HANDBOOK OF NATURE-INSPIRED AND INNOVATIVE COMPUTING Integrating Classical Models with Emerging Technologies HANDBOOK OF NATURE-INSPIRED AND INNOVATIVE COMPUTING Integrating Classical Models with Emerging Technologies Edited by Albert Y Zomaya The University of Sydney, Australia Library of Congress Control Number: 2005933256 Handbook of Nature-Inspired and Innovative Computing: Integrating Classical Models with Emerging Technologies Edited by Albert Y Zomaya ISBN-10: 0-387-40532-1 ISBN-13: 978-0387-40532-2 e-ISBN-10: 0-387-27705-6 e-ISBN-13: 978-0387-27705-9 Printed on acid-free paper © 2006 Springer Science+Business Media, Inc All rights reserved This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, Inc., 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden The use in this publication of trade names, trademarks, service marks and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights Printed in the United States of America springeronline.com SPIN 10942543 To my family for their help, support, and patience Albert Zomaya Table of Contents Contributors ix Preface xiii Acknowledgements xv Section I: Chapter 1: Models Changing Challenges for Collaborative Algorithmics Arnold L Rosenberg Chapter 2: ARM++: A Hybrid Association Rule Mining Algorithm Zahir Tari and Wensheng Wu Chapter 3: Multiset Rule-Based Programming Paradigm for Soft-Computing in Complex Systems E.V Krishnamurthy and Vikram Krishnamurthy 45 77 Chapter 4: Evolutionary Paradigms Franciszek Seredynski 111 Chapter 5: Artificial Neural Networks Javid Taheri and Albert Y Zomaya 147 Chapter 6: Swarm Intelligence James Kennedy 187 Chapter 7: Fuzzy Logic Javid Taheri and Albert Y Zomaya 221 Chapter 8: Quantum Computing J Eisert and M.M Wolf 253 Section II: Chapter 9: Enabling Technologies Computer Architecture Joshua J Yi and David J Lilja Chapter 10: A Glance at VLSI Optical Interconnects: From the Abstract Modelings of the 1980s to Today’s MEMS Implements Mary M Eshaghian-Wilner and Lili Hai 287 315 viii Table of Contents Chapter 11: Morphware and Configware Reiner Hartenstein 343 Chapter 12: Evolving Hardware Timothy G.W Gordon and Peter J Bentley 387 Chapter 13: Implementing Neural Models in Silicon Leslie S Smith 433 Chapter 14: Molecular and Nanoscale Computing and Technology Mary M Eshaghian-WIlner, Amar H Flood, Alex Khitun, J Fraser Stoddart and Kang Wang 477 Chapter 15: Trends in High-Performance Computing Jack Dongarra 511 Chapter 16: Cluster Computing: High-Performance, High-Availability and High-Throughput Processing on a Network of Computers 521 Chee Shin Yeo, Rajkumar Buyya, Hossein Pourreza, Rasit Eskicioglu, Peter Graham and Frank Sommers Chapter 17: Web Service Computing: Overview and Directions Boualem Benatallah, Olivier Perrin, Fethi A Rabhi and Claude Godart 553 Chapter 18: Predicting Grid Resource Performance Online Rich Wolski, Graziano Obertelli, Matthew Allen, Daniel Nurm and John Brevik 575 Section III: Chapter 19: Application Domains Pervasive Computing: Enabling Technologies and Challenges Mohan Kumar and Sajal K Das 613 Chapter 20: Information Display Peter Eades, Seokhee Hong, Keith Nesbitt and Masahiro Takatsuka 633 Chapter 21: Bioinformatics Srinivas Aluru 657 Chapter 22: Noise in Foreign Exchange Markets George G Szpiro 697 Index 711 CONTRIBUTORS Editor in Chief Albert Y Zomaya Advanced Networks Research Group School of Information Technology The University of Sydney NSW 2006, Australia Advisory Board David Bader University of New Mexico Albuquerque, NM 87131, USA Richard Brent Oxford University Oxford OX1 3QD, UK Jack Dongarra University of Tennessee Knoxville, TN 37996 and Oak Ridge National Laboratory Oak Ridge, TN 37831, USA Mary Eshaghian-Wilner Dept of Electrical Engineering University of California, Los Angeles Los Angeles, CA 90095, USA Gerard Milburn University of Queensland St Lucia, QLD 4072, Australia Franciszek Seredynski Institute of Computer Science Polish Academy of Sciences Ordona 21, 01-237 Warsaw, Poland Authors/Co-authors of Chapters Matthew Allen Computer Science Dept University of California, Santa Barbara Santa Barbara, CA 93106, USA Srinivas Aluru Iowa State University Ames, IA 50011, USA Boualem Benatallah School of Computer Science and Engineering The University of New South Wales Sydney, NSW 2052, Australia Peter J Bentley University College London London WC1E 6BT, UK John Brevik Computer Science Dept University of California, Santa Barbara Santa Barbara, CA 93106, USA Rajkumar Buyya Grid Computing and Distributed Systems Laboratory and NICTA Victoria Laboratory Dept of Computer Science and Software Engineering The University of Melbourne Victoria 3010, Australia x Contributors Sajal K Das Center for Research in Wireless Mobility and Networking (CReWMaN) The University of Texas, Arlington Arlington, TX 76019, USA Peter Graham Parallel and Distributed Systems Laboratory Dept of Computer Sciences The University of Manitoba Winniepeg, MB R3T 2N2, Canada Jack Dongarra University of Tennessee Knoxville, TN 37996 and Oak Ridge National Laboratory Oak Ridge, TN 37831, USA Lili Hai State University of New York College at Old Westbury Old Westbury, NY 11568–0210, USA Peter Eades National ICT Australia Australian Technology Park Eveleigh NSW, Australia Jens Eisert Universität Potsdam Am Neuen Palais 10 14469 Potsdam, Germany and Imperial College London Prince Consort Road SW7 2BW London, UK Mary M Eshaghian-Wilner Dept of Electrical Engineering University of California, Los Angeles Los Angeles, CA 90095, USA Rasit Eskicioglu Parallel and Distributed Systems Laboratory Dept of Computer Sciences The University of Manitoba Winniepeg, MB R3T 2N2, Canada Amar H Flood Dept of Chemistry University of California, Los Angeles Los Angeles, CA 90095, USA Claude Godart INRIA-LORIA F-54506 Vandeuvre-lès-Nancy Cedex, France Timothy G W Gordon University College London London WC1E 6BT, UK Reiner Hartenstein TU Kaiserslautern Kaiserslautern, Germany Seokhee Hong National ICT Australia Australian Technology Park Eveleigh NSW, Australia Jim Kennedy Bureau of Labor Statistics Washington, DC 20212, USA Alex Khitun Dept of Electrical Engineering University of California, Los Angeles Los Angeles, CA 90095, USA E V Krishnamurthy Computer Sciences Laboratory Australian National University, Canberra ACT 0200, Australia Vikram Krishnamurthy Dept of Electrical and Computer Engineering University of British Columbia Vancouver, V6T 1Z4, Canada Mohan Kumar Center for Research in Wireless Mobility and Networking (CReWMaN) The University of Texas, Arlington Arlington, TX 76019, USA xi Contributors David J Lilja Dept of Electrical and Computer Engineering University of Minnesota 200 Union Street SE Minneapolis, MN 55455, USA Keith Nesbitt Charles Sturt University School of Information Technology Panorama Ave Bathurst 2795, Australia Daniel Nurmi Computer Science Dept University of California, Santa Barbara Santa Barbara, CA 93106, USA Graziano Obertelli Computer Science Dept University of California, Santa Barbara Santa Barbara, CA 93106, USA Olivier Perrin INRIA-LORIA F-54506 Vandeuvre-lès-Nancy Cedex, France Hossein Pourreza Parallel and Distributed Systems Laboratory Dept of Computer Sciences The University of Manitoba Winniepeg, MB R3T 2N2, Canada Fethi A Rabhi School of Information Systems, Technology and Management The University of New South Wales Sydney, NSW 2052, Australia Arnold L Rosenberg Dept of Computer Science University of Massachusetts Amherst Amherst, MA 01003, USA Franciszek Seredynski Institute of Computer Science Polish Academy of Sciences Ordona 21, 01-237 Warsaw, Poland Leslie Smith Dept of Computing Science and Mathematics University of Stirling Stirling FK9 4LA, Scotland Frank Sommers Autospaces, LLC 895 S Norton Avenue Los Angeles, CA 90005, USA J Fraser Stoddart Dept of Chemistry University of California, Los Angeles Los Angeles, CA 90095, USA George G Szpiro P.O.Box 6278, Jerusalem, Israel Javid Taheri Advanced Networks Research Group School of Information Technology The University of Sydney NSW 2006, Australia Masahiro Takatsuka The University of Sydney School of Information Technology NSW 2006, Australia Zahir Tari Royal Melbourne Institute of Technology School of Computer Science Melbourne, Victoria 3001, Australia Kang Wang Dept of Electrical Engineering University of California, Los Angeles Los Angeles, CA 90095, USA M.M Wolf Max-Planck-Institut für Quantenoptik Hans-Kopfermann-Str 85748 Garching, Germany Rich Wolski Computer Science Dept University of California, Santa Barbara Santa Barbara, CA 93106, USA 722 HNOW models, 20 comparing, 21 HNOW-Exploitation Problem, 21, 22 abstraction of, 26 pipelined, 25 solving, 25–26 variants of, 28–29 HNOW-Rental Problem, 21, 29 HNOW-Utilization Problem, 21, 26–27 solving, 28–29 Hodgkin-Huxley equations, 448 Holland, John, 120 Hopfield’s model, 159–160, 442–443 training data for, 159t Hoskins, Dough, 198 Host-parasite interactions, 114 Hosts, 9, 586 Houston Automatic Spooling Priority (HASP), 521 Hubble Space Telescope, 518 Hybrid architecture, 329–334 Hypercomputers, 253n1 Hypercubes, Hypernetwork Model, 319 Hyperpolarization, 435, 438 Identification, 101 Identification systems fuzzy, 248f ILOG, 634 Image rendering, 545–547 Immunocomputing, 78 UMPP and, 97–98 Implication, 227 In-order issue policy, 297 Incircuit execution, 351 Increased complexity evolution, 413 Incremental learning EH and, 412–413 Indels, 662 Indestructibility of evolutionary platforms, 420 Indexing finishing, 22 startup, 22 Individual, 208–209 Influence particle swarms, 203–206 Information Sonification, 647 Information-theoretic frameworks, 625 Inhibit dependence (ID) in UMPP, 83 Index Initial parameters in fuzzy systems, 243–244 Initialization phase, 133 Innovation in EH, 398–403 Input vectors generalization across, 404–405 Instability defining, 82 Instruction fetch, 377f trace cache, 305–306 Instruction scheduling, 362 Instruction set architecture, 289 actions of, 289t Instruction streams, 343 Instruction-streams, 344 Integrated Parallel Accurate Reservoir Simulator (IPARS), 543 Intelligent Concurrent Object-oriented Synthesis (ICOS), 369 Interaction rule, 189 Interconnection networks bandwidth of, 528f latency of, 528f types of, 6, 7f Interconnection technologies cluster computing and, 523–531 comparisons of, 525t examples of, 524t Internet computing, 1, 3–4, 616 challenges in tempora coping with factual unreliability, 33–35 coping with temporal unreliability, 31–33 factual unpredictability in, 30–31 platforms, 29–30 temporal unpredictability in, 30 unreliability of, Internet throughput, 591f, 601f Interoperability across multiple technologies, 623–624 in pervasive computing, 620–621 Interrupts, 19 Intersection, 223 Intrinsic evolution, 389 Invariants, 88 Ion channels, 436f Irreversibility defining, 82 Island model, 129–130 Index Issue policy in-order, 297 out-of-order, 297 Item-list Ideal, 74 Itemset combination ARM++, 67–68 Itemset-counter table, 52–54 Iterative dynamics of UMPP, 90–91 Iterative learning, 158 JavaGroups, 539 JavaSpaces, 538 Job Entry System (JES), 521 Job structure, K-band, 666 K-flow, 87 K-means clustering, 162, 233–234 results of, 163f KEEP_ALIVE, 600 Killer-applications, 521 Killer-microprocessors, 521 Killer-networks, 521 Killer-tools, 521 Knapsack problems, 122 Knowledge discovery, 45–46 Known-Risk models, 18 Kohonen clustering, 163–164 classification results for, 165 output topology of, 163f Kohonen mapping network, 446 KressArray Xplorer, 369, 370f antimachine mapped with, 375f L-extensions, 48 Lamarckian evolution, 111–112 Landscaping rule, 96 Langmuir-Blodgett (LB) technique, 479 Laplacian matrix, 639 Largest of maximum (LOM), 226 Last Value predictors, 593 Latané, Bibb, 194 Latency, 11 of different interconnects, 528f lbest topology, 188, 196, 204 LCS See Learning classifier systems Leaky integrate-and-fire model, 447–448, 459 unit, 447f Learning, 208 social, 209 723 Learning classifier systems (LCS), 114, 136–138 anticipatory, 138 concept of, 137f Learning systems neural models and, 441–442 Learning Vector Quantization (LVQ) basic structure of, 164f defining, 173 learning algorithm, 173–175 subclass association of, 164f Learning vector quantization (LVQ), 445–446 Libra, 535–536 Life functions, 18, 19 Ligation, 100 Linda tuplespace, 537–548 Linear Algebra Libraries, 519 Linear array with a reconfigurable pipelined bus system (LARPBS), 328–329 Linear auto-associative learning, 156–158 Links, 147, 563 LINPACK benchmark, 513 Linux clusters, 527 Lloyd’s metaphor, 273 Load balancing, Load bypassing, 299 Load forwarding, 300 LoadLeveler, 534–535 Local alignments, 666–667 Local frequent itemsets, 50 Local search algorithms in GAs, 126–127 Local-area networks (LAN), Locality, 2, spatial, 298 temporal, 298 value, 306 Location awareness, 622 Location fusion, 624 Location management architecture, 622–623 Location prediction, 624 Location privacy, 625 Location translation, 624 Location-aware computing, 622 Location-independent computing, 622 Lock-in-place mechanisms, 260 Lock-key paradigms, 79, 98–99 Loftus, Elizabeth, 192 Log, 587 724 LogP models, 11 Lookup tables (LUTs), 400 exact matches and, 668–669 Loop transformations, 369 Low-cost hardware automatic design of, 392–393 LSF, 534–535 LSF Batch, 535 LSF Multicluster, 535 LU-A benchmark NPB, 529f speedup for, 530f LUT implementation, 352f LVQ See Learning Vector Quantization Machine availability, 603f MLE exponential and, 605f Machine paradigms, 369–373 illustrating, 372f Magnetic spring algorithm, 635 Maintenance, Repair, and Operating (MRO), 561 Mamdani systems, 226–228 flow diagram for, 229f salary, 227f shower, 238f surface view of, 229f Mapping networks Kohonen, 446 Markov chain Monte Carlo (MCMC), 78 UMPP and, 91–92 Markov Chain Monte Carlo-based Bayesian inference, 77 Massively Parallel Processors (MPPs), 512, 513 Match sets, 137 Mating restriction mechanisms, 128 Matrix crossbars, 322–323 MavHome Smart Home pervasive computing and, 628–629 Maximum Likelihood Estimation (MLE), 605 machine availability and, 605f McCulloch-Pitts model, 440–441 Mean of maximum (MOM), 226 Mean square error (MSE) algorithms, 160–161 Measurement noise dynamic noise v., 699–700 Membrane circuits and, 437f Index Membrane computing, 78 UMPP and, 97–98 Memes in particle swarms, 209–211 Memory, 579, 587 NWS, 581–582 Memory buffer, 310 Memory bus, 349 Memory gap, 298–299 Memory technology VLSI, 452–453 Memory, high-performance policies and additions for, 299–301 memorySpeedMonitor, 583 MEMS See Micro-electro-mechanicalsystems Mendel, Gregor, 112 Merge, 102 Meshlike networks, Message Passing Interface (MPI), 519, 523, 536, 538–539, 545 communicators, 539 Message queues, 538 Message-passing multiprocessors, 2, Metal-organic chemical vapor deposition (MOCVD), 483 METEOR-S, 571 Metric entropy machines positive, 86 zero, 86 Micro-electro-mechanical-systems (MEMS), 334–335, 494, 616 multisensor nodes, 618 Microarrays, 680 Middleware technologies, 619–620 Minimum-allele-reserve-keeper, 125 Mining association, 46–47 AIS and, 48–49 ARM++, 51–52 confidence in, 46–47 support in, 46–47 Mixed reality, 642 Mixing, 87 Mixtrinsic evolution, 407 Mobile communications, 616–617 Mobile environments web services in, 570–571 Mobile hosts (MH), 617 Mobility, 613 in pervasive computing, 621–622 Molecular beam epitaxy (MBE), 483 Molecular biology, 658–660 725 Index Molecular chemical transactions, 101–102 Molecular computing challenges of, 502 Molecular DNA computation, 99–100 Molecular multiset data structure, 100–101 Molecular quantum computers, 281 Molecular self-assembly, 496–497 Molecular switches, 481–483 Molecular-based computing models nanotechnology, 492–493 Molecular-switch tunnel junctions (MSTJ), 481–482 Monitors NWS, 583 Monotonic systems, 82 Moore’s law, 373f, 387, 434, 478, 516 peak performance and, 512f physical limits of, 255 Moore, Gordon, 255, 511 MOPSO (multiobjective particle swarm optimization), 200 Morphware, 345–349 acronyms, 345f alternative applications, 349f application development support, 356–359 applications of, 354–356 coarse grain, 350, 359–373 computing sciences and, 373–379 configware, 345f evolvable, 358–359 fine-grain, 350–360 in education, 357–358 in innovative applications, 358–359 introduction to, 343–345 terminology, 347f Morris-Lecar equations, 448 Mountain clustering, 235 Mountain function, 235 MPI See Message Passing Interface MPICH, 539 mRNA, 659 Multicomparment neurons, 464 Multilayer learning, 167 Multilayer perceptron, 150–152 basic structure of, 150f functional representation of, 152–153 Multilevel approach to graph drawing, 635–637 Multilevel atomicity, 94 Multilevel caches, 298–299 Multimodal random problem generator, 202–203 Multiobjective evolutionary algorithms (MOEAs), 128 Multiobjective optimization in particle swarm research, 199–200 Multiple instruction issue, 295–297 Multiple Particle Filter approach, 92 Multiple-Instruction, Multiple-Data (MIMD), 536 Multiple-Instruction, Single-Data (MISD), 536 Multiplexed fiber arrays using, 327–328 Multiprocessors, message-passing, platforms, shared-memory, Multiscale architecture design hierarchical, 495f nanoscale and, 493–496 Multiscale technique, 636 Multisensor nodes MEMS, 618 Multisensory display, 645–650 designing, 648–649 user interfaces, 646f Multistage fiber interconnection networks, 326–327 Multisurface display projector, 643 Multithread computation, 13 Multithreaded architecture, 309–312 simultaneous, 311–312 speculative, 309–311 Multivalue algebra, 221 MUMmer, 687–688 Mutations, 117, 120, 390 in GAs, 125 point, 391 single-bit, 120 Myelinization, 439, 464n2 Myrinet, 526 Name dependencies, 294 Nameserver, 579 NWS, 580–581 Nano-electro-mechanical systems (NEMS), 335 Nanoscale, 335, 403 multiscale architecture and, 493–496 726 Nanoscale technology design issues, 501–503 introduction to, 477–480 molecular-based computing models, 492–493 quantum-based computing modules, 490–491 spin-based computing models, 491–492 switching elements in, 480–490 Nanotubes (NTs), 485 National Partnership for Advanced Computational Infrastructure (NPACI), 575 National Science Foundation, 575 Native services, 554 Natural joins, 98 Natural selection, 112 Near-optimal signaling traffic, 624–625 Nearest-neighbor clustering fuzzy system design using, 246–247 Negative differential resistance switching devices with, 483–485 Neighborhood best, 189 Neighbors, 27 Network emulations, 9–11 computation phase, 10 coordination phase, 10 Network heterogeneity, 601–603 Network Interface Cards (NIC), 523, 527 Network processors, 349 Network topology RBF, 170–171 Network Weather Service (NWS), 577 architecture of, 579–588 cache, 585–586 clique skills, 584 design considerations, 584–586 development and deployment of, 599–603 dynamic model differentiation, 588–589 error bars, 592–593 examples of, 590–595 forecasting errors, 594–595 forecasting methodology, 588–590 forecasts of, 591f, 592f grid performance tools and services, 599–601 measurements of, 594f, 595f memory, 581–582 monitors, 583 nameservers, 580–581 network heterogeneity, 601–603 Index Network Weather Service (NWS) (Continued ) overview of, installations, 579f periodic skills, 584 sensors, 582–583 user interface, 586–588 Networks of workstations (NOWS) See Clusters Neural models complex, implementation, 463–466 detailed, 448 hardware implementation and, 449–467 implementation techniques, 450t implementing, in silicon, 433–434 implementing, simple time-free, 454–458 learning in, 448–449 self-organizing, 445 simple, 440–446 time and, 446–449 VLSI implementation of, 450–451 Neural networks applications, 176 biased structures of, 148f controllers, 177f feed-forward, 444f inputs and outputs of, 148f output for, 156f perceptron, 155f truth tables of, 148t two-layer, 168f unbiased structures of, 148f Neuromorphic Architecture, 485 examples of, 496f Neuromorphic Architecture design, 496–497 Neurons, real, 435–440 See also Point neurons; Spiking neurons Neurons, time-free developed hardware for, 457–458 synapses for, 455–456 Neurotransmitters, 437 Neutral networks EH and, 412–413 Next-line prefetching, 309 Niches, 111, 113–114 Niching algorithms, 128 No free lunch theorem, 138 No-cloning theorem, 259 Noise, foreign market autocorrelation for, 707f chaos and, 701–702 727 Index Noise, foreign market (Continued ) data, 702 dimension and, 701–702 findings in, 703–707 in intramonth data, 704f, 705f, 706f in scrambled time series, 704f intraday data, 706f introduction to, 697–699 measurement of, 701–702 measurement v dynamic, 699–700 Noise-cancellation networks, 178–179 input and target signals for, 179f performance and error signal of, 180 Nonequilibrium systems, 87, 95 Nonlinear dynamic systems fuzzy systems and, 247–248 Nonmonotonic systems, 82 Nontermination defining, 82 North American Industry Classification System (NAICS), 558 NP-Hardness, 26 NPB FT-A benchmark, 529f LU-A benchmark, 529f Nuclear magnetic resonance (NMR), 280 quantum computing, 282–283 Numerical Aerodynamic Simulation (NAS) nwsActivity, 581 nwsControl, 581 nwsHost, 580 nwsSeries, 581 nwsSkill, 581 Object class NWS, 580–581 OCPC See Optical communication parallel Computer model simulation algorithms, 319–322 Octree meshes etree method of, 545f Odyssey, 626 Oligonucleotides, 100 OMC See Optical model of computation On-demand pair generation, 680–681 One-way quantum computation, 278 Online training, 177 Opcode, 290 Open Grid Services Architecture (OGSA), 517 Open systems, 85–87 simulating, 88 Open-world hypothesis, 78, 102 OpenGL, 641 OpenPBS, 535 Operating environments generalization across, 405–406 Opposition dependence (OD) in UMPP, 83 Optical computing abstract models of, 316 introduction to, 315–316 Optical interconnects fiber-guided, 326–329 free-space, 322–325 Optical mesh using mirrors, 324–325 Optical methods quantum, 280 Optical model of computation (OMC), 317–319 schematic of, 318f simulation algorithms, 319–322 Optical quantum computers, 281 Optical Reconfigurable Mesh, 316 Optical reconfigurable mesh (ORM), 329–330 deflection unit of, 330 electrical routing in, 330–331 electro-optical routing, 331–333 optical routing in, 330, 331 processing unit of, 329–330 schematic of, 330f Optical routing ORM, 331 Optimal EREW algorithms, 320–321 Optimal Postcasts, 593 Oracle, 261 ORM See Optical reconfigurable mesh Oscilatory chemical reactions UMPP and, 95–96 Out-of-order issue policy, 297 Outsourcing agreements, 554 Overhead, 11 OWL, 571 Oxygen project pervasive computing and, 626–627 PACT XPP, 363f PAM matrix, 673 Parallel computing, 728 Parallel processing reconfigurable computing v., 376–378 Parallel slack, 11 Parallel Virtual Machine (PVM), 539–540 Parallelism, 7, 82 branch predication and, 304–305 branch prediction and, 301–304 competitive, 84 control dependencies and, 294–295 cooperative, 84 data, 93, 514–515 data dependencies and, 294–295 high-performance memory and, 299–301 memory gap and, 298–299 multilevel caches in, 298–299 multiple instruction issue in, 295–297 pipeline, 93 pipelining and, 292–294 prefetching, 308–309 task, 514–515 value prediction, 306–307 vector, 93 Parallelizing using dataflow techniques, via partitioning, Parameter Sweep, 540 Parameterized models, 11 Parent-oriented schedules, 32 Pareto model, 605 Pareto sets, 199, 213 Parity check matrix, 276 Partial differential equations (PDE), 519 Partially commutative systems, 82 Particle filters, 92 Particle swarms applications of, 212 binary, 202–203 canonical algorithm, 189 constants, 189 convergence and, 197–199 defining, 187 dynamic problems, 201–202 evaluation of, 191 evolution of, 196–197 evolutionary computation and, 207–209 explosion and, 197–199 exteriorizing, 211 flocking, 195–196 fully informed, 205 future of, 212 Gaussian, 206–207 Index Particle swarms (Continued ) general characteristics of, 188–189 influence, 203–206 initialization, 189 memes in, 209–211 multiobjective optimization in, 199–200 neighborhood best, 189 optimization, 187 origins of canonical, 193 points to test in, 190–191 schooling, 195–196 social psychology and genetic algorithms, 194–195 sociocognitive metaphors, 191–193 theory, 214 topology, 203–206 tweaking, 213 Partition algorithm, 50, 59, 67, 69 ARM++ in, 65 comparisons, 74–75 execution time, 74 FilterApr and, 74–75 scalability, 75 Partition approach, 47 Partitioned optical passive stars (POPS), 327 Partitioning parallelizing via, 7–8 Partner Link Types, 563 Paths, Pattern history table (PHT), 303–304 Pauli gates, 258 Pauli groups, 277 pbest topology, 196 PE, 320–321 labeling, 321f Pebble games, 31 rules of, 32 Pell’s equation, 270 Per transmission costs, 25 Perceptrons, 441–442 learning single-layer models, 154–155 multilayer, 150–153 single layer, 149 training sets for, 156t Perceptual synthesis, 646 Performance Application Programmers Interface (PAPI), 519 Performance growth, 515f Performance prediction introduction to, 575–577 NWS architecture and, 579–588 Index Performance prediction (Continued ) requirements for, 577–578 resource characteristics, 603–607 Periodic skills NWS, 584 Pervasive computing aura and, 625–626 heterogeneity in, 620–621 interoperability in, 620–621 introduction to, 613–615 MavHome Smart Home, 628–629 mobility in, 621–622 Oxygen project and, 626–627 PICO and, 627–628 proactivity in, 621 transparency in, 621 Pervasive Information Community Organization (PICO), 627–628 Petroleum Reservoir Simulation, 542–543 Phase, 203 Phase flip errors, 274 Phase gates, 258 Phenotypes, 112, 116, 390, 415 Phi, 197, 198 Phylogenetic analysis, 661 Physical behavior, 399 Physiologist’s Friend chip, 466 Ping, 587 Pipe networks, 362–363 Pipelining, 501 parallelism and, 292–294 Placement software, 351 Platform research EH in, 419–421 Platform Space Explorers (PSEs), 369 Platforms EH and, 421 PLD See Programmable Logic Device Pleiades architecture, 368 Point mutation, 391 Point neurons, 447 implementation of, 459–460 models, 448 Pollack’s Law, 374f Population fault-tolerance (PFT), 409 Population manipulation in GAs, 123–124 Population overlaps, 123 Population sets, 137 Portability, 407 Portable Batch System (PBS), 535 729 Portable Extensible Toolkit for Scientific Computation (PETSc), 543 Portable performance, 519 Positive metric entropy machines, 86–87 Possibility probability v., 222 Possible subset items (PSI), 62–63 Possible transaction items, 60, 63 Postcasting, 589, 590 Postsynaptic potentiation, 437 Potential bias, 124 Potentiation long-term, 440 postsynaptic, 437 PRAM algorithm, 319, 320 ERCW, 320 EREW, 320 Predator-prey interactions, 114 Predicate registers, 304 Predictability, 3–4 Prefetching, 308–309 next-line, 309 Prefix comparison, 130 Pressure selection, 203 Principal component analysis (PCA), 638 Prism, 626 Privacy in web service, 569–570 location information and, 625 Proactivity in pervasive computing, 621 Probability possibility v., 222 Procedure worksteal, 14–15, 17 performance of, 16 Process-based integration in web services, 567–568 Processing layer, 317 Processor bus, 349 Processor design, 514f Processor numbers, 11 Program counter (PC), 288 Program shells, 78 Programmable Arithmetic Device for DSP (PADDI), 358 Programmable logic abstractions, 400–401 Programmable Logic Device (PLD), 351, 389, 407 Prokaryotic organisms, 658 Promise algorithms, 262 Promoters, 659 730 Propagating waves in earthquake simulation, 546f Proportional selection, 120 Protein Explorer, 543–544 block diagram of, 544f Protein interaction model, 419f Protein structure prediction, 661 Pseudocode of canonical algorithm, 190t PSTSWM, 526n1, 529 Pulse-based neuron implementations, 458–463 QCA See Quantum cellular automata QFT See Quantum fourier transform QOS See Quality of Service Quality of Service (QOS), 615 web services and, 570–571 Quantiles, 604 estimation methods using, 606t Quantum adiabatic theorem, 271 Quantum algorithms, 260–264, 269–270 Quantum cellular automata (QCA), 335, 490 Quantum computers, 253, 403 adiabatic, 270–272 building, 279–283 circuit model of, 257–258 classical computers and, 256–260 computational tasks and, 254 fault-tolerating, 278–279 future perspectives on, 282–283 molecular, 281 NMR, 282–283 one-way, 278 optical, 281 programming, 259–260 read-out and probabilistic nature of, 257 silicon-based nuclear spin, 282 small, 255–256 solid-state approaches to, 282 universal, 272 Quantum dots, 282, 489, 491f regular arrays of, 497–498 Quantum electrodynamics, 281 Quantum error correction, 260, 273–279 CSS codes, 277–278 introductory example of, 274–275 Shor code, 275–276 stabilizer codes, 277–278 Steane code, 276–277 Index Quantum fourier transform (QFT) in Shor’s algorithm, 266 Shor’s algorithm and, 268–269 Quantum mechanics, 253 Quantum modular exponentiation, 269–270 Quantum optical methods, 280–281 Quantum parallelism, 480 qubits and, 256–257 Quantum random walks, 270 Quantum simulators, 255 Quantum systems simulation of, 254–255, 272–273 Quantum-based computing modules nanotechnology, 490–491 Qubits, 253 quantum parallelism and, 256–257 Radial Basis Function (RBF), 444, 455 basic structure of, 171f defining, 170 network topology, 170–171 training algorithms, 171–172 typical data sets for, 173f Radio frequency identification (RFID), 610, 613, 614, 618 RAM-based machine paradigms, 349–350 Random graph models, 78 Random key, 133–134 Ranking, 124 Rapid prototyping, 351, 354 RBF See Radial Basis Function RDF, 571 Read operation CRCW, 333 Read-out process of quantum computers, 257 Ready deque, 14 Real sensory systems, 434 Real-value functions, 152 neural models corresponding to, 154f neural networks implementing, 153f truth table for, 153t Recombination, 207, 209 Reconfigurable Architecture Workstation (RAW), 368, 376 Reconfigurable Data Path Arrays (rDPAs), 359–360, 363, 367 Reconfigurable Gate Arrays (rGAs), 350–351 Index Reconfiguration, 347 dynamic, 354 of accelerators, 349 of evolutionary platforms, 420 parallel processing v., 376–378 self, 357 Recursive least squares fuzzy system design using, 244–245 Reduced instruction set computer See RISC Register, 587 Registration, 580 Relational database model, 98–99 Relocatability, 359 Reorder buffers (ROB), 295 RepeatMasker, 686 Repetition encoding, 274 Representations, 116 dynamic, 414 EH, 410–411 Resonance stochastic, 403 Resonant-tunneling diodes (RTD), 483, 484 energy levels of, 484f Resource availability, 576 Resource characteristics measuring and predicting, 603–607 Resource management systems (RMS) cluster computing, 533–536 examples of, 534t Restarts, 115 in GAs, 127 Retro emulation, 355 Return address stack (RAS), 304 Reverse complementation, 658 Rewards, 137 RFID See Radio frequency identification RISC (reduced instruction set computer), 289–290, 512 CISC v., 289 performance analysis of, 291–292 RMS See Resource management systems Robot path planning, 178 optimal, 178f with deep U-traps, 179f RosettaNet, 561 Rotor stacking problem, 122 Roulette wheel, 120, 124 Routing congestion, 351 Routing software, 351 731 Rule-based systems stochastic, 88–89 types of, 82 Run-Time Reconfiguration (RTR), 356 Sample data classification answers for, 161f Scaffolds generation of, 678 Scalability, 359, 623 Scalable orchestration of web services, 569 Scalable traffic, 624–625 Scaling problems, 124 Scanning tunneling microscope (STM), 479 Schooling particle swarms, 195–196 Schrödinger equation SCI, 526, 527, 531 Scoring schemes bioinformatics and, 672–673 Search space, 390 Security, 625 Selection, 208 in GAs, 124 tournament, 124 truncation, 124 Selection pressure, 124, 203 Selective amplify, 101 Self-adaptation, 209 evolution strategies with, 118–119 Self-assembled structures, 497–501 images of, 498f Self-assembly conjoin and, 99 molecular, 498–499 Self-organized criticality, 80 Self-organizing systems, 445–446 Self-reconfigurating designs, 357 SELF-SERV, 568 Semantic web services, 571 Sensor networks, 617–618 Sensors, 579, 614 NWS, 582–583 Serial program, parallel subsystem (SPPS), 536, 539 Server Daemon, 535 Service advertisement, 555 Service composition, 562 Service provider communities, 628 Set oriented mining (SETM), 49 732 Set-theoretic operations, 223 complement, 223 intersection, 223 union, 223 SET See Single-electron transistors SGE, 535 SGI, 514 Shared-memory multiprocessors, 2, distributed, 5–6 Shönhagen-Strassen algorithm, 269n27 Shor code, 275–276 qubit, 275 encoding circuits of, 279f Shor’s algorithm, 254n3, 255, 264 classical part, 266, 267–268 efficient implementation of, 267 exponential speed-up in, 266–267 joining pieces together in, 269–270 QFT for period-finding, 266 Shor, Peter, 254 Shower system, 237f Mamdani, 238f Si-Based SRAM cell, 484 characteristics of, 484f Sibling table, 52–54 Signal coding VLSI, 451–452 Silicon implement neuron models in, 433–434 Silicon technology crisis, 344 Simian, 545–546 Simon’s algorithm, 263–264 Simple neuron models, 440–446 Simple Object Access Protocol (SOAP), 556–557 Simplicity accuracy v., 221–222 Simulated annealing, 369 Simulating quantum systems, 272–273 Simultaneous multithreading, 311–312 Single crossbars, 499 Single nucleotide polymorphism (SNP), 659–660, 683 identification, 679 Single System Image (SSI), 530 achieving, 532t at operating system level, 531–533 defining, 531 Single-electron transistors (SET), 487–489 inverters, 488f Single-Instruction, Multiple-Data (SIMD), 536 Index Single-layer perceptron, 149 Hopfield’s model for learning, 159–160 iterative learning, 158 linear auto-associative learning, 156–158 MSE algorithms for learning, 160–161 multioutput, 150f perceptron learning, 154–155 supervised learning, 154 widow-Hoff rule and, 161–162 Single-population master-slaves model, 128–129 Single-stuck-at (SSA) faults, 408 Single-walled carbon nanotubes (SWNT), 499, 500f Single-Instruction, Single-Data (SISD), 536 Skill, 587 SMPs See Symmetric multiprocessors SNP See Single nucleotide polymorphism SoC See System on chip Social evolution, 208 Social learning, 209 Social psychology genetic algorithms and, 194–195 Sociocognition, 192 Sociocognitive metaphors particle swarms and, 191–193 Sociometry, 188, 206 Soft computation, 78 Soft CPUs, 359 Software languages, 371f Software-defined ratio, 360f360 Solution space, 390 Sound displays, 645–647 Sound field simulation, 646 Space domain, 347 Space reduction techniques in alignments, 664–666 Species, 111, 113–114 Species Adaptation Genetic Algorithm (SAGA), 412 Specification defining, 81 Spectra, 626 Spectral methods of graph drawing, 639–640 Speculative multithreaded processors, 309–311 Speedups for FT-A benchmark, 530f for LU-A benchmark, 530f Index SPICE, 407, 408 Spiking neurons hardware, 465–466 implementing, 458–463 interconnecting, 463 pulse-based implementations of, 458–459 synapses for, 461–463 Spin-based computing models nanotechnology, 491–492 Spin-based logic NAND gate, 492 Spins, 489–490 Splitting factors, 63 SPPS See Serial program, parallel subsystem Spring algorithms, 635 Spring embedder, 635 Sprouting, 130 SSI See Single System Image Stabilizer codes, 277–278 Stacks, 14 Start/stop, 587 startMonitor, 583 Startup indexing, 22 Stastical homogeneity, 86 State vectors, 259n7 Static RAM (sRAM), 452 Steady-state reproduction, 123, 127 Steane code 7-qubit, 276 encoding circuits of, 279f error correction of, 276–277 Stepping rule, 96 Stigmergy, 78 Stochastic approximation algorithm, 104 Stochastic marked point processes, 78 Stochastic optimization discrete adaptive, 102–105 Stochastic resonance, 403 Stochastic rule-based paradigm, 88–89 UMPP properties and, 89–90 Stochastic selection, 120 Stochastic universal selection, 124 Stochasticity, 87 Stockpile Stewardship Program (SSP), 518 Strean Processing Unit (SPU), 641 Strong Church-Turling thesis, 254n3 Structural homologies, 661 Structure, circuit, 404 Structured activities, 563 Structured Configware Design, 359 733 Subgroup problems hidden, 267 Subset comparison, 57 candidate comparison and, 70–73 transform transactions and, 73 Subset transformation, 59 FilterApr, 62–64 Subset_transform, 63–64 Subtracting clustering, 235–236 Success probability, 271 Suffix arrays exact matches in, 669–671 generalized, 671f Suffix trees exact matches in, 669–671 generalized, 671f Sugeno systems, 228–230 flow diagram of, 231f overview of, 230f surface view of, 231f Sugiyama method, 635 Sum, 102 Sum of maximum (SOM), 226 Superclique, 585 Supercomputers, 511 Superconducting quantum interference devices (SQUID), 282 Superposition, 256 SuperScalar processors, 295–296 Supersystolic array, 362, 363 Superthreaded Architecture (STA), 310, 311 Support in mining association, 46–47 Swarm intelligence defining, 187, 191 Swarm paradigm UMPP and, 96 Switch boxes, 351 Switchable molecules graphical representations of, 482f Switching elements in nanotechnology, 480–490 molecular, 481–483 negative differential resistance, 483–485 Symmetric multiprocessors (SMPs), 512, 514, 521, 522 Symmetry breaking, 2, Synapses, 147, 436–437 arrangement of, 456f excitatory, 438 for spiking neurons, 461–463 734 Synapses (Continued ) for time-free neurons, 455–456 inhibitory, 438 ionotropic, 438f Syntenic alignment problem, 686f Synthetic data sets, 71t System defining, 81 System identification, 247–248 System on chip (SoC), 343, 376 Systolic arrays, 8, 365f Tactilization, 647 Takens’ embedding theorem, 698n1 Task arrivals, 16 Task-allocation functions (TAF), 34 Taxonomy, 378–379 TCP/IP throughput capture percentages for, 598f TCP/IP traces, 590 tcpConnectMonitor, 583 tcpMessageMonitor, 583 Temp variable fuzzy membership function for, 238f Tensor products, 256 TeraGrid, 602 Termination defining, 81 Termination conditions, 115, 116 Test, 587 Thomson’s VLSI model, 318 Threads, 13–14 Threshold theorems, 279 Throughputs internet, 591f, 601f of workstation P, 27–28 Tick sizes, 699–700 Time division multiplexing (TDM), 326 Time domain, 347, 351 Time reduction techniques in alignments, 664–666 Timeshares, 29 Timestamps, 580 Toffoli gates, 278 TomSawyer Software, 634 Top500 results extrapolation of, 516f performance growth of, 515f processor design, 514f Topology gbest, 188, 196, 201, 204 lbest, 188, 196, 204 Index Topology (Continued ) particle swarms, 203–206 pbest, 196 Tournament selection, 124 Trace cache, 305–306 Traceroute data, 590 Training algorithms, 171–172 Training data auto-associative networks, 157t Hopfield’s model, 159t inseparable, 160f sample, 178f Transaction Processing Monitors (TPM), 537 Transaction transformation, 59 FilterApr, 59–62 filters, 60f list data size, 67 possible items for, 61f Transaction’s ID (TID), 49, 50 performance of, 66–67 Transaction_transform, 60–61, 61–62 Transcription, 659 Transform transactions subsets and, 73 Translation, 659 Transparency in pervasive computing, 621 Traveling Salesman Problem (TSP), 118 Tredennick, Nick, 372f Tree-dags, 32 Tree-optimization problems, 122 Trotter’s formula, 273 Truncation selection, 124 Truth tables for real-value functions, 153t Tuples, 537–548, 570 Two-layer networks, 168f Two-member ES, 117 Two-member tournament selection, 390 Ubiquitous computing, 621–622 UMPP See Unified multiset programming paradigm Unified multiset programming paradigm (UMPP), 78 ant colony paradigm and, 96 classifier/bucket-brigade systems and, 92–93 computational features of, 79–80 Conrad’s Lock-Key paradigm and, 97 ED in, 83 Index Unified multiset programming paradigm (UMPP) (Continued ) evolutionary optimization and, 94–95 genetic algorithms and, 93–94 genetic programming and, 94 ID in, 83 immunocomputing and, 97–98 iterative dynamics of, 90–91 MCMC and, 91–92 membrane computing and, 97–98 OD in, 83 oscillatory chemical reactions and, 95–96 properties of, 89–90 randomized grid Bayesian interface and, 91–92 structure of, 79 swarm paradigm, 96 Union, 223 Universal Description Discovery and Integration (UDDI), 558 Universal gates, 258 array, 259 Universal location management infrastructure, 623 Universal Standard Products and Services Code System (UNSPSC), 558 Unsupervised learning, 162 ART1, 164–166 ART2, 166 K-means clustering, 162 Kohonen clustering, 163–164 Useful behavior, 399 Value prediction, 306–307 Value reuse, 307–308 Value reuse table (VRT), 308 Vectors, 512 VEPSO (vector-evaluated particle swarm organization), 200 Very Large Scale IC’s (VLSI), 315–316, 317, 319, 461, 466, 488–489 abstract models of, 316 analogue v digital, 451–454 memory technologies, 452–453 neural models and, 450–451 signal coding, 451–452 simple arithmetic operations, 453–454 Thomson’s, 318 VHDL, 358 Vibrational modes, 281 Victim caches, 300–301 735 Vigilance factors, 165 Virtual Interface Architecture (VIA), 523 Virtualized reality, 643 Visualization, 633 augmented displays, 642–643 high-resolution displays, 641–642 integration of technologies, 643–645 new tools for, 641–645 VLIW (very-long instruction word) processors, 295–296 VLSI See Very Large Scale IC’s VLSIO computing, 319 Vmax, 197, 198, 213 Von Neumann architecture, 287 basic components of, 288f Von Neumann bottleneck, 343 Von Neumann machine paradigm, 343, 346, 358, 372 Von Neumann processors, 349f Von Neumann, John, 287, 343 Warsaw Simulation System, 194 Watson-Crick complements (WCC), 100 Wavefront array, 363 Wavelength division multiplexing (WDM), 326 Web Service basic concepts of, 554–555 business process execution language for, 562–565 composition and orchestration, 562 dependable integration of, 569 development life cycle, 554 in mobile environments, 570–571 infrastructure, 555–560 introduction to, 553–554 optimal QoS-driven, 570–571 orchestration, 569 overview of stack, 555f privacy in, 569–570 process-based integration in, 567–568 semantic, 571 Web Service Choreography Interface (WSCI), 565 Web Service Coordination, 559–560 Web Service Description Language (WSDL), 557–558, 563 Web Service Policy, 560 Web Service Reliability, 559 Web Service Security, 558–559 Web Service Transaction, 559–560 736 Web Services Conversation Language (WSCL), 567 Web Services Modeling Framework (WSMF), 571 Web-based computing, 29, 30 coping with factual unreliability, 33–35 coping with temporal unreliability, 31–33 factual unpredictability in, 30–31 temporal unpredictability in, 30 Weibull model, 606 Widow-Hoff rule, 161–162 WireGL, 641 Wireless communications, 616–617 Wireless LANS (WLANs), 616 Wolfram classes, 90–91 Work allocations fractional, 22–23 Worksharing cluster computing via, 20–29 Workstation P computation rates of, 27 throughputs of, 27–28 Index Workstations, rented, 22 timeline for, 23 Workstealing cluster computing via, 13–17 fixed points of, 16–17 procedure, 14–15 systems, 15–16 Write operation CRCW, 332–333 xCBL, 561 XOR gates, 400 XPUs configurable, 362f Zadeh, Lotfi, 221 Zero metric entropy machines, 86 Zero tests, 102 ... the areas included in the handbook The handbook endeavors to strike a balance between theoretical and practical coverage of a range of innovative computing paradigms and applications The handbook. .. California, Santa Barbara Santa Barbara, CA 93106, USA Rajkumar Buyya Grid Computing and Distributed Systems Laboratory and NICTA Victoria Laboratory Dept of Computer Science and Software Engineering.. .HANDBOOK OF NATURE- INSPIRED AND INNOVATIVE COMPUTING Integrating Classical Models with Emerging Technologies HANDBOOK OF NATURE- INSPIRED AND INNOVATIVE COMPUTING Integrating Classical Models