as: f ( ) p( ) (9) S f k k1 35
5 A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen where f s the ftness value of the ndvdual. The roulette wheel selecton schema s adopted to mplement the selecton step. The cumulatve probablty of the ndvdual could be obtaned from Equaton Crossover and Mutaton P ( ) p( k) (10) s Crossover s known as a basc genetc operator. It partally exchanges nformaton between the two selected chromosomes [6,12]. Once the strng s pcked at random to be subjected to crossover from the populaton, t randomly chooses several crossover ponts and exchanges the alleles wth ts mate to form two new strngs. For example, two crossng chromosomes- and can exchange one or more alleles. Mutaton helps avod stckng at the local optmum and guarantee the populaton dversty. Chromosome reversal strategy s used as the mutaton methodology n ths paper. The chromosome randomly selects ts substrng and nverts t Proposed Algorthm Procedure The man procedure of the new algorthm s descrbed as follows. Step1: Generate an ntal populaton P(0) usng the matchng rate. Step2: Sort the ftness values of the chromosomes n ascendng order, k=0. Step3: Choose two chromosomes usng the roulette wheel and prepare them for crossover and mutaton. Step4: Use crossover and mutaton to create a new populaton P(k+1), k=k+1. Step5: If the maxmum number of generatons or a convergence s not reached, then return to Step Expermental results and evaluaton A smulaton experment s desgned to compare the schedulng performance of the BGA and Improved Genetc Algorthm (IGA). The experments have been carred out on the smulaton platform named CloudSm. The ntal parameters of the algorthms are as follows: maxmum number of generatons 80, resource number 20, crossover probablty 0.8, mutaton probablty 0.2. The value range of task number s from 20 to 100, and the weght coeffcent array { 1, 2, 3, 4 } s set to{0.6,0.1,0.3,0}( 4 s set to 0 because of the breakdown rate of resources obtaned by the platform CloudSm). The fnshed tme of two algorthms s shown n fgure 2.And the ftness value of two algorthms s shown n fgure 3. k1 Fgure 2. Fnshed tme of two algorthms 36
6 A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen As t s shown n Fgure2, the average fnsh tme of the BGA at the prelmnary stage s less than that of IGA. However, as the number of generatons ncreases, the advantages of the IGA become more and more obvous. The reason s that the crossover and mutaton of the IGA mprove ts global search ablty. The ftness value could reflect users satsfacton of the schedulng result. The schedulng result s congruent wth users satsfacton when the ftness value s 0. If the ftness value s bgger than 0, t means the schedulng result exceeds users expectatons. It can be seen from the expermental results that the IGA has hgher ftness value than standardzed Genetc Algorthm, whch means the schedulng result of IGA can satsfy users expectatons better. Fgure 3. Ftness value of two algorthms 5. Conclusons Resource schedulng becomes more complex as the ntroducton of vrtualzaton technology n cloud computng[13]. Ths paper presented an mproved task schedulng algorthm based on the basc genetc algorthm combned QoS for the task schedulng n cloud computng, wth the objectve to satsfy users expectatons on servce response tme, network bandwdth, task expenses and relablty. The results show that the new IGA based task schedulng algorthm not only can be able to get hgher resources utlzaton, but also has the ablty to reflect the conformty between the schedule result and users expectatons. In addton, the next step s to focus on the study of dynamc queue schedulng algorthm to the realzaton of a unversal task schedulng algorthm and combne wth other related algorthm to make comprehensve comparsons accordng to the dfferent performance ndex. 6. References [1] Kwok Y K, Ahmad I, Statc schedulng algorthms for allocatng drected task graphs to multprocessors, ACM Computng Surveys, Vol.31, No.4, pp.406 ~ 471, [2] Chenghua Sh, Xaomn Wang, Schedulng Model of Dspatchng Ready Mxed Concrete Trucks Based on GA, AISS, Vol. 4, No. 8, pp. 131 ~ 136, [3] JanPng Wang, YanL Zhu, HongYu Feng, A Mult-Task Schedulng Method Based on Ant Colony Algorthm Combned QoS n Cloud Computng, AISS, Vol. 4, No. 11, pp. 185 ~ 192, [4] Paton N W, de Aragao M A T, Lee K, et al, Optmzng utlty n cloud computng through automatc workload executon, IEEE Data Eng Bull, Vol.32, No.1, pp.51 ~ 58,
7 A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen [5] Luyun Xu, Yunsheng Zhang, Xa-an B, A New Model and Queue Management Algorthm for Congeston Control n Cloud Servce, AISS, Vol. 4, No. 11, pp. 320 ~ 327, [6] RUDOLPH G, Convergence analyss of canoncal genetc algorthms, IEEE Trans on Neural Networks, Vol.5, No.1, pp , [7] D Martno V, Mllott M, Suboptmal schedulng n a grd usng genetc algorthms, Parallel Computng, Vol.30, pp , [8] Correa R.C., Ferrera A., Rebreyend P., Schedulng multprocessor tasks wth genetc algorthms, IEEE Transactons on Parallel and Dstrbuted Systems, Vol.10, No.8, pp [9] JnFeng Wang, KaYu Chu, An Applcaton of Genetc Algorthms for the Flexble Job-shop Schedulng Problem, IJACT, Vol. 4, No. 3, pp. 271 ~ 278, [10] Salcedo-Sanz S.,Bousono-Calzon C.,Fgueras-Vdal A.R., A mxed neural-genetc algorthm for the broadcast schedulng problem, IEEE Transactons on Wreless Communcatons, Vol.2, No.2, pp [11] Zomaya A.Y., Ward C., Macey B., Genetc Schedulng for parallel processor systems: comparatve studes and performance ssues, IEEE Transactons on Parallel and Dstrbuted Systems, Vol.10, No.8, pp , [12] Arnold D V, Hans-Georg B, A General Nose Model and Its Effects on Evoluton Strategy Performance, IEEE Transacton on Evolutonary Computaton, Vol.10, No.4, pp , [13] Janfeng Zhao, Wenhua Zeng, Mu Lu, Guangmng L, A model of Vrtual Resource Schedulng n Cloud Computng and Its Soluton usng EDAs, JDCTA, Vol. 6, No. 4, pp. 102 ~ 113,
The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis
The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationA Load-Balancing Algorithm for Cluster-based Multi-core Web Servers
Journal of Computatonal Informaton Systems 7: 13 (2011) 4740-4747 Avalable at http://www.jofcs.com A Load-Balancng Algorthm for Cluster-based Mult-core Web Servers Guohua YOU, Yng ZHAO College of Informaton
More informationA heuristic task deployment approach for load balancing
Xu Gaochao, Dong Yunmeng, Fu Xaodog, Dng Yan, Lu Peng, Zhao Ja Abstract A heurstc task deployment approach for load balancng Gaochao Xu, Yunmeng Dong, Xaodong Fu, Yan Dng, Peng Lu, Ja Zhao * College of
More informationThe Greedy Method. Introduction. 0/1 Knapsack Problem
The Greedy Method Introducton We have completed data structures. We now are gong to look at algorthm desgn methods. Often we are lookng at optmzaton problems whose performance s exponental. For an optmzaton
More informationOpen Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1
Send Orders for Reprnts to reprnts@benthamscence.ae The Open Cybernetcs & Systemcs Journal, 2014, 8, 115-121 115 Open Access A Load Balancng Strategy wth Bandwdth Constrant n Cloud Computng Jng Deng 1,*,
More informationPower Consumption Optimization Strategy of Cloud Workflow. Scheduling Based on SLA
Power Consumpton Optmzaton Strategy of Cloud Workflow Schedulng Based on SLA YONGHONG LUO, SHUREN ZHOU School of Computer and Communcaton Engneerng Changsha Unversty of Scence and Technology 960, 2nd Secton,
More informationLITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING
LITERATURE REVIEW: VARIOUS PRIORITY BASED TASK SCHEDULING ALGORITHMS IN CLOUD COMPUTING 1 MS. POOJA.P.VASANI, 2 MR. NISHANT.S. SANGHANI 1 M.Tech. [Software Systems] Student, Patel College of Scence and
More informationA Replication-Based and Fault Tolerant Allocation Algorithm for Cloud Computing
A Replcaton-Based and Fault Tolerant Allocaton Algorthm for Cloud Computng Tork Altameem Dept of Computer Scence, RCC, Kng Saud Unversty, PO Box: 28095 11437 Ryadh-Saud Araba Abstract The very large nfrastructure
More informationSurvey on Virtual Machine Placement Techniques in Cloud Computing Environment
Survey on Vrtual Machne Placement Technques n Cloud Computng Envronment Rajeev Kumar Gupta and R. K. Paterya Department of Computer Scence & Engneerng, MANIT, Bhopal, Inda ABSTRACT In tradtonal data center
More informationPAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign
PAS: A Packet Accountng System to Lmt the Effects of DoS & DDoS Debsh Fesehaye & Klara Naherstedt Unversty of Illnos-Urbana Champagn DoS and DDoS DDoS attacks are ncreasng threats to our dgtal world. Exstng
More informationData Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network *
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 24, 819-840 (2008) Data Broadcast on a Mult-System Heterogeneous Overlayed Wreless Network * Department of Computer Scence Natonal Chao Tung Unversty Hsnchu,
More informationOn the Optimal Control of a Cascade of Hydro-Electric Power Stations
On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;
More informationResource Sharing Models and Heuristic Load Balancing Methods for
Resource Sharng Models and Heurstc Load Balancng Methods for Grd Schedulng Problems Wanneng Shu 1,2, Lxn Dng 2,3,*, Shenwen Wang 2,3 1 College of Computer Scence, South-Central Unversty for Natonaltes,
More informationOptimization Model of Reliable Data Storage in Cloud Environment Using Genetic Algorithm
Internatonal Journal of Grd Dstrbuton Computng, pp.175-190 http://dx.do.org/10.14257/gdc.2014.7.6.14 Optmzaton odel of Relable Data Storage n Cloud Envronment Usng Genetc Algorthm Feng Lu 1,2,3, Hatao
More informationA GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES
82 Internatonal Journal of Electronc Busness Management, Vol. 0, No. 3, pp. 82-93 (202) A GENETIC ALGORITHM-BASED METHOD FOR CREATING IMPARTIAL WORK SCHEDULES FOR NURSES Feng-Cheng Yang * and We-Tng Wu
More informationA hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More informationAn Evolutionary Game Theoretic Approach to Adaptive and Stable Application Deployment in Clouds
An Evolutonary Game Theoretc Approach to Adaptve and Stable Applcaton Deployment n Clouds Chonho Lee Unversty of Massachusetts, Boston Boston, MA 5, USA chonho@csumbedu Yuj Yamano OGIS Internatonal, Inc
More informationImproved SVM in Cloud Computing Information Mining
Internatonal Journal of Grd Dstrbuton Computng Vol.8, No.1 (015), pp.33-40 http://dx.do.org/10.1457/jgdc.015.8.1.04 Improved n Cloud Computng Informaton Mnng Lvshuhong (ZhengDe polytechnc college JangSu
More informationProject Networks With Mixed-Time Constraints
Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
More informationFeature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College
Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure
More informationAn Interest-Oriented Network Evolution Mechanism for Online Communities
An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne
More informationA New Service Pricing Mechanism based on Coalition Game Theory in
A New Servce Prcng Mechansm based on Coalton Game Theory n Cloud Servce A New Servce Prcng Mechansm based on Coalton Game Theory n Cloud Servce 1 Luyun Xu, 2 Yunsheng Zhang *1, Frst Author, Correspondng
More informationResearch Article A Time Scheduling Model of Logistics Service Supply Chain with Mass Customized Logistics Service
Hndaw Publshng Corporaton Dscrete Dynamcs n Nature and Socety Volume 01, Artcle ID 48978, 18 pages do:10.1155/01/48978 Research Artcle A Tme Schedulng Model of Logstcs Servce Supply Chan wth Mass Customzed
More informationResource Scheduling Scheme Based on Improved Frog Leaping Algorithm in Cloud Environment
Informaton technologes Resource Schedulng Scheme Based on Improved Frog Leapng Algorthm n Cloud Envronment Senbo Chen 1, 2 1 School of Computer Scence and Technology, Nanjng Unversty of Aeronautcs and
More informationTesting and Debugging Resource Allocation for Fault Detection and Removal Process
Internatonal Journal of New Computer Archtectures and ther Applcatons (IJNCAA) 4(4): 93-00 The Socety of Dgtal Informaton and Wreless Communcatons, 04 (ISSN: 0-9085) Testng and Debuggng Resource Allocaton
More informationOptimized ready mixed concrete truck scheduling for uncertain factors using bee algorithm
Songklanakarn J. Sc. Technol. 37 (2), 221-230, Mar.-Apr. 2015 http://www.sst.psu.ac.th Orgnal Artcle Optmzed ready mxed concrete truck schedulng for uncertan factors usng bee algorthm Nuntana Mayteekreangkra
More informationForecasting the Direction and Strength of Stock Market Movement
Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems
More informationFault tolerance in cloud technologies presented as a service
Internatonal Scentfc Conference Computer Scence 2015 Pavel Dzhunev, PhD student Fault tolerance n cloud technologes presented as a servce INTRODUCTION Improvements n technques for vrtualzaton and performance
More informationEnergy Efficient Coverage Optimization in Wireless Sensor Networks based on Genetic Algorithm
Unversal Journal of Communcatons and Network 3(4): 82-88, 2015 DOI: 10.13189/ujcn.2015.030402 http://www.hrpub.org Energy Effcent Coverage Optmzaton n Wreless Sensor Networks based on Genetc Algorthm Al
More informationSoftware project management with GAs
Informaton Scences 177 (27) 238 241 www.elsever.com/locate/ns Software project management wth GAs Enrque Alba *, J. Francsco Chcano Unversty of Málaga, Grupo GISUM, Departamento de Lenguajes y Cencas de
More informationA Dynamic Energy-Efficiency Mechanism for Data Center Networks
A Dynamc Energy-Effcency Mechansm for Data Center Networks Sun Lang, Zhang Jnfang, Huang Daochao, Yang Dong, Qn Yajuan A Dynamc Energy-Effcency Mechansm for Data Center Networks 1 Sun Lang, 1 Zhang Jnfang,
More informationSciences Shenyang, Shenyang, China.
Advanced Materals Research Vols. 314-316 (2011) pp 1315-1320 (2011) Trans Tech Publcatons, Swtzerland do:10.4028/www.scentfc.net/amr.314-316.1315 Solvng the Two-Obectve Shop Schedulng Problem n MTO Manufacturng
More informationOptimal Choice of Random Variables in D-ITG Traffic Generating Tool using Evolutionary Algorithms
Optmal Choce of Random Varables n D-ITG Traffc Generatng Tool usng Evolutonary Algorthms M. R. Mosav* (C.A.), F. Farab* and S. Karam* Abstract: Impressve development of computer networks has been requred
More informationPerformance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application
Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdo-dong,
More informationA Programming Model for the Cloud Platform
Internatonal Journal of Advanced Scence and Technology A Programmng Model for the Cloud Platform Xaodong Lu School of Computer Engneerng and Scence Shangha Unversty, Shangha 200072, Chna luxaodongxht@qq.com
More informationSelfish Constraint Satisfaction Genetic Algorithm for Planning a Long-distance Transportation Network
JOURNAL OF COMPUTERS, VOL. 3, NO. 8, AUGUST 2008 77 Selfsh Constrant Satsfacton Genetc Algorthm for Plannng a Long-dstance Transportaton Network Takash Onoyama and Takuya Maekawa Htach Software Engneerng
More informationNetwork Security Situation Evaluation Method for Distributed Denial of Service
Network Securty Stuaton Evaluaton Method for Dstrbuted Denal of Servce Jn Q,2, Cu YMn,2, Huang MnHuan,2, Kuang XaoHu,2, TangHong,2 ) Scence and Technology on Informaton System Securty Laboratory, Bejng,
More informationModule 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
More informationAnts Can Schedule Software Projects
Ants Can Schedule Software Proects Broderck Crawford 1,2, Rcardo Soto 1,3, Frankln Johnson 4, and Erc Monfroy 5 1 Pontfca Unversdad Católca de Valparaíso, Chle FrstName.Name@ucv.cl 2 Unversdad Fns Terrae,
More informationRESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.
ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract
More informationA spam filtering model based on immune mechanism
Avalable onlne www.jocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):2533-2540 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A spam flterng model based on mmune mechansm Ya-png
More informationLoad Balancing By Max-Min Algorithm in Private Cloud Environment
Internatonal Journal of Scence and Research (IJSR ISSN (Onlne: 2319-7064 Index Coperncus Value (2013: 6.14 Impact Factor (2013: 4.438 Load Balancng By Max-Mn Algorthm n Prvate Cloud Envronment S M S Suntharam
More informationIntelligent Method for Cloud Task Scheduling Based on Particle Swarm Optimization Algorithm
Unversty of Nzwa, Oman December 9-11, 2014 Page 39 THE INTERNATIONAL ARAB CONFERENCE ON INFORMATION TECHNOLOGY (ACIT2014) Intellgent Method for Cloud Task Schedulng Based on Partcle Swarm Optmzaton Algorthm
More informationMooring Pattern Optimization using Genetic Algorithms
6th World Congresses of Structural and Multdscplnary Optmzaton Ro de Janero, 30 May - 03 June 005, Brazl Moorng Pattern Optmzaton usng Genetc Algorthms Alonso J. Juvnao Carbono, Ivan F. M. Menezes Luz
More informationAnt Colony Optimization for Economic Generator Scheduling and Load Dispatch
Proceedngs of the th WSEAS Int. Conf. on EVOLUTIONARY COMPUTING, Lsbon, Portugal, June 1-18, 5 (pp17-175) Ant Colony Optmzaton for Economc Generator Schedulng and Load Dspatch K. S. Swarup Abstract Feasblty
More informationHosting Virtual Machines on Distributed Datacenters
Hostng Vrtual Machnes on Dstrbuted Datacenters Chuan Pham Scence and Engneerng, KyungHee Unversty, Korea pchuan@khu.ac.kr Jae Hyeok Son Scence and Engneerng, KyungHee Unversty, Korea sonaehyeok@khu.ac.kr
More informationA DATA MINING APPLICATION IN A STUDENT DATABASE
JOURNAL OF AERONAUTICS AND SPACE TECHNOLOGIES JULY 005 VOLUME NUMBER (53-57) A DATA MINING APPLICATION IN A STUDENT DATABASE Şenol Zafer ERDOĞAN Maltepe Ünversty Faculty of Engneerng Büyükbakkalköy-Istanbul
More informationStudy on Model of Risks Assessment of Standard Operation in Rural Power Network
Study on Model of Rsks Assessment of Standard Operaton n Rural Power Network Qngj L 1, Tao Yang 2 1 Qngj L, College of Informaton and Electrcal Engneerng, Shenyang Agrculture Unversty, Shenyang 110866,
More informationResearch of Network System Reconfigurable Model Based on the Finite State Automation
JOURNAL OF NETWORKS, VOL., NO. 5, MAY 24 237 Research of Network System Reconfgurable Model Based on the Fnte State Automaton Shenghan Zhou and Wenbng Chang School of Relablty and System Engneerng, Behang
More informationDynamic Constrained Economic/Emission Dispatch Scheduling Using Neural Network
Dynamc Constraned Economc/Emsson Dspatch Schedulng Usng Neural Network Fard BENHAMIDA 1, Rachd BELHACHEM 1 1 Department of Electrcal Engneerng, IRECOM Laboratory, Unversty of Djllal Labes, 220 00, Sd Bel
More informationSCHEDULING OF CONSTRUCTION PROJECTS BY MEANS OF EVOLUTIONARY ALGORITHMS
SCHEDULING OF CONSTRUCTION PROJECTS BY MEANS OF EVOLUTIONARY ALGORITHMS Magdalena Rogalska 1, Wocech Bożeko 2,Zdzsław Heduck 3, 1 Lubln Unversty of Technology, 2- Lubln, Nadbystrzycka 4., Poland. E-mal:rogalska@akropols.pol.lubln.pl
More informationRate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Priority-based scheduling. States of a process
Dsadvantages of cyclc TDDB47 Real Tme Systems Manual scheduler constructon Cannot deal wth any runtme changes What happens f we add a task to the set? Real-Tme Systems Laboratory Department of Computer
More informationAdaptive and Dynamic Load Balancing in Grid Using Ant Colony Optimization
Sandp Kumar Goyal et al. / Internatonal Journal of Engneerng and Technology (IJET) Adaptve and Dynamc Load Balancng n Grd Usng Ant Colony Optmzaton Sandp Kumar Goyal 1, Manpreet Sngh 1 Department of Computer
More informationResource Scheduling in Desktop Grid by Grid-JQA
The 3rd Internatonal Conference on Grd and Pervasve Computng - Worshops esource Schedulng n Destop Grd by Grd-JQA L. Mohammad Khanl M. Analou Assstant professor Assstant professor C.S. Dept.Tabrz Unversty
More informationAn efficient constraint handling methodology for multi-objective evolutionary algorithms
Rev. Fac. Ing. Unv. Antoqua N. 49. pp. 141-150. Septembre, 009 An effcent constrant handlng methodology for mult-objectve evolutonary algorthms Una metodología efcente para manejo de restrccones en algortmos
More informationAn Analysis of Dynamic Severity and Population Size
An Analyss of Dynamc Severty and Populaton Sze Karsten Wecker Unversty of Stuttgart, Insttute of Computer Scence, Bretwesenstr. 2 22, 7565 Stuttgart, Germany, emal: Karsten.Wecker@nformatk.un-stuttgart.de
More informationA Design Method of High-availability and Low-optical-loss Optical Aggregation Network Architecture
A Desgn Method of Hgh-avalablty and Low-optcal-loss Optcal Aggregaton Network Archtecture Takehro Sato, Kuntaka Ashzawa, Kazumasa Tokuhash, Dasuke Ish, Satoru Okamoto and Naoak Yamanaka Dept. of Informaton
More informationFair Virtual Bandwidth Allocation Model in Virtual Data Centers
Far Vrtual Bandwdth Allocaton Model n Vrtual Data Centers Yng Yuan, Cu-rong Wang, Cong Wang School of Informaton Scence and Engneerng ortheastern Unversty Shenyang, Chna School of Computer and Communcaton
More informationANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING
ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 610-519-4390,
More informationResearch Article Enhanced Two-Step Method via Relaxed Order of α-satisfactory Degrees for Fuzzy Multiobjective Optimization
Hndaw Publshng Corporaton Mathematcal Problems n Engneerng Artcle ID 867836 pages http://dxdoorg/055/204/867836 Research Artcle Enhanced Two-Step Method va Relaxed Order of α-satsfactory Degrees for Fuzzy
More informationJoint Scheduling of Processing and Shuffle Phases in MapReduce Systems
Jont Schedulng of Processng and Shuffle Phases n MapReduce Systems Fangfe Chen, Mural Kodalam, T. V. Lakshman Department of Computer Scence and Engneerng, The Penn State Unversty Bell Laboratores, Alcatel-Lucent
More informationDownlink Power Allocation for Multi-class. Wireless Systems
Downlnk Power Allocaton for Mult-class 1 Wreless Systems Jang-Won Lee, Rav R. Mazumdar, and Ness B. Shroff School of Electrcal and Computer Engneerng Purdue Unversty West Lafayette, IN 47907, USA {lee46,
More informationA Performance Analysis of View Maintenance Techniques for Data Warehouses
A Performance Analyss of Vew Mantenance Technques for Data Warehouses Xng Wang Dell Computer Corporaton Round Roc, Texas Le Gruenwald The nversty of Olahoma School of Computer Scence orman, OK 739 Guangtao
More informationLuby s Alg. for Maximal Independent Sets using Pairwise Independence
Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent
More informationA DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña
Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION
More informationSchedulability Bound of Weighted Round Robin Schedulers for Hard Real-Time Systems
Schedulablty Bound of Weghted Round Robn Schedulers for Hard Real-Tme Systems Janja Wu, Jyh-Charn Lu, and We Zhao Department of Computer Scence, Texas A&M Unversty {janjaw, lu, zhao}@cs.tamu.edu Abstract
More informationOptimal Provisioning of Resource in a Cloud Service
ISSN (Onlne): 169-081 95 Optmal Provsonng of Resource n a Cloud Servce Yee Mng Chen 1 Shn-Yng Tsa Department of Industral Engneerng and Management Yuan Ze Unversty 135 Yuan-Tung Rd. Chung-L Tao-Yuan Tawan
More information"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More informationA Secure Password-Authenticated Key Agreement Using Smart Cards
A Secure Password-Authentcated Key Agreement Usng Smart Cards Ka Chan 1, Wen-Chung Kuo 2 and Jn-Chou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,
More informationPolitecnico di Torino. Porto Institutional Repository
Poltecnco d Torno Porto Insttutonal Repostory [Artcle] A cost-effectve cloud computng framework for acceleratng multmeda communcaton smulatons Orgnal Ctaton: D. Angel, E. Masala (2012). A cost-effectve
More informationJ. Parallel Distrib. Comput.
J. Parallel Dstrb. Comput. 71 (2011) 62 76 Contents lsts avalable at ScenceDrect J. Parallel Dstrb. Comput. journal homepage: www.elsever.com/locate/jpdc Optmzng server placement n dstrbuted systems n
More informationSelf-Adaptive SLA-Driven Capacity Management for Internet Services
Self-Adaptve SLA-Drven Capacty Management for Internet Servces Bruno Abrahao, Vrglo Almeda and Jussara Almeda Computer Scence Department Federal Unversty of Mnas Geras, Brazl Alex Zhang, Drk Beyer and
More informationIWFMS: An Internal Workflow Management System/Optimizer for Hadoop
IWFMS: An Internal Workflow Management System/Optmzer for Hadoop Lan Lu, Yao Shen Department of Computer Scence and Engneerng Shangha JaoTong Unversty Shangha, Chna lustrve@gmal.com, yshen@cs.sjtu.edu.cn
More informationJoint Dynamic Radio Resource Allocation and Mobility Load Balancing in 3GPP LTE Multi-Cell Network
288 FENG LI, LINA GENG, SHIHUA ZHU, JOINT DYNAMIC RADIO RESOURCE ALLOCATION AND MOBILITY LOAD BALANCING Jont Dynamc Rado Resource Allocaton and Moblty Load Balancng n 3GPP LTE Mult-Cell Networ Feng LI,
More informationDistributed Optimal Contention Window Control for Elastic Traffic in Wireless LANs
Dstrbuted Optmal Contenton Wndow Control for Elastc Traffc n Wreless LANs Yalng Yang, Jun Wang and Robn Kravets Unversty of Illnos at Urbana-Champagn { yyang8, junwang3, rhk@cs.uuc.edu} Abstract Ths paper
More informationNetwork Aware Load-Balancing via Parallel VM Migration for Data Centers
Network Aware Load-Balancng va Parallel VM Mgraton for Data Centers Kun-Tng Chen 2, Chen Chen 12, Po-Hsang Wang 2 1 Informaton Technology Servce Center, 2 Department of Computer Scence Natonal Chao Tung
More informationGENETIC ALGORITHM FOR PROJECT SCHEDULING AND RESOURCE ALLOCATION UNDER UNCERTAINTY
Int. J. Mech. Eng. & Rob. Res. 03 Fady Safwat et al., 03 Research Paper ISS 78 049 www.jmerr.com Vol., o. 3, July 03 03 IJMERR. All Rghts Reserved GEETIC ALGORITHM FOR PROJECT SCHEDULIG AD RESOURCE ALLOCATIO
More informationMethodology to Determine Relationships between Performance Factors in Hadoop Cloud Computing Applications
Methodology to Determne Relatonshps between Performance Factors n Hadoop Cloud Computng Applcatons Lus Eduardo Bautsta Vllalpando 1,2, Alan Aprl 1 and Alan Abran 1 1 Department of Software Engneerng and
More informationResource Scheduling Based on Dynamic Dependence Injection in Virtualization-based Simulation Grid
Proceedngs of the 200 4th Internatonal Conference on Computer Supported Cooperatve Work n Desgn Resource Schedulng Based on Dynamc Dependence Injecton n Vrtualzaton-based Smulaton Grd Hanbng Lu,Hongy Su,
More informationAn MILP model for planning of batch plants operating in a campaign-mode
An MILP model for plannng of batch plants operatng n a campagn-mode Yanna Fumero Insttuto de Desarrollo y Dseño CONICET UTN yfumero@santafe-concet.gov.ar Gabrela Corsano Insttuto de Desarrollo y Dseño
More informationDocument Clustering Analysis Based on Hybrid PSO+K-means Algorithm
Document Clusterng Analyss Based on Hybrd PSO+K-means Algorthm Xaohu Cu, Thomas E. Potok Appled Software Engneerng Research Group, Computatonal Scences and Engneerng Dvson, Oak Rdge Natonal Laboratory,
More informationGenetic Algorithm Based Optimization Model for Reliable Data Storage in Cloud Environment
Advanced Scence and Technology Letters, pp.74-79 http://dx.do.org/10.14257/astl.2014.50.12 Genetc Algorthm Based Optmzaton Model for Relable Data Storage n Cloud Envronment Feng Lu 1,2,3, Hatao Wu 1,3,
More informationAN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE
AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE Yu-L Huang Industral Engneerng Department New Mexco State Unversty Las Cruces, New Mexco 88003, U.S.A. Abstract Patent
More informationPeriod and Deadline Selection for Schedulability in Real-Time Systems
Perod and Deadlne Selecton for Schedulablty n Real-Tme Systems Thdapat Chantem, Xaofeng Wang, M.D. Lemmon, and X. Sharon Hu Department of Computer Scence and Engneerng, Department of Electrcal Engneerng
More informationPatterns Antennas Arrays Synthesis Based on Adaptive Particle Swarm Optimization and Genetic Algorithms
IJCSI Internatonal Journal of Computer Scence Issues, Vol. 1, Issue 1, No 2, January 213 ISSN (Prnt): 1694-784 ISSN (Onlne): 1694-814 www.ijcsi.org 21 Patterns Antennas Arrays Synthess Based on Adaptve
More informationDynamic Scheduling of Emergency Department Resources
Dynamc Schedulng of Emergency Department Resources Junchao Xao Laboratory for Internet Software Technologes, Insttute of Software, Chnese Academy of Scences P.O.Box 8718, No. 4 South Fourth Street, Zhong
More informationA Prefix Code Matching Parallel Load-Balancing Method for Solution-Adaptive Unstructured Finite Element Graphs on Distributed Memory Multicomputers
Ž. The Journal of Supercomputng, 15, 25 49 2000 2000 Kluwer Academc Publshers. Manufactured n The Netherlands. A Prefx Code Matchng Parallel Load-Balancng Method for Soluton-Adaptve Unstructured Fnte Element
More informationAn Energy-Efficient Data Placement Algorithm and Node Scheduling Strategies in Cloud Computing Systems
2nd Internatonal Conference on Advances n Computer Scence and Engneerng (CSE 2013) An Energy-Effcent Data Placement Algorthm and Node Schedulng Strateges n Cloud Computng Systems Yanwen Xao Massve Data
More informationGender Classification for Real-Time Audience Analysis System
Gender Classfcaton for Real-Tme Audence Analyss System Vladmr Khryashchev, Lev Shmaglt, Andrey Shemyakov, Anton Lebedev Yaroslavl State Unversty Yaroslavl, Russa vhr@yandex.ru, shmaglt_lev@yahoo.com, andrey.shemakov@gmal.com,
More informationA Genetic Algorithm Based Approach for Campus Equipment Management System in Cloud Server
JOURNAL OF ELECTRONIC SCIENCE AND TECHNOLOGY, VOL. 11, NO. 2, JUNE 2013 187 A Genetc Algorthm Based Approach for Campus Equpment Management System n Cloud Server Yu-Cheng Ln Abstract In ths paper, we proposed
More informationA QUANTITATIVE APPROACH TO CONSTRUCTION POLLUTION CONTROL BASED ON RESOURCE LEVELING
A QUANTITATIVE AOACH TO CONSTUCTION OLLUTION CONTOL BASED ON ESOUCE LEVELING Heng L 1, Zhen Chen 2, Conrad T C Wong 3 and eter E D Love 4 ABSTACT: A quanttatve approach for constructon polluton control
More informationBlending Roulette Wheel Selection & Rank Selection in Genetic Algorithms
Internatonal Journal of Machne Learnng and Computng, Vol. 2, o. 4, August 2012 Blendng Roulette Wheel Selecton & Rank Selecton n Genetc Algorthms Rakesh Kumar, Senor Member, IACSIT and Jyotshree, Member,
More informationPreventive Maintenance and Replacement Scheduling: Models and Algorithms
Preventve Mantenance and Replacement Schedulng: Models and Algorthms By Kamran S. Moghaddam B.S. Unversty of Tehran 200 M.S. Tehran Polytechnc 2003 A Dssertaton Proposal Submtted to the Faculty of the
More informationivoip: an Intelligent Bandwidth Management Scheme for VoIP in WLANs
VoIP: an Intellgent Bandwdth Management Scheme for VoIP n WLANs Zhenhu Yuan and Gabrel-Mro Muntean Abstract Voce over Internet Protocol (VoIP) has been wdely used by many moble consumer devces n IEEE 802.11
More informationPerformance Analysis and Coding Strategy of ECOC SVMs
Internatonal Journal of Grd and Dstrbuted Computng Vol.7, No. (04), pp.67-76 http://dx.do.org/0.457/jgdc.04.7..07 Performance Analyss and Codng Strategy of ECOC SVMs Zhgang Yan, and Yuanxuan Yang, School
More information行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告
行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告 畫 類 別 : 個 別 型 計 畫 半 導 體 產 業 大 型 廠 房 之 設 施 規 劃 計 畫 編 號 :NSC 96-2628-E-009-026-MY3 執 行 期 間 : 2007 年 8 月 1 日 至 2010 年 7 月 31 日 計 畫 主 持 人 : 巫 木 誠 共 同
More informationtaposh_kuet20@yahoo.comcsedchan@cityu.edu.hk rajib_csedept@yahoo.co.uk, alam_shihabul@yahoo.com
G. G. Md. Nawaz Al 1,2, Rajb Chakraborty 2, Md. Shhabul Alam 2 and Edward Chan 1 1 Cty Unversty of Hong Kong, Hong Kong, Chna taposh_kuet20@yahoo.comcsedchan@ctyu.edu.hk 2 Khulna Unversty of Engneerng
More informationResearch of concurrency control protocol based on the main memory database
Research of concurrency control protocol based on the man memory database Abstract Yonghua Zhang * Shjazhuang Unversty of economcs, Shjazhuang, Shjazhuang, Chna Receved 1 October 2014, www.cmnt.lv The
More informationAn Optimal Model for Priority based Service Scheduling Policy for Cloud Computing Environment
An Optmal Model for Prorty based Servce Schedulng Polcy for Cloud Computng Envronment Dr. M. Dakshayn Dept. of ISE, BMS College of Engneerng, Bangalore, Inda. Dr. H. S. Guruprasad Dept. of ISE, BMS College
More informationThe Network flow Motoring System based on Particle Swarm Optimized
The Network flow Motorng System based on Partcle Swarm Optmzed Neural Network Adult Educaton College, Hebe Unversty of Archtecture, Zhangjakou Hebe 075000, Chna Abstract The compatblty of the commercal
More information