DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT
|
|
- Allyson Wheeler
- 5 years ago
- Views:
Transcription
1 Iteratioal Joural of Iformatio Techology ad Kowledge Maagemet July-December 20, Volume 4, No. 2, pp DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT Maish Arora & M. Syamala Devi 2 Traditioal algorithms are suitable whe steps of algorithm are to be executed i a sequece ad at a sigle locatio. These algorithms have limitatios, whe used i multi-aget eviromet, where differet agets of sigle applicatio ru o differet odes, thus emphasizig the eed for distributed algorithms. Agets i multi-aget systems perform task idepedetly ad share the result with other agets. This motivates to use distributed algorithm, where tasks of the busiess process are distributed amog agets, so that they ca perform i parallel ad idepedetly. This paper presets a distributed algorithm for multi aget systems with case study of budget allocatio i web-based eviromet. The algorithm is based o heuristic approach. Three agets of systems perform differet tasks of budget allocatio procedure like iformatio gatherig, filterig, evaluatig ad budget allocatio at differet locatios ad timigs. This approach takes advatage of distributig ad parallel computig. Keywords: Distributed Algorithm, JADE, Multi Aget System.. INTRODUCTION Distributed algorithms have advatages over traditioal algorithm i multi aget eviromet where may agets operate i eviromet, gather iformatio from eviromet ad act accordigly. Distributed algorithms are efficiet algorithms as compared to traditioal oes that ru i a particular order. A distributed algorithm is desiged ad implemeted for multi aget eviromet. The aim is to allocate budget to deservig fud seekers whe fuds are limited. Agets of system evaluate the proposals techically ad fiacially ad the fially allocate budget after rakig proposals. The structure of the paper is as follows: sectio 2 briefs the backgroud ad related work. Sectio 3 details the budget allocatio problem. Sectio 4 describes multi aget approach to solve the budget allocatio problem. Sectio 5 defied traditioal algorithm to allocate budget, while sectio 6 describes distributed algorithm for multi aget eviromet. Sectio 7 shows the implemetatio of agets ad algorithm usig aget developmet tools. 2. BACKGROUND AND RELATED WORK A Aget is a autoomous etity, which performs a give task usig iformatio gathered from its eviromet to act i a suitable maer to complete the task successfully. Aget must be able to chage its behavior based o chages occurrig i its eviromet. A Aget has characteristics of reactivity, autoomy, collaborative behavior, DOEACC Society, Chadigarh Cetre, Chadigarh, INDIA 2 Departmet of Computer Sciece ad Applicatio, Pajab Uiversity, Patiala, INDIA id_maish@yahoo.com, 2 symala@pu.ac.i commuicatio act, mobility, proactive, adaptability ad iferetial capabilities []. A Multi Aget Systems (MAS) cosist of umber of agets that iteract with oe aother. Agets act o the behalf of users/other agets with differet goals ad motivatio. The Agets i MAS work i a team to achieve commo goal by iteractig with oe aother [2]. Agets perform task as a part of their actios. This could be ay scietific computatio or busiess logic. The steps to be performed are represeted as a algorithm ad implemeted usig aget developmet tool. A algorithm is well-defied computatioal procedure that takes some value as iput ad produces some value or set of values as output. Algorithm is thus a sequece of steps that trasforms iput ito output [3]. Algorithm ca be executed i sequetial, parallel or distributed maer. Sequetial algorithm or traditioal algorithm performs steps i a particular sequece at a sigle hardware locatio. With the evolutio of techologies i the area of multiprocessor system or multi taskig capabilities i a sigle processor, the focus of researchers moved from traditioal approach to parallel or distributed algorithm. If traditioal algorithms are executed i multiprocessor computers or etworked computers, these computers would be uderutilized. Moreover, majority of the busiess processes have some tasks that ca be performed idepedetly. Executig such algorithms over etworked machies, multiprocessor machies or sigle processor capable of multitaskig is cost ieffective i terms of CPU utilizatio. Distributed algorithm is desiged to ru o multiple computatioal odes. Nodes could be computer coected i etwork, a process or a thread. Node carries out a task or part of the algorithm ad commuicates with others by passig messages. Differet odes perform differet tasks
2 520 MANISH ARORA & M. SYAMALA DEVI of the same algorithm at the same time. Distributed algorithms have advatage of iheret parallelism ad scalability. Node, executig a part of algorithm, has limited iformatio about what the other odes, executig other parts of same algorithm, have iformatio with them. A fully decetralized algorithm provides a atural path for parallelism [4]. Oe major challege i desigig distributed algorithm is successful coordiatig behavior i the evet of processor failure or commuicatio lik failure, so these algorithms must be robust eough to hadle such situatios without affectig the overall executio of process. Distributed algorithms are also desiged to exchage iformatio, share resource, icrease reliability, ad icrease performace due to parallelism. These algorithms are suitable for wide rage of applicatio i the area of Telecommuicatio, Distributed Iformatio Processig ad Scietific Computatio. The algorithm of multi-aget systems differs from that of traditioal computatio sciece due to dyamic eviromet. Visualizatio agets, their actio ad behavior ca properly defie the algorithm [5]. Traditioal algorithms are foud usuitable or cost ieffective whe implemeted i multi-aget system due to followig reasos. (i) I multi aget system, differet agets perform differet tasks of the problem idepedetly. (ii) Agets reside o differet machies/odes. (iii) Solutio, i traditioal algorithm, is foud i cetralized, sequetial ad determiistic eviromet while i multi-aget system, solutio is obtaied as result of distributed iteractio of agets. (iv) I case of multi aget system, if traditioal algorithm is used, sequece of evets is very importat ad requires mutual exclusio. I case, a aget, performig oe actio, requires some kid of resources, it has to broadcast request to all the agets operatig i eviromet for the required resource. If aget receives, clear sigal from every aget oly the it ca use the resource. If ay other participatig aget declies the resource, requestig aget will have to wait. Failure i coectio or commuicatio liks durig this process leads to delay i executig the process or algorithm. May owadays applicatios are based o distributed computatio; it may be readig or browsig Iteret etc. Some form of distributed computig is ivolved, ragig from simple cliet server computig to grid computig. I web applicatio, server process keeps providig iformatio to other cliet processes, eve if, some of them fail or get discoected. Web image retrieval usig multi-aget techology uses distributed algorithm, where agets searches the images with characteristics like color ad shape stored o differet locatios. Images are grouped together ad mobile aget searches from these groups. The images are raked accordig to similarities i features ad are show to cliet [6]. Distributed algorithms are beig used i various multi aget systems like schedulig, productio ad risk allocatios [7-0] Based o backgroud, it is observed that i multi aget applicatio, busiess logic ca be depicted as distributed algorithm ad implemeted accordigly. The parts of algorithms are executed by agets o differet odes. O similar lies, a distributed algorithm has bee desiged to allocate budget to deservig fud seekers ad implemeted for multi-aget budget allocatio problem i web based eviromet. 3. BUDGET ALLOCATION PROBLEM Budget allocatio problem occurs whe limited fuds are to be allocated to most deservig ad competet fud seekers. These fuds are allocated to fud seekers to execute their projects. I Idia, lots of fuds are allocated i various areas like educatio, research & developmet ad social orieted schemes. Fuds seekers submit project proposals ad these proposals are filtered accordig to criteria set by fud allocator. The proposals are the evaluated techically ad fiacially. Both quatifiable ad o-quatifiable decisio-makig factors are cosidered to rak the projects. Weightage is give to each decisio-makig criterio. After rakig, budget is allocated accordig to availability. Quatificatio of o-quatifiable factors is doe usig heuristic approach ad fuzzy system []. From the review of curret practices ad expert views, five high level decisio makig factors are idetified; Solutio Delivery & Cotributio, Techical, Fiacial, Capacity & Expertise ad Risk Maagemet. 4. MULTI-AGENT BASED BUDGET ALLOCATION Based o the problem metioed above, a multi-aget system for resource (budget) allocatio is desiged that iteracts with users (fud seekers, fud allocator ad reviewer) through web-based iterface. The system has back support of database to share iformatio betwee agets eve if, agets are off lie due to some reaso. Three agets have bee desiged based o requiremets of actios, resposibilities ad autoomy. The Fig. shows the model of complete web based budget allocatio system usig multi-aget techology amed as Multi Aget System for Resource Allocatio ad Moitorig (MASRAM). () Coordiator Aget Coordiator Aget iteracts with three types of users of MASRAM i.e. Fud Seeker user, Fud Allocator user ad Reviewer guser. Fud Seeker user seeks fuds, Fud
3 DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT 52 Allocator user allocates fuds ad moitors the utilizatio while Review user reviews the allocatio. sufficiet fuds are available, all the qualified proposals are give fuds accordig to their eed. I secod case, where fuds are more tha weighted required ad less tha total requiremet, fuds are allocated accordig to weight. I third possibility, fuds are allocated proportioally accordig to weighted requiremet. The steps have bee show i Fig.2. Fig. : Architecture of Budget Allocatio (2) Fud Seeker Aget Fud Seeker Aget receives all the requests set by Coordiator Aget ad act accordigly. This aget iteracts with Coordiator Aget oly. (3) Fud Allocator ad Moitor Aget Fud Allocator ad Moitor Aget i tur evaluates proposal, assigs weights ad allocates suitable fuds based o allocatio procedure. Fud Allocator ad Moitor Aget processes all the requests received from Coordiator Aget. Steps ivolved i budget allocatio are: (i) Iformatio Gatherig Phase: I this phase, required iformatio is gathered from user as iput like complete proposal details, fud available, fuds already allocated ad criteria to qualify for availig fuds. (ii) Filterig Phase: I this phase, proposals are checked agaist the criteria set by allocator. Those proposals are cosidered for allocatios who qualify, remaiig proposals are rejected. (iii) Evaluatig Phase: Filterig phase evaluates proposals with respect to decisio-makig criteria. A umerical value is calculated agaist each criterio. Accumulated assiged values helps i rakig the projects. (iv) Allocatig Phase: Allocatig phase allocates budget based o availability ad rak of the proposal. The allocatio could be zero or 00 percet. Three possibilities are there; oe whe Fig. 2: Budget Allocatio Phases 5. ALGORITHM STEPS This sectio describes all four phases metioed above to allocate budget mathematically. Iformatio gatherig phase is covered i step I. Steps II ad III belog to filterig phase, steps IV ad V detail evaluatig phase ad step VI represets allocatig phase as show i Table. The procedures i table are detailed further. Step I Step II Step III Step IV Step V Step VI Table Traditioal Algorithm Do iitialize()//iitializatio Repeat step III to step VI for p = to m Do match_criteria() //Matchig Criteria Do evaluate() //Evaluatig Proposals Do assig_weight() //Assigig Weights to Proposals Do allocate() //Allocatig Fuds
4 522 MANISH ARORA & M. SYAMALA DEVI Procedure iitialize() Table 2 Iitializatio Let R = {R, R2, R3 Rm} be set of resources (fuds) for a particular category of fuds. Let Ai, <=i<= be fud seekers requirig fuds. Let Xi,j be the fuds requiremet by ith fud seeker from jth fud category. Let r be umber of Decisio Makig Factors (DMF). Let CMINi, <=i<=r be miimum requiremet for ith criteria. Let Ci,j be the criteria value of ith fud seeker jth criteria. <=i<=, <=j<=r. Let EVALij be evaluatio matrix where <=i<= ad <=j<=r. Let W = {W, W2, W3 W} be set of weight assiged to ith proposal. Let ARi,j be fud allotted matrix to ith fud seeker from jth resource. Let PROJECT_STATUSi stores whether proposal qualified for allocatio or ot. Procedure match_criteria() For i = to for For j = to r If (CMIN j < C i,j the Else if for Table 3 Filterig Procedure Project_status i = Rejected X i, j 0 Procedure evaluate() Begi For i = to For j = to r Project_status i = Qualified Table 4 Evaluatig Procedure If(PROPJECT_STATUS i = QUALIFIED if for for ; do Evaluate_cri(i,j) // calls procedure to evaluate proposals Table 5 Weight Assigmet Procedure Procedure assig_weight() For i = to r For j = to If(PROPJECT_STATUS i = QUALIFIED = K i * /EVAL k,i ; if for for W i = Geometric Mea ( ), <=i<= ad <=j<=r ad PROPJECT_STATUS i = QUALIFIED Procedure do allocate () beig ed Table 6 Fial Allocatio Procedure Xi, j if Rj Xp, j p= Ri, j Wi * Xi, j if Wp * Xp, j Rj Xp, j p= p= Wi * Xi, j Rj Otherwise Wi * Xp, j p= 6. DISTRIBUTED ALGORITHM TO ALLOCATE BUDGET Agets of the system perform actios at differet time ad at differet locatio. The steps metioed i previous sectio cover all the actios performed by agets at differet times ad locatios. Hece it becomes importat that algorithm may be distributed oe. Though agets perform task idepedetly, yet they eed to share iformatio with other agets to accomplish overall goal of the system. Table 8 shows the distributio of tasks of algorithm amog agets. Table 7 Evaluate Procedure Procedure evaluate_cri(i,j) Begi If(j = ) the Fid total umber of core keywords i i th proposal ad let it be kw EVAL i, j Else if (j = 2) the
5 DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT 523 Fid total umber cadidates to be traied i i th proposal ad let it be kw EVAL i, j Else if (j = 3) the Fid total umber atioal developmet ad social impact keywords i i th proposal ad let it be kw EVAL i, j Else if (j = 4) the Fid total umber techical used keywords i i th proposal ad let it be kw EVAL i, j Else if (j = 5) the Let tpc be the total projects completed by i th fud seeker Let tpd be the total projects delayed by i th fud seeker Let tp be the total projects hadled by i th fud seeker prob_tpc = tpc/tp prob_tpd = tpd/tp prob_either = (prob_tpc + prob_tpd)-(prob_tpc * prob_tpd) prob_either Else if (j = 6) the Let tb be total budget proposed by i th fud seeker Let tr be total budget required by i th fud seeker tr/tb Else if (j = 7) the // time beig Else if (j = 8) the Let s be sum of ifrastructure available (ifrastructure ID wise) for all the qualified fud seeker ifrastructure available for i th fud seeker Else if (j = 9) the Fid total umber maagemet capability keywords i i th proposal ad let it be kw Else if (j = 0) the Let s be sum of mapower available (Desigatio wise) for all the qualified fud seeker staff(i) mapower available for i th fud seeker Else if (j = ) the - EVAL i,6 Else if (j = 2) the if Aget Fud Seeker Fud Allocator ad Moitor Coordiator Aget Table 8 Tasks Allocatio Steps of Algorithm Step I, II ad III Step IV, V ad VI To iteract with user through web based iterface Agets ca also work i parallel, e.g. Fud Seeker aget ca be busy i gatherig iformatio from Fud Seeker FS while Fud Allocator ad Moitor Aget is may be i evaluatig ad allocatig budget to FS2 ad FS3 fud seekers. Fud Seeker Aget passes the iformatio to Fud Allocator ad Moitor Aget through database support ad well-defied otology [2]. Distributed Algorithm completes the task whe all participatig agets complete their tasks. Step IV of the algorithm is further divided ito multiple tasks eablig us to use multi threadig. There are 2 differet decisio makig factors categorized ito five high level factors as discussed i previous sectio. These are idepedet except 5. as is it depedet o 2.2 (Table 3). The computatios of these factors are multithreaded takig advatage of both parallel ad distributed eviromet. The distributed algorithm is described i table 9. Table 9 Distributed Algorithm // Distributed Algorithm Begi Thread FS_thread Requests aget Fud Seeker Aget to provide fud requiremet from fud seeker user Thread FA_thread Requests aget Fud Allocator ad Moitor Aget to provide takes iformatio from fud seeker aget Do while fud requiremet foud ad budget foud Begi //assig task to Fud Allocator ad Moitor Aget Do iitialize() For I = to m // allocatig categories Create thread t i = budget() // calls budget procedure for Thread_wait //Wait for all the active threads to fiish Table 0 Distributed Algorithm (Allocatio Procedure) //budget procedure do match_criteria() do evaluate_da(i) do assig_weight() do allocate_fuds() ed procedure evaluate_da(i) for j = to r//o. of decisio makig factors create thread t ij =evaluate() // calls evaluate procedure ed for thread_wait // waits for all the active threads to fiish 7. IMPLEMENTATION The above metioed algorithm is implemeted i web based multi aget system for resource allocatio ad moitorig. All the three agets reside o server side. Two servers are used for aget-based applicatio: oe as database
6 524 MANISH ARORA & M. SYAMALA DEVI server ad secod as aget server. Aget Server hosts all three agets. Three types of users iteract with agets from cliet machie through Graphical User Iterface (GUI). Iterface programs to iteract with the users are implemeted usig JSP (Java Server Pages). Agets are implemeted usig JADE, Java Aget Developmet Framework, a FIPA (Foudatio of Itelliget Physical Agets) compliat framework to develop agets, ad oracle is used as backed database. The iteractio betwee agets ad database is through Java busiess classes [3]. Iformatio gatherig task has bee distributed betwee two agets; Fud Seeker Aget ad Fud Allocator & Moitor Aget. Fud Seeker Aget seeks iformatio from fud seeker user while Fud Allocator & Moitor Aget seeks iformatio from Fud allocator user ad reviewer user. Both store the iformatio i database. Fud Allocator & Moitor Aget from time to time seses the requests to Table Budget Requiremet ad Allocatio allocate fuds ad does the remaiig phases of filterig, evaluatig ad allocatig. To evaluate proposals, separate eleve threads are started oe each for eleve idepedet decisio-makig factors. This is takes advatage of parallelism. Table shows the Budget requiremet ad budget allocatio of three projects i two slots. At first time, Fud Allocator & Moitor Aget fids oly oe proposal ad durig ext slot, it fids two proposals. The proposals are raked after evaluatio ad assigig weights. Project ID 8 is allotted full amout of budget required as it was available, but Project ID 48 ad 6 are allocated proportioately accordig to weight ad rak sice limited fuds are available as show i Table 2 alog with criteria ad fuds available. Project Id Category Allocato r ID Seeker ID Budget Weightag Allocated Slot No. Rak Required e Budget Table 2 Miimum Criteria Allocatio ID Category Criteria Mi Available For R & D Mi Experiece of Seeker Already Doe similar projects For quality Educatio Mi Staff Member Mi Experiece of Seeker 0 Already Doe similar projects 2 Table 3 shows the decisio-makig factors ad their weightage i allocatio of budget. Table 4 shows the result of evaluatio of proposals agaist these decisio-makig factors. First proposals are evaluated agaist these factors ad the weightage is give accordig to decisio-makig weights. Table 3 Weightage of Decisio Makig Factors Decisio Makig Id Decisio Makig Factor Decisio Makig Weight. Core Area HR Developmet Natioal Developmet ad Social Impact Available Techology Success Probability Cost Ivolved ECO Beefit Ifrastructure Maagemet Capability Staff Experiece Project Completio Risk Implemetatio Risk.06
7 DISTRIBUTED ALGORITHM FOR MULTI-AGENT ENVIRONMENT 525 Table 4 Calculated Weights Project Id - 48 Project Id - 6 Project Id - 8 Decisio Evaluated Decisio Evaluated Decisio Makig Makig Value Makig Value Makig Value ID ID ID CONCLUSION I multi-aget systems, agets perform differet tasks at differet locatios ad time to achieve their idividual goals ad overall goal of the system. Traditioal algorithms to allocate budget were foud usuitable due to their characteristics of orderly executio ad that too at a sigle locatio i multi aget eviromet. The distributed algorithm to allocate budget i multi-aget eviromet removes the limitatio of traditioal algorithms. Parts of the budget allocatio problem were distributed amog two agets. Durig allocatio procedure, further multithreadig is used. This distributed algorithm to allocate budget foud fit for multi aget eviromet. This procedure takes advatage of parallel ad distributig computatio. REFERENCES [] Associatio of Advacemet of Artificial Itelligece, Available at accessed o April 0, [2] Jarg Deziger, Multi Aget Systems, Departmet of Computer Sciece, Uiversity of Calgary, Caada, Available at witer2006/slides/04-masdef-hadout.pdf, accessed o April, [3] Thomas H. Corme et al., Itroductio to Algorithm, Secod editio, MIT Press, Cambridge, Massachusetts Lodo, Eglad, 200. [4] Raz Nissim, et al., A Geeral, Fully Distributed Multi-Aget Plaig Algorithm,9 th Iteratioal Coferece o Autoomous Agets ad Multi Aget Systems, AAMAS, Toroto, pp , 200. [5] Jose M. Vidal et al., The Past ad Future of Multi Aget System, AAMAS Workshop o Teachig Multi-Aget Systems, [6] Alaa M. Riad, et al., A Itelliget Distributed Algorithm for Efficiet Web Images Retrieval, Iteratioal Joural of Commuicatio, pp 63-76, [7] Ro Xie, et al, Schedulig Multi-Task Multi Aget Systems, Proceedig o 5 th Iteratioal Coferece o Autoomous Agets, ACM New York, 200 [8] Masahiro Oo, et al, Market Based Risk Allocatio for Multi Aget System, Proceedig o 9 th Iteratioal Coferece o Autoomous Agets ad Multi Aget Systems,, AAMAS 0, 200. [9] Toru Ishida, Parallel, Distributed ad Multi-Aget Productio Systems -A Research Foudatio for Distributed Artificial Itelligece, Proceedigs of the First Iteratioal Coferece o Multi Aget Systems, pp , 995. [0] Sebastie Paquet et al., Multi-aget Systems Viewed as Distributed Schedulig Systems: Methodology ad Experimets, Advaces i Artificial Itelligece, Lecture Notes i Computer Sciece (Sprigerlik), vol 350, [] Ji Cheg, Haipig Bai ad Zipig Li, Quatificatio of No Quatitative Idicators of Performace Measuremet, Wireless Commuicatios, Networkig ad Mobile Computig, WiCOM 08. 4th Iteratioal Coferece, page(s): -5, [2] Maish Arora, M. Syamala Devi, Otology Based Aget Commuicatio i Resource Allocatio ad Moitorig, IJCSI Iteratioal Joural of Computer Sciece Issues, 7, Issue 6, November 200, ISSN (Olie): [3] Maish Arora, M. Syamala Devi, Role of Database i Resource Allocatio Problem, Iteratioal Joural of Computer Sciece ad Iformatio Techology, 2(2),pp , 20.
Ones Assignment Method for Solving Traveling Salesman Problem
Joural of mathematics ad computer sciece 0 (0), 58-65 Oes Assigmet Method for Solvig Travelig Salesma Problem Hadi Basirzadeh Departmet of Mathematics, Shahid Chamra Uiversity, Ahvaz, Ira Article history:
More informationEvaluation scheme for Tracking in AMI
A M I C o m m u i c a t i o A U G M E N T E D M U L T I - P A R T Y I N T E R A C T I O N http://www.amiproject.org/ Evaluatio scheme for Trackig i AMI S. Schreiber a D. Gatica-Perez b AMI WP4 Trackig:
More information3D Model Retrieval Method Based on Sample Prediction
20 Iteratioal Coferece o Computer Commuicatio ad Maagemet Proc.of CSIT vol.5 (20) (20) IACSIT Press, Sigapore 3D Model Retrieval Method Based o Sample Predictio Qigche Zhag, Ya Tag* School of Computer
More informationCOSC 1P03. Ch 7 Recursion. Introduction to Data Structures 8.1
COSC 1P03 Ch 7 Recursio Itroductio to Data Structures 8.1 COSC 1P03 Recursio Recursio I Mathematics factorial Fiboacci umbers defie ifiite set with fiite defiitio I Computer Sciece sytax rules fiite defiitio,
More informationCS 683: Advanced Design and Analysis of Algorithms
CS 683: Advaced Desig ad Aalysis of Algorithms Lecture 6, February 1, 2008 Lecturer: Joh Hopcroft Scribes: Shaomei Wu, Etha Feldma February 7, 2008 1 Threshold for k CNF Satisfiability I the previous lecture,
More informationGE FUNDAMENTALS OF COMPUTING AND PROGRAMMING UNIT III
GE2112 - FUNDAMENTALS OF COMPUTING AND PROGRAMMING UNIT III PROBLEM SOLVING AND OFFICE APPLICATION SOFTWARE Plaig the Computer Program Purpose Algorithm Flow Charts Pseudocode -Applicatio Software Packages-
More informationAn Improved Shuffled Frog-Leaping Algorithm for Knapsack Problem
A Improved Shuffled Frog-Leapig Algorithm for Kapsack Problem Zhoufag Li, Ya Zhou, ad Peg Cheg School of Iformatio Sciece ad Egieerig Hea Uiversity of Techology ZhegZhou, Chia lzhf1978@126.com Abstract.
More informationChapter 4 Threads. Operating Systems: Internals and Design Principles. Ninth Edition By William Stallings
Operatig Systems: Iterals ad Desig Priciples Chapter 4 Threads Nith Editio By William Stalligs Processes ad Threads Resource Owership Process icludes a virtual address space to hold the process image The
More informationSectio 4, a prototype project of settig field weight with AHP method is developed ad the experimetal results are aalyzed. Fially, we coclude our work
200 2d Iteratioal Coferece o Iformatio ad Multimedia Techology (ICIMT 200) IPCSIT vol. 42 (202) (202) IACSIT Press, Sigapore DOI: 0.7763/IPCSIT.202.V42.0 Idex Weight Decisio Based o AHP for Iformatio Retrieval
More informationTask scenarios Outline. Scenarios in Knowledge Extraction. Proposed Framework for Scenario to Design Diagram Transformation
6-0-0 Kowledge Trasformatio from Task Scearios to View-based Desig Diagrams Nima Dezhkam Kamra Sartipi {dezhka, sartipi}@mcmaster.ca Departmet of Computig ad Software McMaster Uiversity CANADA SEKE 08
More informationSoftware development of components for complex signal analysis on the example of adaptive recursive estimation methods.
Software developmet of compoets for complex sigal aalysis o the example of adaptive recursive estimatio methods. SIMON BOYMANN, RALPH MASCHOTTA, SILKE LEHMANN, DUNJA STEUER Istitute of Biomedical Egieerig
More informationA SOFTWARE MODEL FOR THE MULTILAYER PERCEPTRON
A SOFTWARE MODEL FOR THE MULTILAYER PERCEPTRON Roberto Lopez ad Eugeio Oñate Iteratioal Ceter for Numerical Methods i Egieerig (CIMNE) Edificio C1, Gra Capitá s/, 08034 Barceloa, Spai ABSTRACT I this work
More informationChapter 1. Introduction to Computers and C++ Programming. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 1 Itroductio to Computers ad C++ Programmig Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 1.1 Computer Systems 1.2 Programmig ad Problem Solvig 1.3 Itroductio to C++ 1.4 Testig
More informationInterference Aware Channel Assignment Scheme in Multichannel Wireless Mesh Networks
Iterferece Aware Chael Assigmet Scheme i Multichael Wireless Mesh Networks Sumyeg Kim Departmet of Computer Software Egieerig Kumoh Natioal Istitute of Techology Gum South Korea Abstract Wireless mesh
More informationAnalysis of Server Resource Consumption of Meteorological Satellite Application System Based on Contour Curve
Advaces i Computer, Sigals ad Systems (2018) 2: 19-25 Clausius Scietific Press, Caada Aalysis of Server Resource Cosumptio of Meteorological Satellite Applicatio System Based o Cotour Curve Xiagag Zhao
More informationElementary Educational Computer
Chapter 5 Elemetary Educatioal Computer. Geeral structure of the Elemetary Educatioal Computer (EEC) The EEC coforms to the 5 uits structure defied by vo Neuma's model (.) All uits are preseted i a simplified
More informationFREQUENCY ESTIMATION OF INTERNET PACKET STREAMS WITH LIMITED SPACE: UPPER AND LOWER BOUNDS
FREQUENCY ESTIMATION OF INTERNET PACKET STREAMS WITH LIMITED SPACE: UPPER AND LOWER BOUNDS Prosejit Bose Evagelos Kraakis Pat Mori Yihui Tag School of Computer Sciece, Carleto Uiversity {jit,kraakis,mori,y
More informationMulti-Threading. Hyper-, Multi-, and Simultaneous Thread Execution
Multi-Threadig Hyper-, Multi-, ad Simultaeous Thread Executio 1 Performace To Date Icreasig processor performace Pipeliig. Brach predictio. Super-scalar executio. Out-of-order executio. Caches. Hyper-Threadig
More informationAppendix D. Controller Implementation
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Appedix D Cotroller Implemetatio Cotroller Implemetatios Combiatioal logic (sigle-cycle); Fiite state machie (multi-cycle, pipelied);
More informationArchitectural styles for software systems The client-server style
Architectural styles for software systems The cliet-server style Prof. Paolo Ciacarii Software Architecture CdL M Iformatica Uiversità di Bologa Ageda Cliet server style CS two tiers CS three tiers CS
More informationOptimization for framework design of new product introduction management system Ma Ying, Wu Hongcui
2d Iteratioal Coferece o Electrical, Computer Egieerig ad Electroics (ICECEE 2015) Optimizatio for framework desig of ew product itroductio maagemet system Ma Yig, Wu Hogcui Tiaji Electroic Iformatio Vocatioal
More informationData diverse software fault tolerance techniques
Data diverse software fault tolerace techiques Complemets desig diversity by compesatig for desig diversity s s limitatios Ivolves obtaiig a related set of poits i the program data space, executig the
More informationWhat are Information Systems?
Iformatio Systems Cocepts What are Iformatio Systems? Roma Kotchakov Birkbeck, Uiversity of Lodo Based o Chapter 1 of Beett, McRobb ad Farmer: Object Orieted Systems Aalysis ad Desig Usig UML, (4th Editio),
More information1 Enterprise Modeler
1 Eterprise Modeler Itroductio I BaaERP, a Busiess Cotrol Model ad a Eterprise Structure Model for multi-site cofiguratios are itroduced. Eterprise Structure Model Busiess Cotrol Models Busiess Fuctio
More informationEnhancing Cloud Computing Scheduling based on Queuing Models
Ehacig Cloud Computig Schedulig based o Queuig Models Mohamed Eisa Computer Sciece Departmet, Port Said Uiversity, 42526 Port Said, Egypt E. I. Esedimy Computer Sciece Departmet, Masoura Uiversity, Masoura,
More informationA Hierarchical Load Balanced Fault tolerant Grid Scheduling Algorithm with User Satisfaction
A Hierarchical Load Balaced Fault tolerat Grid Schedulig Algorithm with User Satisfactio 1 KEERTHIKA P, 2 SURESH P Assistat Professor (Seior Grade), Departmet o Computer Sciece ad Egieerig Assistat Professor
More informationService Oriented Enterprise Architecture and Service Oriented Enterprise
Approved for Public Release Distributio Ulimited Case Number: 09-2786 The 23 rd Ope Group Eterprise Practitioers Coferece Service Orieted Eterprise ad Service Orieted Eterprise Ya Zhao, PhD Pricipal, MITRE
More informationCopyright 2016 Ramez Elmasri and Shamkant B. Navathe
Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe CHAPTER 19 Query Optimizatio Copyright 2016 Ramez Elmasri ad Shamkat B. Navathe Itroductio Query optimizatio Coducted by a query optimizer i a DBMS Goal:
More informationΤεχνολογία Λογισμικού
ΕΘΝΙΚΟ ΜΕΤΣΟΒΙΟ ΠΟΛΥΤΕΧΝΕΙΟ Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών Τεχνολογία Λογισμικού, 7ο/9ο εξάμηνο 2018-2019 Τεχνολογία Λογισμικού Ν.Παπασπύρου, Αν.Καθ. ΣΗΜΜΥ, ickie@softlab.tua,gr
More informationAnalysis of Documents Clustering Using Sampled Agglomerative Technique
Aalysis of Documets Clusterig Usig Sampled Agglomerative Techique Omar H. Karam, Ahmed M. Hamad, ad Sheri M. Moussa Abstract I this paper a clusterig algorithm for documets is proposed that adapts a samplig-based
More informationLow Complexity H.265/HEVC Coding Unit Size Decision for a Videoconferencing System
BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 15, No 6 Special Issue o Logistics, Iformatics ad Service Sciece Sofia 2015 Prit ISSN: 1311-9702; Olie ISSN: 1314-4081 DOI:
More informationImprovement of the Orthogonal Code Convolution Capabilities Using FPGA Implementation
Improvemet of the Orthogoal Code Covolutio Capabilities Usig FPGA Implemetatio Naima Kaabouch, Member, IEEE, Apara Dhirde, Member, IEEE, Saleh Faruque, Member, IEEE Departmet of Electrical Egieerig, Uiversity
More informationCSC 220: Computer Organization Unit 11 Basic Computer Organization and Design
College of Computer ad Iformatio Scieces Departmet of Computer Sciece CSC 220: Computer Orgaizatio Uit 11 Basic Computer Orgaizatio ad Desig 1 For the rest of the semester, we ll focus o computer architecture:
More informationOutline. CSCI 4730 Operating Systems. Questions. What is an Operating System? Computer System Layers. Computer System Layers
Outlie CSCI 4730 s! What is a s?!! System Compoet Architecture s Overview Questios What is a?! What are the major operatig system compoets?! What are basic computer system orgaizatios?! How do you commuicate
More informationOntology-based Decision Support System with Analytic Hierarchy Process for Tour Package Selection
2017 Asia-Pacific Egieerig ad Techology Coferece (APETC 2017) ISBN: 978-1-60595-443-1 Otology-based Decisio Support System with Aalytic Hierarchy Process for Tour Pacage Selectio Tie-We Sug, Chia-Jug Lee,
More informationPanel for Adobe Premiere Pro CC Partner Solution
Pael for Adobe Premiere Pro CC Itegratio for more efficiecy The makes video editig simple, fast ad coveiet. The itegrated pael gives users immediate access to all medialoopster features iside Adobe Premiere
More informationCORD Test Project in Okinawa Open Laboratory
CORD Test Project i Okiawa Ope Laboratory Fukumasa Morifuji NTT Commuicatios Trasform your busiess, trasced expectatios with our techologically advaced solutios. Ageda VxF platform i NTT Commuicatios Expectatio
More informationPolitecnico di Milano Advanced Network Technologies Laboratory. Internet of Things. Projects
Politecico di Milao Advaced Network Techologies Laboratory Iteret of Thigs Projects 2016-2017 Politecico di Milao Advaced Network Techologies Laboratory Geeral Rules Geeral Rules o Gradig 26/30 are assiged
More informationPruning and Summarizing the Discovered Time Series Association Rules from Mechanical Sensor Data Qing YANG1,a,*, Shao-Yu WANG1,b, Ting-Ting ZHANG2,c
Advaces i Egieerig Research (AER), volume 131 3rd Aual Iteratioal Coferece o Electroics, Electrical Egieerig ad Iformatio Sciece (EEEIS 2017) Pruig ad Summarizig the Discovered Time Series Associatio Rules
More informationMorgan Kaufmann Publishers 26 February, COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 5
Morga Kaufma Publishers 26 February, 28 COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 5 Set-Associative Cache Architecture Performace Summary Whe CPU performace icreases:
More informationTowards Efficient Selection of Web Services
Towards Efficiet Selectio of Web Services Amir Padovitz School of Computer Sciece & Software Egieerig, Moash Uiversity Padovitz@bigpodcom Shoali Krishaswamy School of Computer Sciece & Software Egieerig,
More informationLoad balanced Parallel Prime Number Generator with Sieve of Eratosthenes on Cluster Computers *
Load balaced Parallel Prime umber Geerator with Sieve of Eratosthees o luster omputers * Soowook Hwag*, Kyusik hug**, ad Dogseug Kim* *Departmet of Electrical Egieerig Korea Uiversity Seoul, -, Rep. of
More informationSorting in Linear Time. Data Structures and Algorithms Andrei Bulatov
Sortig i Liear Time Data Structures ad Algorithms Adrei Bulatov Algorithms Sortig i Liear Time 7-2 Compariso Sorts The oly test that all the algorithms we have cosidered so far is compariso The oly iformatio
More informationVISUALSLX AN OPEN USER SHELL FOR HIGH-PERFORMANCE MODELING AND SIMULATION. Thomas Wiedemann
Proceedigs of the 2000 Witer Simulatio Coferece J. A. Joies, R. R. Barto, K. Kag, ad P. A. Fishwick, eds. VISUALSLX AN OPEN USER SHELL FOR HIGH-PERFORMANCE MODELING AND SIMULATION Thomas Wiedema Techical
More informationA Parallel DFA Minimization Algorithm
A Parallel DFA Miimizatio Algorithm Ambuj Tewari, Utkarsh Srivastava, ad P. Gupta Departmet of Computer Sciece & Egieerig Idia Istitute of Techology Kapur Kapur 208 016,INDIA pg@iitk.ac.i Abstract. I this
More informationOutline n Introduction n Background o Distributed DBMS Architecture
Outlie Itroductio Backgroud o Distributed DBMS Architecture Datalogical Architecture Implemetatio Alteratives Compoet Architecture o Distributed DBMS Architecture o Distributed Desig o Sematic Data Cotrol
More informationn Explore virtualization concepts n Become familiar with cloud concepts
Chapter Objectives Explore virtualizatio cocepts Become familiar with cloud cocepts Chapter #15: Architecture ad Desig 2 Hypervisor Virtualizatio ad cloud services are becomig commo eterprise tools to
More informationAdaptive Resource Allocation for Electric Environmental Pollution through the Control Network
Available olie at www.sciecedirect.com Eergy Procedia 6 (202) 60 64 202 Iteratioal Coferece o Future Eergy, Eviromet, ad Materials Adaptive Resource Allocatio for Electric Evirometal Pollutio through the
More informationA TRICKY TASK SCHEDULING TECHNIQUE TO OPTIMIZE TIME COST AND RELIABILITY IN MOBILE COMPUTING ENVIRONMENT
A TRICKY TASK SCHEDULING TECHNIQUE TO OPTIMIZE TIME COST AND RELIABILITY IN MOBILE COMPUTING ENVIRONMENT Faizul Navi Kha 1, Kapil Govil 2 1 Departmet of Computer Applicatio, Teerthaker Mahaveer Uiversity,
More informationSCI Reflective Memory
Embedded SCI Solutios SCI Reflective Memory (Experimetal) Atle Vesterkjær Dolphi Itercoect Solutios AS Olaf Helsets vei 6, N-0621 Oslo, Norway Phoe: (47) 23 16 71 42 Fax: (47) 23 16 71 80 Mail: atleve@dolphiics.o
More information. Written in factored form it is easy to see that the roots are 2, 2, i,
CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or
More informationPython Programming: An Introduction to Computer Science
Pytho Programmig: A Itroductio to Computer Sciece Chapter 1 Computers ad Programs 1 Objectives To uderstad the respective roles of hardware ad software i a computig system. To lear what computer scietists
More informationRunning Time. Analysis of Algorithms. Experimental Studies. Limitations of Experiments
Ruig Time Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Most algorithms trasform iput objects ito output objects. The
More informationImproving Information Retrieval System Security via an Optimal Maximal Coding Scheme
Improvig Iformatio Retrieval System Security via a Optimal Maximal Codig Scheme Dogyag Log Departmet of Computer Sciece, City Uiversity of Hog Kog, 8 Tat Chee Aveue Kowloo, Hog Kog SAR, PRC dylog@cs.cityu.edu.hk
More informationA New Morphological 3D Shape Decomposition: Grayscale Interframe Interpolation Method
A ew Morphological 3D Shape Decompositio: Grayscale Iterframe Iterpolatio Method D.. Vizireau Politehica Uiversity Bucharest, Romaia ae@comm.pub.ro R. M. Udrea Politehica Uiversity Bucharest, Romaia mihea@comm.pub.ro
More informationΤεχνολογία Λογισμικού
ΕΘΝΙΚΟ ΜΕΤΣΟΒΙΟ ΠΟΛΥΤΕΧΝΕΙΟ Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών Τεχνολογία Λογισμικού, 7ο/9ο εξάμηνο 2018-2019 Τεχνολογία Λογισμικού Ν.Παπασπύρου, Αν.Καθ. ΣΗΜΜΥ, ickie@softlab.tua,gr
More informationAn Algorithm to Solve Fuzzy Trapezoidal Transshipment Problem
Iteratioal Joural of Systems Sciece ad Applied Mathematics 206; (4): 58-62 http://www.sciecepublishiggroup.com/j/ssam doi: 0.648/j.ssam.206004.4 A Algorithm to Solve Fuzzy Trapezoidal Trasshipmet Problem
More informationSession Initiated Protocol (SIP) and Message-based Load Balancing (MBLB)
F5 White Paper Sessio Iitiated Protocol (SIP) ad Message-based Load Balacig (MBLB) The ability to provide ew ad creative methods of commuicatios has esured a SIP presece i almost every orgaizatio. The
More informationOptimization of Priority based CPU Scheduling Algorithms to Minimize Starvation of Processes using an Efficiency Factor
Iteratioal Joural of Computer Applicatios (97 8887) Volume 132 No.11, December21 Optimizatio of based CPU Schedulig Algorithms to Miimize Starvatio of Processes usig a Efficiecy Factor Muhammad A. Mustapha
More informationLecture 18. Optimization in n dimensions
Lecture 8 Optimizatio i dimesios Itroductio We ow cosider the problem of miimizig a sigle scalar fuctio of variables, f x, where x=[ x, x,, x ]T. The D case ca be visualized as fidig the lowest poit of
More informationThreads and Concurrency in Java: Part 1
Cocurrecy Threads ad Cocurrecy i Java: Part 1 What every computer egieer eeds to kow about cocurrecy: Cocurrecy is to utraied programmers as matches are to small childre. It is all too easy to get bured.
More informationEFFICIENT MULTIPLE SEARCH TREE STRUCTURE
EFFICIENT MULTIPLE SEARCH TREE STRUCTURE Mohammad Reza Ghaeii 1 ad Mohammad Reza Mirzababaei 1 Departmet of Computer Egieerig ad Iformatio Techology, Amirkabir Uiversity of Techology, Tehra, Ira mr.ghaeii@aut.ac.ir
More informationThreads and Concurrency in Java: Part 1
Threads ad Cocurrecy i Java: Part 1 1 Cocurrecy What every computer egieer eeds to kow about cocurrecy: Cocurrecy is to utraied programmers as matches are to small childre. It is all too easy to get bured.
More informationA Study on the Performance of Cholesky-Factorization using MPI
A Study o the Performace of Cholesky-Factorizatio usig MPI Ha S. Kim Scott B. Bade Departmet of Computer Sciece ad Egieerig Uiversity of Califoria Sa Diego {hskim, bade}@cs.ucsd.edu Abstract Cholesky-factorizatio
More informationComputers and Scientific Thinking
Computers ad Scietific Thikig David Reed, Creighto Uiversity Chapter 15 JavaScript Strigs 1 Strigs as Objects so far, your iteractive Web pages have maipulated strigs i simple ways use text box to iput
More informationKeywords Software Architecture, Object-oriented metrics, Reliability, Reusability, Coupling evaluator, Cohesion, efficiency
Volume 3, Issue 9, September 2013 ISSN: 2277 128X Iteratioal Joural of Advaced Research i Computer Sciece ad Software Egieerig Research Paper Available olie at: www.ijarcsse.com Couplig Evaluator to Ehace
More informationOn Nonblocking Folded-Clos Networks in Computer Communication Environments
O Noblockig Folded-Clos Networks i Computer Commuicatio Eviromets Xi Yua Departmet of Computer Sciece, Florida State Uiversity, Tallahassee, FL 3306 xyua@cs.fsu.edu Abstract Folded-Clos etworks, also referred
More informationGoals of the Lecture UML Implementation Diagrams
Goals of the Lecture UML Implemetatio Diagrams Object-Orieted Aalysis ad Desig - Fall 1998 Preset UML Diagrams useful for implemetatio Provide examples Next Lecture Ð A variety of topics o mappig from
More informationRange Free Localization Schemes For Wireless Sensor Networks
Rage Free Localizatio Schemes For Wireless Sesor Networks ASHOK KUMAR, VINAY KUMAR AND VINOD KAPOOR Departmet of Electroics ad Commuicatio Egieerig Natioal Istitute of Techology Hamirpur (HP) 177 005 INDIA
More informationAlgorithms for Disk Covering Problems with the Most Points
Algorithms for Disk Coverig Problems with the Most Poits Bi Xiao Departmet of Computig Hog Kog Polytechic Uiversity Hug Hom, Kowloo, Hog Kog csbxiao@comp.polyu.edu.hk Qigfeg Zhuge, Yi He, Zili Shao, Edwi
More informationBaan Finance Financial Statements
Baa Fiace Fiacial Statemets Module Procedure UP041A US Documetiformatio Documet Documet code : UP041A US Documet group : User Documetatio Documet title : Fiacial Statemets Applicatio/Package : Baa Fiace
More informationBayesian approach to reliability modelling for a probability of failure on demand parameter
Bayesia approach to reliability modellig for a probability of failure o demad parameter BÖRCSÖK J., SCHAEFER S. Departmet of Computer Architecture ad System Programmig Uiversity Kassel, Wilhelmshöher Allee
More informationNew HSL Distance Based Colour Clustering Algorithm
The 4th Midwest Artificial Itelligece ad Cogitive Scieces Coferece (MAICS 03 pp 85-9 New Albay Idiaa USA April 3-4 03 New HSL Distace Based Colour Clusterig Algorithm Vasile Patrascu Departemet of Iformatics
More informationPrevention of Black Hole Attack in Mobile Ad-hoc Networks using MN-ID Broadcasting
Vol.2, Issue.3, May-Jue 2012 pp-1017-1021 ISSN: 2249-6645 Prevetio of Black Hole Attack i Mobile Ad-hoc Networks usig MN-ID Broadcastig Atoy Devassy 1, K. Jayathi 2 *(PG scholar, ME commuicatio Systems,
More informationRunning Time ( 3.1) Analysis of Algorithms. Experimental Studies. Limitations of Experiments
Ruig Time ( 3.1) Aalysis of Algorithms Iput Algorithm Output A algorithm is a step- by- step procedure for solvig a problem i a fiite amout of time. Most algorithms trasform iput objects ito output objects.
More informationAnalysis of Algorithms
Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Ruig Time Most algorithms trasform iput objects ito output objects. The
More informationCOMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 4. The Processor. Part A Datapath Design
COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter The Processor Part A path Desig Itroductio CPU performace factors Istructio cout Determied by ISA ad compiler. CPI ad
More informationEFFECT OF QUERY FORMATION ON WEB SEARCH ENGINE RESULTS
Iteratioal Joural o Natural Laguage Computig (IJNLC) Vol. 2, No., February 203 EFFECT OF QUERY FORMATION ON WEB SEARCH ENGINE RESULTS Raj Kishor Bisht ad Ila Pat Bisht 2 Departmet of Computer Sciece &
More informationEvaluation of Distributed and Replicated HLR for Location Management in PCS Network
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 9, 85-0 (2003) Evaluatio of Distributed ad Replicated HLR for Locatio Maagemet i PCS Network Departmet of Computer Sciece ad Iformatio Egieerig Natioal Chiao
More informationLecture 5. Counting Sort / Radix Sort
Lecture 5. Coutig Sort / Radix Sort T. H. Corme, C. E. Leiserso ad R. L. Rivest Itroductio to Algorithms, 3rd Editio, MIT Press, 2009 Sugkyukwa Uiversity Hyuseug Choo choo@skku.edu Copyright 2000-2018
More informationImproving Template Based Spike Detection
Improvig Template Based Spike Detectio Kirk Smith, Member - IEEE Portlad State Uiversity petra@ee.pdx.edu Abstract Template matchig algorithms like SSE, Covolutio ad Maximum Likelihood are well kow for
More informationperformance to the performance they can experience when they use the services from a xed location.
I the Proceedigs of The First Aual Iteratioal Coferece o Mobile Computig ad Networkig (MobiCom 9) November -, 99, Berkeley, Califoria USA Performace Compariso of Mobile Support Strategies Rieko Kadobayashi
More informationAn Algorithm to Solve Multi-Objective Assignment. Problem Using Interactive Fuzzy. Goal Programming Approach
It. J. Cotemp. Math. Scieces, Vol. 6, 0, o. 34, 65-66 A Algorm to Solve Multi-Objective Assigmet Problem Usig Iteractive Fuzzy Goal Programmig Approach P. K. De ad Bharti Yadav Departmet of Mathematics
More informationAdministrative UNSUPERVISED LEARNING. Unsupervised learning. Supervised learning 11/25/13. Final project. No office hours today
Admiistrative Fial project No office hours today UNSUPERVISED LEARNING David Kauchak CS 451 Fall 2013 Supervised learig Usupervised learig label label 1 label 3 model/ predictor label 4 label 5 Supervised
More informationBOOLEAN DIFFERENTIATION EQUATIONS APPLICABLE IN RECONFIGURABLE COMPUTATIONAL MEDIUM
MATEC Web of Cofereces 79, 01014 (016) DOI: 10.1051/ mateccof/0167901014 T 016 BOOLEAN DIFFERENTIATION EQUATIONS APPLICABLE IN RECONFIGURABLE COMPUTATIONAL MEDIUM Staislav Shidlovskiy 1, 1 Natioal Research
More informationEnd Semester Examination CSE, III Yr. (I Sem), 30002: Computer Organization
Ed Semester Examiatio 2013-14 CSE, III Yr. (I Sem), 30002: Computer Orgaizatio Istructios: GROUP -A 1. Write the questio paper group (A, B, C, D), o frot page top of aswer book, as per what is metioed
More informationAn Algorithm of Mobile Robot Node Location Based on Wireless Sensor Network
A Algorithm of Mobile Robot Node Locatio Based o Wireless Sesor Network https://doi.org/0.399/ijoe.v3i05.7044 Peg A Nigbo Uiversity of Techology, Zhejiag, Chia eirxvrp2269@26.com Abstract I the wireless
More informationLecture 28: Data Link Layer
Automatic Repeat Request (ARQ) 2. Go ack N ARQ Although the Stop ad Wait ARQ is very simple, you ca easily show that it has very the low efficiecy. The low efficiecy comes from the fact that the trasmittig
More informationMindmapping: A General Purpose (Test) Planning Tool
W8 Test Strategy, Plaig, Metrics Wedesday, May 2d, 2018 1:45 PM Midmappig: A Geeral Purpose (Test) Plaig Tool Preseted by: Bob Gale Zeergy Techologies Brought to you by: 350 Corporate Way, Suite 400, Orage
More informationFAST BIT-REVERSALS ON UNIPROCESSORS AND SHARED-MEMORY MULTIPROCESSORS
SIAM J. SCI. COMPUT. Vol. 22, No. 6, pp. 2113 2134 c 21 Society for Idustrial ad Applied Mathematics FAST BIT-REVERSALS ON UNIPROCESSORS AND SHARED-MEMORY MULTIPROCESSORS ZHAO ZHANG AND XIAODONG ZHANG
More informationHADOOP: A NEW APPROACH FOR DOCUMENT CLUSTERING
Y.K. Patil* Iteratioal Joural of Advaced Research i ISSN: 2278-6244 IT ad Egieerig Impact Factor: 4.54 HADOOP: A NEW APPROACH FOR DOCUMENT CLUSTERING Prof. V.S. Nadedkar** Abstract: Documet clusterig is
More informationData Structures and Algorithms. Analysis of Algorithms
Data Structures ad Algorithms Aalysis of Algorithms Outlie Ruig time Pseudo-code Big-oh otatio Big-theta otatio Big-omega otatio Asymptotic algorithm aalysis Aalysis of Algorithms Iput Algorithm Output
More informationA PREDICTION MODEL FOR USER S SHARE ANALYSIS IN DUAL- SIM ENVIRONMENT
GSJ: Computer Sciece ad Telecommuicatios 03 No.3(39) ISSN 5-3 A PRDICTION MODL FOR USR S SHAR ANALYSIS IN DUAL- SIM NVIRONMNT Thakur Sajay, Jai Parag Orietal Uiversity, Idore, Idia sajaymca00@yahoo.com
More informationLecture 1: Introduction and Strassen s Algorithm
5-750: Graduate Algorithms Jauary 7, 08 Lecture : Itroductio ad Strasse s Algorithm Lecturer: Gary Miller Scribe: Robert Parker Itroductio Machie models I this class, we will primarily use the Radom Access
More informationOutline. Research Definition. Motivation. Foundation of Reverse Engineering. Dynamic Analysis and Design Pattern Detection in Java Programs
Dyamic Aalysis ad Desig Patter Detectio i Java Programs Outlie Lei Hu Kamra Sartipi {hul4, sartipi}@mcmasterca Departmet of Computig ad Software McMaster Uiversity Caada Motivatio Research Problem Defiitio
More informationPython Programming: An Introduction to Computer Science
Pytho Programmig: A Itroductio to Computer Sciece Chapter 6 Defiig Fuctios Pytho Programmig, 2/e 1 Objectives To uderstad why programmers divide programs up ito sets of cooperatig fuctios. To be able to
More informationPseudocode ( 1.1) Analysis of Algorithms. Primitive Operations. Pseudocode Details. Running Time ( 1.1) Estimating performance
Aalysis of Algorithms Iput Algorithm Output A algorithm is a step-by-step procedure for solvig a problem i a fiite amout of time. Pseudocode ( 1.1) High-level descriptio of a algorithm More structured
More informationHand Gesture Recognition for Human-Machine Interaction
Had Gesture Recogitio for Huma-Machie Iteractio Elea Sáchez-Nielse Departmet of Statistic, O.R. ad Computer Sciece, Uiversity of La Lagua Edificio de Física y Matemáticas 38271, La Lagua, Spai eielse@ull.es
More informationMining from Quantitative Data with Linguistic Minimum Supports and Confidences
Miig from Quatitative Data with Liguistic Miimum Supports ad Cofideces Tzug-Pei Hog, Mig-Jer Chiag ad Shyue-Liag Wag Departmet of Electrical Egieerig Natioal Uiversity of Kaohsiug Kaohsiug, 8, Taiwa, R.O.C.
More informationRevisiting the performance of mixtures of software reliability growth models
Revisitig the performace of mixtures of software reliability growth models Peter A. Keiller 1, Charles J. Kim 1, Joh Trimble 1, ad Marlo Mejias 2 1 Departmet of Systems ad Computer Sciece 2 Departmet of
More information