{"product_id":"large-scale-network-centric-distributed-systems-hardback-9780470936887","title":"Large Scale Network-Centric Distributed Systems (Hardback) 9780470936887","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eLarge Scale Network-Centric Distributed Systems\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eHamid Sarbazi-Azad (Edited by), H Sarbazi–Azad (Author), Albert Y. Zomaya (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470936887, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 10 December 2013\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e760 pages\u003cbr\u003e24.1 x 16.5 x 4.1 cm, 1.161 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eA highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eEvolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eLarge Scale Network-Centric Distributed Systems \u003c\/i\u003eprovides in-depth coverage ranging from ground-level hardware issues (such as buffer organization, router delay, and flow control) to the high-level issues immediately concerning application or system users (including parallel programming, middleware, and OS support for such computing systems). Arranged in five parts, it explains and analyzes complex topics to an unprecedented degree:\u003c\/p\u003e \u003cul\u003e \u003cli\u003e\n\u003cb\u003ePart 1: \u003c\/b\u003eMulticore and Many-Core (Mc) Systems-on-Chip\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003ePart 2: \u003c\/b\u003ePervasive\/Ubiquitous Computing and Peer-to-Peer Systems\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003ePart 3: \u003c\/b\u003eWireless\/Mobile Networks\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003ePart 4: \u003c\/b\u003eGrid and Cloud Computing\u003c\/li\u003e \u003cli\u003e\n\u003cb\u003ePart 5: \u003c\/b\u003eOther Topics Related to Network-Centric Computing and Its Applications\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eLarge Scale Network-Centric Distributed Systems\u003c\/i\u003e is an incredibly useful resource for practitioners, postgraduate students, postdocs, and researchers.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface xxix  \u003cp\u003eAcknowledgments xxxvii\u003c\/p\u003e \u003cp\u003eList of Figures xxxix\u003c\/p\u003e \u003cp\u003eList of Tables li\u003c\/p\u003e \u003cp\u003eList of Contributors lv\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 1 MULTICORE AND MANY-CORE (MC) SYSTEMS-ON-CHIP\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1 A RECONFIGURABLE ON-CHIP INTERCONNECTION NETWORK FOR LARGE MULTICORE SYSTEMS 3\u003cbr\u003e \u003ci\u003eMehdi Modarressi and Hamid Sarbazi-Azad\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 4\u003c\/p\u003e \u003cp\u003e1.2 Topology and Reconfiguration 8\u003c\/p\u003e \u003cp\u003e1.3 The Proposed NoC Architecture 9\u003c\/p\u003e \u003cp\u003e1.4 Energy and Performance-Aware Mapping 14\u003c\/p\u003e \u003cp\u003e1.5 Experimental Results 19\u003c\/p\u003e \u003cp\u003e1.6 Conclusion 25\u003c\/p\u003e \u003cp\u003e2 COMPILERS, TECHNIQUES, AND TOOLS FOR SUPPORTING PROGRAMMING HETEROGENEOUS MANY\/MULTICORE SYSTEMS 31\u003cbr\u003e \u003ci\u003ePasquale Cantiello, Beniamino Di Martino, and Francesco Moscato\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 32\u003c\/p\u003e \u003cp\u003e2.2 Programming Models and Tools for Many\/Multicore 32\u003c\/p\u003e \u003cp\u003e2.3 Compilers and Support Tools 42\u003c\/p\u003e \u003cp\u003e2.4 CALuMET: A Tool for Supporting Software Parallelization 45\u003c\/p\u003e \u003cp\u003e2.5 Conclusion 49\u003c\/p\u003e \u003cp\u003e3 A MULTITHREADED BRANCH-AND-BOUND ALGORITHM FOR SOLVING THE FLOW-SHOP PROBLEM ON A MULTICORE ENVIRONMENT 53\u003cbr\u003e \u003ci\u003eMohand Mezmaz, Nouredine Melab, and Daniel Tuyttens\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 54\u003c\/p\u003e \u003cp\u003e3.2 Flow-Shop Scheduling Problem 55\u003c\/p\u003e \u003cp\u003e3.3 Parallel Branch-and-Bound Algorithms 56\u003c\/p\u003e \u003cp\u003e3.4 A Multithreaded Branch-and-Bound 58\u003c\/p\u003e \u003cp\u003e3.5 The Proposed Multithreaded B\u0026amp;B 60\u003c\/p\u003e \u003cp\u003e3.6 Experiments and Results 63\u003c\/p\u003e \u003cp\u003e3.7 Conclusion 68\u003c\/p\u003e \u003cp\u003ePART 2 PERVASIVE\/UBIQUITOUS COMPUTING AND PEER-TO-PEER SYSTEMS 4 LARGE-SCALE P2P-INSPIRED PROBLEM-SOLVING: A FORMAL AND EXPERIMENTAL STUDY 73\u003cbr\u003e \u003ci\u003eMathieu Djama¨ý, Bilel Derbel, and Nouredine Melab\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 74\u003c\/p\u003e \u003cp\u003e4.2 Background 77\u003c\/p\u003e \u003cp\u003e4.3 A Pure Peer-to-Peer B\u0026amp;B Approach 80\u003c\/p\u003e \u003cp\u003e4.4 Complexity Issues 87\u003c\/p\u003e \u003cp\u003e4.5 Experimental Results 90\u003c\/p\u003e \u003cp\u003e4.6 Conclusion 99\u003c\/p\u003e \u003cp\u003eAcknowledgment 99\u003c\/p\u003e \u003cp\u003e5 DATA DISTRIBUTION MANAGEMENT 103\u003cbr\u003e \u003ci\u003eAzzedine Boukerche and Yunfeng Gu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Addressing DDM in Different Network Environments 104\u003c\/p\u003e \u003cp\u003e5.2 DDM in P2P Overlay Networks 106\u003c\/p\u003e \u003cp\u003e5.3 DDM in Cluster-Based Network Environments 111\u003c\/p\u003e \u003cp\u003e6 MIDDLEWARE SUPPORT FOR CONTEXT HANDLING AND INTEGRATION IN UBIQUITOUS COMPUTING 123\u003cbr\u003e \u003ci\u003eFrederico Lopes, Paulo F. Pires, Flávia C. Delicato, Thais Batista, and Luci Pirmez\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 124\u003c\/p\u003e \u003cp\u003e6.2 Ubiquitous Computing 126\u003c\/p\u003e \u003cp\u003e6.3 Middleware for Ubiquitous Computing 128\u003c\/p\u003e \u003cp\u003e6.4 A Solution to Integrating Context Provision Middleware for Ubiquitous Computing 133\u003c\/p\u003e \u003cp\u003e6.5 Conclusion 142\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 3 WIRELESS\/MOBILE NETWORKS\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7 CHALLENGES IN THE USE OF WIRELESS SENSOR NETWORKS FOR MONITORING THE HEALTH OF CIVIL STRUCTURES 147\u003cbr\u003e \u003ci\u003eFlávia C. Delicato, Igor L. dos Santos, Luci Pirmez, Paulo F. Pires, and Claudio M. de Farias\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 148\u003c\/p\u003e \u003cp\u003e7.2 Structural Health Monitoring 150\u003c\/p\u003e \u003cp\u003e7.3 Wireless Sensor Networks 155\u003c\/p\u003e \u003cp\u003e7.4 Applying Wireless Sensor Networks for Structural Health Monitoring 157\u003c\/p\u003e \u003cp\u003e7.5 Conclusion 163\u003c\/p\u003e \u003cp\u003e8 MOBILITY EFFECTS IN WIRELESS MOBILE NETWORKS 167\u003cbr\u003e \u003ci\u003eAbbas Nayebi and Hamid Sarbazi-Azad\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 167\u003c\/p\u003e \u003cp\u003e8.2 The Effect of Node Mobility on Wireless Links 168\u003c\/p\u003e \u003cp\u003e8.3 The Effect of Node Mobility on Network Topology 172\u003c\/p\u003e \u003cp\u003e8.4 Conclusion 177\u003c\/p\u003e \u003cp\u003e9 ANALYTICAL MODEL OF TIME-CRITICAL WIRELESS SENSOR NETWORK: THEORY AND EVALUATION 183\u003cbr\u003e \u003ci\u003eKambiz Mizanian and Amir Hossein Jahangir\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 184\u003c\/p\u003e \u003cp\u003e9.2 Real-Time Wireless Sensor Network: An Overview 185\u003c\/p\u003e \u003cp\u003e9.3 Real-Time Degree 188\u003c\/p\u003e \u003cp\u003e9.4 Reliable Real-Time Degree 195\u003c\/p\u003e \u003cp\u003e9.5 Model Validation 197\u003c\/p\u003e \u003cp\u003e9.6 Conclusion 199\u003c\/p\u003e \u003cp\u003e10 MULTICAST TRANSPORT PROTOCOLS FOR LARGE-SCALE DISTRIBUTED COLLABORATIVE ENVIRONMENTS 203\u003cbr\u003e \u003ci\u003eHaifa Raja Maamar and Azzedine Boukerche\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 204\u003c\/p\u003e \u003cp\u003e10.2 Definition and Features 204\u003c\/p\u003e \u003cp\u003e10.3 Classification of Multicast Protocols 207\u003c\/p\u003e \u003cp\u003e10.4 Conclusion 216\u003c\/p\u003e \u003cp\u003e11 NATURE-INSPIRED COMPUTING FOR AUTONOMIC WIRELESS SENSOR NETWORKS 219\u003cbr\u003e \u003ci\u003eWei Li, Javid Taheri, Albert Y. Zomaya, Franciszek Seredynski, and Bjorn Landfeldt\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 220\u003c\/p\u003e \u003cp\u003e11.2 Autonomic WSNs 222\u003c\/p\u003e \u003cp\u003e11.3 Principles of Nature-Inspired Computing 224\u003c\/p\u003e \u003cp\u003e11.4 Cellular Automata 226\u003c\/p\u003e \u003cp\u003e11.5 Swarm Intelligence 228\u003c\/p\u003e \u003cp\u003e11.6 Artificial Immune Systems 233\u003c\/p\u003e \u003cp\u003e11.7 Evolutionary Computing 238\u003c\/p\u003e \u003cp\u003e11.8 Molecular Biology 242\u003c\/p\u003e \u003cp\u003e11.9 Bio-Networking Architecture 243\u003c\/p\u003e \u003cp\u003e11.10 Conclusion 244\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 4 GRID AND CLOUD COMPUTING\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12 SMART RPC-BASED COMPUTING IN GRIDS AND ON CLOUDS 257\u003cbr\u003e \u003ci\u003eThomas Brady, Oleg Girko, and Alexey Lastovetsky\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 258\u003c\/p\u003e \u003cp\u003e12.2 SmartGridRPC and SmartGridSolve 266\u003c\/p\u003e \u003cp\u003e12.3 Making SmartGridSolve Smarter 277\u003c\/p\u003e \u003cp\u003e12.4 Smart RPC-Based Computing on Clouds: Adaptation of SmartGridRPC and SmartGridSolve to Cloud Computing 282\u003c\/p\u003e \u003cp\u003e13 PROFIT-MAXIMIZING RESOURCE ALLOCATION FOR MULTITIER CLOUD COMPUTING SYSTEMS UNDER SERVICE LEVEL AGREEMENTS 291\u003cbr\u003e \u003ci\u003eHadi Goudarzi and Massoud Pedram\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 292\u003c\/p\u003e \u003cp\u003e13.2 Review of Datacenter Power Management Techniques 294\u003c\/p\u003e \u003cp\u003e13.3 Review of Datacenter Performance Management Techniques 296\u003c\/p\u003e \u003cp\u003e13.4 System Model of a Multitier Application Placement Problem 298\u003c\/p\u003e \u003cp\u003e13.5 Profit Maximization in a Hosting Datacenter 303\u003c\/p\u003e \u003cp\u003e13.6 Simulation Results 310\u003c\/p\u003e \u003cp\u003e13.7 Conclusion 314\u003c\/p\u003e \u003cp\u003e14 MARKET-ORIENTED CLOUD COMPUTING AND THE CLOUDBUS TOOLKIT 319\u003cbr\u003e \u003ci\u003eRajkumar Buyya, Suraj Pandey, and Christian Vecchiola\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 320\u003c\/p\u003e \u003cp\u003e14.2 Cloud Computing 322\u003c\/p\u003e \u003cp\u003e14.3 Cloudbus: Vision and Architecture 338\u003c\/p\u003e \u003cp\u003e14.4 Cloudbus and Clouds Lab Technologies 340\u003c\/p\u003e \u003cp\u003e14.5 Experimental Results 345\u003c\/p\u003e \u003cp\u003e14.6 Related Technologies, Integration, and Deployment 350\u003c\/p\u003e \u003cp\u003e14.7 Conclusion 351\u003c\/p\u003e \u003cp\u003e15 A CLOUD BROKER ARCHITECTURE FOR MULTICLOUD ENVIRONMENTS 359\u003cbr\u003e \u003ci\u003eJose Luis Lucas-Simarro, Iñigo San Aniceto, Rafael Moreno-Vozmediano, Ruben S. Montero, and Ignacio M. Llorente\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 360\u003c\/p\u003e \u003cp\u003e15.2 State of the Art on Cloud Brokering 361\u003c\/p\u003e \u003cp\u003e15.3 Challenges of Cloud Brokering 363\u003c\/p\u003e \u003cp\u003e15.4 Proposal of a Broker Architecture for Multicloud Environments 364\u003c\/p\u003e \u003cp\u003e15.5 Scheduling Policies for Efficient Cloud Brokering 367\u003c\/p\u003e \u003cp\u003e15.6 Results 369\u003c\/p\u003e \u003cp\u003e15.7 Conclusion 373\u003c\/p\u003e \u003cp\u003e16 ENERGY-EFFICIENT RESOURCE UTILIZATION IN CLOUD COMPUTING 377\u003cbr\u003e \u003ci\u003eGiorgio L. Valentini, Samee U. Khan, and Pascal Bouvry\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 378\u003c\/p\u003e \u003cp\u003e16.2 Related Work 380\u003c\/p\u003e \u003cp\u003e16.3 Energy-Efficient Utilization of Resources in Cloud Computing Systems 381\u003c\/p\u003e \u003cp\u003e16.4 Complementarity Approach 386\u003c\/p\u003e \u003cp\u003e16.5 Simulation Results 395\u003c\/p\u003e \u003cp\u003e16.6 Discussion of Results 402\u003c\/p\u003e \u003cp\u003e16.7 Conclusion 404\u003c\/p\u003e \u003cp\u003e17 SEMANTICS-BASED RESOURCE DISCOVERY IN LARGE-SCALE GRIDS 409\u003cbr\u003e \u003ci\u003eJuan Li, Samee U. Khan, and Nasir Ghani\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 410\u003c\/p\u003e \u003cp\u003e17.2 Related Work 411\u003c\/p\u003e \u003cp\u003e17.3 Virtual Organization Formation 412\u003c\/p\u003e \u003cp\u003e17.4 Semantics-Based Resource Discovery in Virtual Organizations 417\u003c\/p\u003e \u003cp\u003e17.5 Prototype Implementation and Evaluation 421\u003c\/p\u003e \u003cp\u003e17.6 Conclusion 427\u003c\/p\u003e \u003cp\u003e18 GAME-BASED MODELS OF GRID USER’S DECISIONS IN SECURITY-AWARE SCHEDULING 431\u003cbr\u003e \u003ci\u003eJoanna Kolodziej, Samee U. Khan, Lizhe Wang, and Dan Chen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 432\u003c\/p\u003e \u003cp\u003e18.2 Security-Aware Scheduling Problems in Computational Grids 433\u003c\/p\u003e \u003cp\u003e18.3 Game Models in Security-Aware Grid Scheduling 441\u003c\/p\u003e \u003cp\u003e18.4 Case Study: Approximating the Equilibrium States of the End Users’ Symmetric Game Using the Genetic Metaheuristics 447\u003c\/p\u003e \u003cp\u003e18.5 Conclusion 460\u003c\/p\u003e \u003cp\u003e19 ADDRESSING OPEN ISSUES ON PERFORMANCE EVALUATION IN CLOUD COMPUTING 463\u003cbr\u003e \u003ci\u003eBeniamino Di Martino, Massimo Ficco, Massimiliano Rak,and Salvatore Venticinque\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 464\u003c\/p\u003e \u003cp\u003e19.2 Benchmarking Approaches 465\u003c\/p\u003e \u003cp\u003e19.3 Monitoring in Cloud Computing 468\u003c\/p\u003e \u003cp\u003e19.4 Attack Countermeasures in Cloud Computing 474\u003c\/p\u003e \u003cp\u003e19.5 Conclusion 480\u003c\/p\u003e \u003cp\u003e20 BROKER-MEDIATED CLOUD-AGGREGATION MECHANISM USING MARKOVIAN QUEUES FOR SCHEDULING BAG-OF-TASKS (BOT) APPLICATIONS 485\u003cbr\u003e \u003ci\u003eGanesh Neelakanta Iyer and Bharadwaj Veeravalli\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 486\u003c\/p\u003e \u003cp\u003e20.2 Literature Review and Contributions 487\u003c\/p\u003e \u003cp\u003e20.3 Problem Setting and Notations 488\u003c\/p\u003e \u003cp\u003e20.4 Proposed Cloud Aggregation Mechanism 489\u003c\/p\u003e \u003cp\u003e20.5 Performance Evaluation and Discussions 494\u003c\/p\u003e \u003cp\u003e20.6 Discussions 497\u003c\/p\u003e \u003cp\u003e20.7 Conclusion 498\u003c\/p\u003e \u003cp\u003e21 ON THE DESIGN OF A BUDGET-CONSCIOUS ADAPTIVE SCHEDULER FOR HANDLING LARGE-SCALE MANY-TASK WORKFLOW APPLICATIONS IN CLOUDS 503\u003cbr\u003e \u003ci\u003eBharadwaj Veeravalli, Lingfang Zeng, and Xiaorong Li\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction 504\u003c\/p\u003e \u003cp\u003e21.2 Related Work and Motivation 505\u003c\/p\u003e \u003cp\u003e21.3 System Model and Problem Setting 506\u003c\/p\u003e \u003cp\u003e21.4 Proposed Scheduling Algorithm 512\u003c\/p\u003e \u003cp\u003e21.5 Performance Evaluation and Results 516\u003c\/p\u003e \u003cp\u003e21.6 Conclusion 522\u003c\/p\u003e \u003cp\u003e22 VIRTUALIZED ENVIRONMENT ISSUES IN THE CONTEXT OF A SCIENTIFIC PRIVATE CLOUD 527\u003cbr\u003e \u003ci\u003eBruno Schulze, Henrique de Medeiros Klˆoh, Matheus Bousquet Bandini, Antonio Roberto Mury, Daniel Massami Muniz Yokoyama, Victor Dias de Oliveira, F´abio Andr´e Machado Porto, and Giacomo Victor McEvoy Valenzano\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e22.1 Introduction 528\u003c\/p\u003e \u003cp\u003e22.2 Related Works 528\u003c\/p\u003e \u003cp\u003e22.3 Methodology 531\u003c\/p\u003e \u003cp\u003e22.4 Experiments 533\u003c\/p\u003e \u003cp\u003e22.5 Conclusion 544\u003c\/p\u003e \u003cp\u003e22.6 Glossary 546\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 5 OTHER TOPICS RELATED TO NETWORK-CENTRIC COMPUTING AND ITS APPLICATIONS\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e23 IN-ADVANCE BANDWIDTH SCHEDULING IN e-SCIENCE NETWORKS 551\u003cbr\u003e \u003ci\u003eYan Li, Eunsung Jung, Sanjay Ranka, Nageswara S. Rao, and Sartaj Sahni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e23.1 Introduction 552\u003c\/p\u003e \u003cp\u003e23.2 Temporal Network Model 554\u003c\/p\u003e \u003cp\u003e23.3 Single-Path Scheduling 556\u003c\/p\u003e \u003cp\u003e23.4 Multiple-Path Scheduling 570\u003c\/p\u003e \u003cp\u003e23.5 Conclusion 587\u003c\/p\u003e \u003cp\u003e24 ROUTING AND WAVELENGTH ASSIGNMENT IN OPTICAL NETWORKS 591\u003cbr\u003e \u003ci\u003eYan Li, Sanjay Ranka, and Sartaj Sahni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e24.1 Introduction 592\u003c\/p\u003e \u003cp\u003e24.2 Scheduling in Full-Wavelength Conversion Network 593\u003c\/p\u003e \u003cp\u003e24.3 Scheduling in Sparse Wavelength Conversion Network 603\u003c\/p\u003e \u003cp\u003e25 COMPUTATIONAL GRAPH ANALYTICS FOR MASSIVE STREAMING DATA 619\u003cbr\u003e \u003ci\u003eDavid Ediger, Jason Riedy, David A. Bader, and Henning Meyerhenke\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e25.1 Introduction 620\u003c\/p\u003e \u003cp\u003e25.2 STINGER: A General-Purpose Data Structure for Dynamic Graphs 622\u003c\/p\u003e \u003cp\u003e25.3 Algorithm for Updating Clustering Coefficients 625\u003c\/p\u003e \u003cp\u003e25.4 Tracking Connected Components in Scale-Free Graphs 628\u003c\/p\u003e \u003cp\u003e25.5 Implementation 632\u003c\/p\u003e \u003cp\u003e25.6 Experimental Results 634\u003c\/p\u003e \u003cp\u003e25.7 Related Work 643\u003c\/p\u003e \u003cp\u003e25.8 Conclusion 644\u003c\/p\u003e \u003cp\u003e26 KNOWLEDGE MANAGEMENT FOR FAULT-TOLERANT WATER DISTRIBUTION 649\u003cbr\u003e \u003ci\u003eJing Lin, Ali Hurson, and Sahra Sedigh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e26.1 Introduction 650\u003c\/p\u003e \u003cp\u003e26.2 Related Work 652\u003c\/p\u003e \u003cp\u003e26.3 Agent-Based Model for WDN Operation 653\u003c\/p\u003e \u003cp\u003e26.4 Classes in WDN Ontology Framework 656\u003c\/p\u003e \u003cp\u003e26.5 Automated Failure Classification and Mitigation 659\u003c\/p\u003e \u003cp\u003e26.6 Validation of Automated Failure Mitigation 668\u003c\/p\u003e \u003cp\u003e26.7 Conclusion 674\u003c\/p\u003e \u003cp\u003eAcknowledgment 675\u003c\/p\u003e \u003cp\u003eReferences 675\u003c\/p\u003e \u003cp\u003eIndex 679\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-IEEE Computer Society Pr","offers":[{"title":"Brand New","offer_id":52278118940952,"sku":"9780470936887","price":102.55,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780470936887.jpg?v=1781458429","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/large-scale-network-centric-distributed-systems-hardback-9780470936887","provider":"Freshly Printed Books","version":"1.0","type":"link"}