Davoli / Meyer / Pugliese Remote Instrumentation and Virtual Laboratories

Service Architecture and Networking
1. Auflage 2010
ISBN: 978-1-4419-5597-5
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 519 Seiten

Accessing remote instrumentation worldwide is one of the goals of e-Science. The task of enabling the execution of complex experiments that involve the use of distributed scientific instruments must be supported by a number of different architectural domains, which inter-work in a coordinated fashion to provide the necessary functionality. These domains embrace the physical instruments, the communication network interconnecting the distributed systems, the service oriented abstractions and their middleware. The Grid paradigm (or, more generally, the Service Oriented Architecture -- SOA), viewed as a tool for the integration of distributed resources, plays a significant role, not only to manage computational aspects, but increasingly as an aggregator of measurement instrumentation and pervasive large-scale data acquisition platforms. In this context, the functionality of a SOA allows managing, maintaining and exploiting heterogeneous instrumentation and acquisition devices in a unified way, by providing standardized interfaces and common working environments to their users, but the peculiar aspects of dealing with real instruments of widely different categories may add new functional requirements to this scenario. On the other hand, the growing transport capacity of core and access networks allows data transfer at unprecedented speed, but new challenges arise from wireless access, wireless sensor networks, and the traversal of heterogeneous network domains. The book focuses on all aspects related to the effective exploitation of remote instrumentation and to the building complex virtual laboratories on top of real devices and infrastructures. These include SOA and related middleware, high-speed networking in support of Grid applications, wireless Grids for acquisition devices and sensor networks, Quality of Service (QoS) provisioning for real-time control, measurement instrumentation and methodology, as well as metrology issues in distributed systems.

Autoren/Hrsg.

Davoli, Franco

Meyer, Norbert

Pugliese, Roberto

Zappatore, Sandro

Inhaltsverzeichnis

1;Preface;6
2;Acknowledgments;10
3;Contents;12
4;Contributors;18
5;Part I Remote Instrumentation Services;28
5.1;1 Open Grid Forum Research Group: Remote Instrumentation Services in Grid Environment -- Overview of Activities;29
5.1.1;1 Introduction;29
5.1.2;2 Main Goals OF OGF RISGE-RG;30
5.1.3;3 Past and Current Activities;30
5.1.4;4 Example Use Case -- Remote Operations of Experimental Facilities;32
5.1.4.1;4.1 Customers;33
5.1.4.2;4.2 Scenario;33
5.1.5;5 Model Use Case;34
5.1.6;6 Conclusions;35
5.1.7;References;36
5.2;2 Adapting the Instrument Element to Support a Remote Instrumentation Infrastructure ;37
5.2.1;1 Introduction;37
5.2.2;2 Related Work;38
5.2.2.1;2.1 Motivations for the New Implementation;38
5.2.3;3 Design Approach;39
5.2.4;4 Implementation Issues;42
5.2.4.1;4.1 Implementing an Instrument Manager;42
5.2.4.2;4.2 Attributes;43
5.2.4.3;4.3 Parameters;44
5.2.4.4;4.4 Commands;44
5.2.4.5;4.5 Deployment;45
5.2.4.6;4.6 Front-End (VCR);45
5.2.5;5 Conclusions;46
5.2.6;References;47
5.3;3 Performance Analysis of a Grid-Based Instrumentation Device Farm ;49
5.3.1;1 Introduction;49
5.3.2;2 GRIDCC Overall Architecture;50
5.3.3;3 VCR - IE Communication;52
5.3.4;4 Performance Evaluation;54
5.3.5;5 Conclusions;57
5.3.6;References;58
5.4;4 Experimental Characterization of Wireless and Wired Access in Distributed Laboratories ;59
5.4.1;1 Introduction;59
5.4.2;2 WiLab Architecture;61
5.4.3;3 Communication Networks Among Distributed Instruments;63
5.4.3.1;3.1 From Internet User to GPIB Resources;63
5.4.3.2;3.2 Remote Access by Intranet User;64
5.4.4;4 Conclusions;68
5.4.5;References;68
5.5;5 Virtual Laboratory and Its Application in Genomics ;69
5.5.1;1 Introduction;69
5.5.2;2 Virtual Laboratory;70
5.5.2.1;2.1 Architecture;70
5.5.2.2;2.2 The Peculiar Nature of the Virtual Laboratory Experiments;71
5.5.2.3;2.3 Workflow Management;72
5.5.2.4;2.4 Digital Library;74
5.5.2.5;2.5 The Example Diagrams;76
5.5.3;3 Genomics;77
5.5.3.1;3.1 Microarray Experiment Execution;77
5.5.3.2;3.2 Genomic Virtual Laboratory;79
5.5.3.3;3.3 Experiment Description;80
5.5.4;4 Conclusions;82
5.5.5;References;83
6;Part II Grid Infrastructure, Services, and Applications;84
6.1;6 The European Grid Initiative (EGI) ;85
6.1.1;1 Introduction;85
6.1.2;2 Example: The Spanish National Grid Infrastructure;87
6.1.3;3 European Grid Infrastructure and Large-Scale Research;89
6.1.4;References;90
6.2;7 Virtual Appliances: A Way to Provide Automatic Service Deployment ;91
6.2.1;1 Introduction;91
6.2.2;2 Related Works;93
6.2.3;3 Issues of a Virtualisation-Based Deployment System;94
6.2.4;4 Automatic Service Deployment;95
6.2.5;5 Automatic Virtual Appliance Creation Service (AVS);97
6.2.6;6 Scheduler Assistant Service (SAS);98
6.2.7;7 Conclusion and Future Work;100
6.2.8;References;100
6.3;8 Job Scheduling in Hierarchical Desktop Grids ;102
6.3.1;1 Introduction;102
6.3.2;2 Related Work;103
6.3.3;3 A Simple Model for Hierarchical Desktop Grids;105
6.3.4;4 Events Changing the Scheduling;106
6.3.4.1;4.1 New Donor;106
6.3.4.2;4.2 Exiting Donor;107
6.3.4.3;4.3 New Workunit;107
6.3.4.4;4.4 Workunit Transition;107
6.3.4.5;4.5 Workunit Processed;107
6.3.4.6;4.6 New Desktop Grid;108
6.3.4.7;4.7 Exiting Desktop Grid;108
6.3.5;5 Scheduling Algorithms;108
6.3.5.1;5.1 Static Scheduling Algorithms;109
6.3.5.2;5.2 Algorithms Depending on Donor Number;110
6.3.5.3;5.3 Algorithms Depending on Time-out;113
6.3.5.4;5.4 Algorithms Considering Local Workunits;115
6.3.6;6 Conclusion and Future Work;118
6.3.7;References;119
6.4;9 Toward QoS Provision for Virtualized Resources in Grids ;121
6.4.1;1 Introduction;121
6.4.2;2 Related work;122
6.4.3;3 QoS Management of VM-based Resource Providers;123
6.4.3.1;3.1 Approach;123
6.4.3.2;3.2 Management Component and Prototype;124
6.4.3.3;3.3 QoS Management;125
6.4.4;4 Experiments and Results;126
6.4.5;5 Conclusions;128
6.4.6;References;129
6.5;10 From Grid Islands to a World Wide Grid ;130
6.5.1;1 Introduction;130
6.5.2;2 Step 1: Introduction of Meta-Brokers;132
6.5.3;3 Step 2: Introduction of Advanced Grid Portals;134
6.5.4;4 Step 3: Network of AGPs to Realize Workflow Interoperation;136
6.5.5;5 Related Work;138
6.5.6;6 Conclusions;140
6.5.7;References;141
6.6;11 The Anatomy of Grid Resource Management ;144
6.6.1;1 Introduction;144
6.6.2;2 The GRM Anatomy;146
6.6.3;3 Interoperability Issues and Requirements for New Solutions;149
6.6.3.1;3.1 Interoperability Problems at All Levels: The Solution Is Meta-Brokering;149
6.6.3.2;3.2 New Candidates for Resource Management: Remote Instrumentation;151
6.6.4;4 Conclusions;152
6.6.5;References;152
6.7;12 SZTAKI Desktop Grid: Adapting Clusters for Desktop Grids;154
6.7.1;1 Introduction;154
6.7.2;2 Related Work;155
6.7.2.1;2.1 BOINC and Condor;155
6.7.2.2;2.2 XtremWeb and Condor;156
6.7.2.3;2.3 BOINC and the Grid;157
6.7.3;3 SZTAKI Desktop Grid and Condor;157
6.7.3.1;3.1 Security;158
6.7.3.2;3.2 Application Deployment;159
6.7.3.3;3.3 Flow;160
6.7.3.4;3.4 Fault Tolerance;161
6.7.3.5;3.5 Future Work;162
6.7.4;4 Applications;162
6.7.5;5 Conclusion;163
6.7.6;References;164
6.8;13 SoRTGrid: A Grid Framework Compliant with Soft Real-Time Requirements;166
6.8.1;1 Introduction;166
6.8.2;2 Related works;167
6.8.3;3 SoRTGrid;168
6.8.4;4 Architecture of SoRTGrid;170
6.8.4.1;4.1 SoRT-Bids and Owner Agents;171
6.8.4.2;4.2 Facilitator Agent: BidMan Service;172
6.8.4.3;4.3 User Agents and Job Requirements Manifests;173
6.8.5;5 Resource Discovery in SoRTGrid;174
6.8.5.1;5.1 Facilitator Agent: DiPe Grid Service;175
6.8.5.2;5.2 Local SoRT-Bid Discovery;176
6.8.5.3;5.3 Remote SoRT-Bid Discovery;177
6.8.5.4;5.4 Neighboring;178
6.8.6;6 Notes on SoRT-Bids Negotiation and Production;179
6.8.6.1;6.1 Timed Pre-reservation of Resources;179
6.8.6.2;6.2 SoRT-Bids Overbooking;180
6.8.7;7 Conclusions;180
6.8.8;References;181
6.9;14 A Data Grid Architecture for Real-Time Electron Microscopy Applications ;183
6.9.1;1 Introduction;183
6.9.2;2 SEM Remote Control Project;184
6.9.3;3 Remote SEM/TEM and Grid Architecture;185
6.9.3.1;3.1 Remote SEM/TEM Requirements;185
6.9.3.2;3.2 A Grid for a Virtual SEM/TEM Laboratory;187
6.9.4;4 Perspectives;190
6.9.5;5 Conclusions;190
6.9.6;References;191
6.10;15 A Network-Aware Grid for Efficient Parallel Monte Carlo Simulation of Coagulation Phenomena ;193
6.10.1;1 Introduction;193
6.10.2;2 Monte Carlo Simulation of a Coagulation Problem;195
6.10.2.1;2.1 Statement of the Problem;195
6.10.2.2;2.2 Parallel Monte Carlo Algorithm;196
6.10.3;3 Network-Aware Grid Architecture;199
6.10.3.1;3.1 Path Computation Algorithm;200
6.10.4;4 Performance Analysis;201
6.10.4.1;4.1 Test Coagulation Equation;202
6.10.4.2;4.2 Simulation Scenario;203
6.10.4.3;4.3 Simulation Results;206
6.10.5;5 Conclusions;207
6.10.6;References;207
7;Part III Interactivity Management;209
7.1;16 Practical Mechanisms for Managing Parallel and Interactive Jobs on Grid Environments ;210
7.1.1;1 Introduction;210
7.1.2;2 Description of the CrossBroker Architecture;211
7.1.3;3 Job Description Language;213
7.1.4;4 Managing Parallel Jobs;214
7.1.5;5 Managing Interactive Jobs;216
7.1.6;6 Conclusions;217
7.1.7;References;217
7.2;17 Int.eu.grid ;219
7.2.1;1 Introduction;219
7.2.2;2 Infrastructure Architecture;220
7.2.3;3 Infrastructure Interactivity Framework;221
7.2.3.1;3.1 Friendly User Access;222
7.2.3.2;3.2 Interactivity;223
7.2.3.3;3.3 Visualization;223
7.2.3.4;3.4 CrossBroker and Time Sharing Mechanisms;224
7.2.3.5;3.5 lcg-CE, JobManagers, and LRMS Configurations;225
7.2.4;4 Conclusions;226
7.2.5;References;226
7.3;18 Interactivity in Grid Computing in the Presence of Web Services ;228
7.3.1;1 Introduction;228
7.3.2;2 Exploring Interactivity;229
7.3.3;3 The Approach of Web Services;230
7.3.3.1;3.1 A Separate Bidirectional Data Channel;230
7.3.3.2;3.2 Providing a Dedicated Web Service;231
7.3.3.3;3.3 Preliminary Experiments;231
7.3.3.4;3.4 An Interactive Service using Globus WSRF;232
7.3.3.5;3.5 Secure Connection Re-Establishment;234
7.3.3.6;3.6 Executing a Command with the InteractiveService;235
7.3.3.7;3.7 Secure Local Communication;236
7.3.4;4 Future and Related Work;237
7.3.5;5 Conclusions;238
7.3.6;References;239
7.4;19 Fusion Simulations, Data Visualization Results and Future Requirements for the Interactive Grid Infrastructure ;241
7.4.1;1 Introduction;241
7.4.2;2 Fusion Introduction and Theoretical models;242
7.4.2.1;2.1 Langevin Approach;243
7.4.2.2;2.2 Direct Approach;243
7.4.3;3 Adaptation of IVISDEP to Int.eu.grid Framework;245
7.4.3.1;3.1 Use Case;245
7.4.3.2;3.2 Architecture;246
7.4.4;4 Proposed Architecture;247
7.4.4.1;4.1 Direct Approach;247
7.4.4.2;4.2 Data Management and Visualization in the Grid;248
7.4.5;5 Conclusions;249
7.4.6;References;249
7.5;20 Interactive Grid-Access Using MATLAB ;251
7.5.1;1 Introduction;251
7.5.1.1;1.1 The Grid Middleware gLite;253
7.5.1.2;1.2 Limitations of gLite;253
7.5.2;2 Improving Grid Access;255
7.5.2.1;2.1 Pilot Jobs;255
7.5.2.2;2.2 GridSolve;255
7.5.3;3 Integration of GridSolve and gLite;256
7.5.3.1;3.1 Giggle design;257
7.5.3.2;3.2 Giggle Tools for Creating Services;258
7.5.3.3;3.3 Giggle Tools for Resource Allocation;259
7.5.3.4;3.4 Giggle Tools for the End-User;259
7.5.4;4 Measurements;259
7.5.5;5 Conclusions;262
7.5.6;References;263
7.6;21 Collaborative Interactivity in Parallel HPC Applications ;264
7.6.1;1 Introduction;265
7.6.2;2 Collaborative Online Visualization and Steering (COVS) Framework;266
7.6.3;3 COVS Framework Features to Manage Interactive Grid Applications;268
7.6.3.1;3.1 Secure Data Transfer and Interactive Access;269
7.6.3.2;3.2 Naming Service for Decoupling COVS Components;271
7.6.3.3;3.3 Enable Collaboration with Naming Service;273
7.6.4;4 Interactive Computational Use Cases;274
7.6.5;5 Related Work;275
7.6.6;6 Conclusions;276
7.6.7;References;276
7.7;22 Interactive and Real-Time Applications on the EGEE Grid Infrastructure;278
7.7.1;1 Introduction;278
7.7.2;2 The EGEE Grid Infrastructure;279
7.7.2.1;2.1 EGEE Project;279
7.7.2.2;2.2 Middleware Architecture;280
7.7.2.3;2.3 Grid Interactivity;280
7.7.3;3 Enabling Interactivity on the EGEE Grid;281
7.7.3.1;3.1 Interactive Jobs;281
7.7.3.2;3.2 Data Management Interactivity;282
7.7.3.3;3.3 Support from the Logging and Bookkeeping Service;282
7.7.3.4;3.4 Low Latency Scheduling;283
7.7.3.5;3.5 Pilot Jobs;283
7.7.3.6;3.6 Interactivity Through Support Tools;284
7.7.4;4 Network Support;284
7.7.5;5 Example Applications;285
7.7.5.1;5.1 Fusion;285
7.7.5.2;5.2 Bioinformatics;285
7.7.5.3;5.3 High Energy Physics;286
7.7.5.4;5.4 Astronomy;286
7.7.6;6 Conclusions and Related Work;287
7.7.7;References;288
8;Part IV Supporting Services;289
8.1;23 g-Eclipse -- A Middleware-Independent Framework for Accessing Existing Grid Infrastructures ;290
8.1.1;1 Introduction;290
8.1.2;2 Grid Roles and Contexts;291
8.1.3;3 Benefitting from the Eclipse Framework;293
8.1.4;4 The g-Eclipse Architecture;294
8.1.4.1;4.1 The Grid Model;294
8.1.4.2;4.2 Job Management;295
8.1.4.3;4.3 Data Management;296
8.1.4.4;4.4 Grid Project;296
8.1.4.5;4.5 Authentication and Authorisation;297
8.1.4.6;4.6 Middleware Implementations;298
8.1.5;5 A Common User Interface for Different Grid Middlewares;299
8.1.5.1;5.1 Grid Model Views;299
8.1.5.2;5.2 Perspectives;300
8.1.5.3;5.3 Wizards and Dialogs;302
8.1.6;6 Conclusions;303
8.1.7;References;304
8.2;24 Semantics-Based Context-Aware Dynamic Service Composition ;306
8.2.1;1 Introduction;306
8.2.2;2 Semantics-Based Context-Aware Dynamic Service Composition Framework;308
8.2.2.1;2.1 Component Service Model with Semantics (CoSMoS);308
8.2.2.2;2.2 Component Runtime Environment (CoRE);312
8.2.2.3;2.3 Semantic Graph-Based Service Composition (SeGSeC);313
8.2.3;3 Case Study;317
8.2.4;4 Simulation Experiments;319
8.2.4.1;4.1 Simulation Configuration and Evaluation Metrics;319
8.2.4.2;4.2 Performance Evaluation Against Heterogeneity and Dynamics of User Contexts;320
8.2.4.3;4.3 Performance Evaluation Against the Number of Possible Workflows;321
8.2.4.4;4.4 Performance Evaluation Against Dynamic Environments;322
8.2.5;5 Conclusions;322
8.2.6;References;323
8.3;25 Distributed e-Science Application for Computational Speech Science ;325
8.3.1;1 Introduction;325
8.3.2;2 Computational Speech Science;327
8.3.2.1;2.1 Computed Tomography (CT) Imaging, Three-Dimensional Model Reconstruction, and Construction of Computational Grids;327
8.3.2.2;2.2 CFD/CAA Simulations of Oral Airflow of Sibilant /s/;328
8.3.2.3;2.3 Current Issues in Computational Speech Science;328
8.3.3;3 Applying e-Science for Computational Speech Science;328
8.3.3.1;3.1 Computational Speech Science Portal;329
8.3.3.2;3.2 Visualization Portlet;330
8.3.3.3;3.3 Geographically Dispersed Storage;333
8.3.3.4;3.4 Large-Scale Data Transfer Over Wide-Area Networks;334
8.3.4;4 Current Implementations and Assessment at SC07 and JGN2 Symposium 2008;334
8.3.5;5 Conclusions;337
8.3.6;References;337
8.4;26 SynchroNet ;339
8.4.1;1 Introduction;339
8.4.2;2 GNSS-Based Synchronization;340
8.4.3;3 SynchroNet Overview;342
8.4.4;4 Distributed Synchronization;345
8.4.5;5 Implementation and Test Results;350
8.4.6;6 Conclusions;352
8.4.7;References;352
8.5;27 Discovery of Resources in a Distributed Grid Environment Based on Specific Service Level Agreements (SLAs) ;354
8.5.1;1 Introduction;354
8.5.1.1;1.1 Background Information and Objectives;355
8.5.2;2 The GRIA Grid Middleware;356
8.5.3;3 Contextualized Discovery Implementation;357
8.5.4;4 Conclusions;359
8.5.5;References;359
8.6;28 Inter-Domain SLA Enforcement in QoS-Enabled Networks;361
8.6.1;1 Introduction;361
8.6.2;2 Related Work;362
8.6.3;3 End-to-End SLA Framework;363
8.6.3.1;3.1 End-to-End SLA Issues;363
8.6.3.2;3.2 End-to-End SLA Template Description;363
8.6.3.3;3.3 SLA Framework Architecture;366
8.6.4;4 SLA Management;366
8.6.5;5 SLA Monitoring;367
8.6.6;6 Conclusions;368
8.6.7;References;369
9;Part V eVLBI and Cosmic Rays Detection;370
9.1;29 High-Bandwidth Data Acquisition and Network Streamingin VLBI;371
9.1.1;1 Introduction;371
9.1.2;2 High-Bandwidth Data Acquisition;372
9.1.2.1;2.1 10G Data Acquisition Design Requirements;373
9.1.2.2;2.2 10G Data Acquisition Hardware and Test Design;374
9.1.3;3 High-Bandwidth Network Streaming and Stream Capture;376
9.1.3.1;3.1 UDP-Based Streaming;378
9.1.3.2;3.2 Stream Recording;378
9.1.3.3;3.3 Tsunami UDP;380
9.1.4;4 Conclusions;381
9.1.5;References;381
9.2;30 Real-Time Software Correlation ;383
9.2.1;1 Introduction;383
9.2.2;2 VLBI;384
9.2.3;3 Software Correlator;387
9.2.3.1;3.1 Design;387
9.2.4;4 Execution and Deployment;389
9.2.4.1;4.1 Real Time and Quality of Service;389
9.2.4.2;4.2 Running SCARIe on DAS-3and Starplane;389
9.2.4.3;4.3 Benchmarks on DAS-3;390
9.2.5;5 Conclusions;392
9.2.6;References;392
9.3;31 AugerAccess -- Virtual Infrastructure for Simulating Complex Networks ;394
9.3.1;1 Introduction;394
9.3.2;2 Fundamentals;395
9.3.2.1;2.1 Auger Observatory;396
9.3.2.2;2.2 AugerAccess;397
9.3.2.3;2.3 Testbed;398
9.3.3;3 Architecture;400
9.3.3.1;3.1 Virtual Machines;402
9.3.3.2;3.2 Virtual Networks;402
9.3.3.3;3.3 Services on the network;403
9.3.4;4 Status and Results;404
9.3.4.1;4.1 Faced Problems;405
9.3.4.2;4.2 Remote Client;405
9.3.5;5 Discussion and Future;407
9.3.6;6 Conclusions;408
9.3.7;References;408
10;Part VI Metrology Issues;410
10.1;32 Challenges and Design Issues in a Distributed MeasurementScenario;411
10.1.1;1 Introduction;411
10.1.2;2 Topology Issues;413
10.1.3;3 Design Issues;414
10.1.4;4 Conclusions;419
10.1.5;References;419
10.2;33 The Distributed Measurement Systems: A New Challengefor the Metrologists ;422
10.2.1;1 Introduction;422
10.2.2;2 The Distributed Measurement Systems;423
10.2.2.1;2.1 The Architecture;423
10.2.2.2;2.2 The Metrology Problem;426
10.2.3;3 Clock Synchronization;427
10.2.3.1;3.1 GPS Synchronization;427
10.2.3.2;3.2 NTP Synchronization;428
10.2.3.3;3.3 Measurement Algorithms;428
10.2.4;4 Conclusions;429
10.2.5;References;429
10.3;34 Recent Progresses of the Remote Didactic Laboratory LA.DI.RE ``G. Savastano'' Project ;432
10.3.1;1 Introduction;432
10.3.2;2 Software and Hardware Architectures of the LA.DI.RE. ``G.Savastano'';434
10.3.3;3 Overview of the Didactic Experiments;435
10.3.3.1;3.1 Sampling and Windowing of Signals;435
10.3.3.2;3.2 Digital Oscilloscope Characterization;435
10.3.3.3;3.3 Automated Power Consumption Measurement of Wireless Modules;436
10.3.3.4;3.4 AC Power-Interference Cancellation in Electrocardiogram (ECG) Signals Using Adaptive Filters;436
10.3.3.5;3.5 Basic Electrical Measurements;437
10.3.3.6;3.6 Magnetic Measurements;438
10.3.3.7;3.7 Uncertainty Characterization of Digital Instrumentation;439
10.3.4;4 Measurement Bench for Remote Laboratory Activities;440
10.3.5;5 Real-Time Visualization of the Instruments Duringthe Experimental Session;440
10.3.6;6 Testing the Quality of the System;442
10.3.7;7 Conclusions;444
10.3.8;References;445
10.4;35 A Software Architecture for the m-Learning in Instrumentation and Measurement;448
10.4.1;1 Introduction;448
10.4.2;2 Services Delivered by Means of LA.DI.RE. ``G. Savastano'';450
10.4.3;3 Technical Characteristics of Mobile Devices;451
10.4.3.1;3.1 Hardware Limitations;451
10.4.3.2;3.2 Software Limitations;452
10.4.3.3;3.3 Bandwidth Limitations;452
10.4.4;4 Software Architecture for the m-Learning;452
10.4.4.1;4.1 Experiment Visualization;453
10.4.4.2;4.2 Experiment Control;454
10.4.4.3;4.3 Experiment Creation;455
10.4.5;5 Design of the New Experiment Creation Module;455
10.4.6;6 An Example of Experiment Creation;458
10.4.7;7 Conclusions;459
10.4.8;References;460
11;Part VII Sensor Networks for Measurement;461
11.1;36 Performance of Linear Field Reconstruction Techniques with Noise and Correlated Field Spectrum ;462
11.1.1;1 Introduction;462
11.1.2;2 Preliminaries;463
11.1.2.1;2.1 Irregular Sampling and Reconstruction of Multidimensional, Band-Limited Signals;463
11.1.2.2;2.2 Previous Results on Reconstruction Quality;465
11.1.3;3 Mathematical Background;466
11.1.3.1;3.1 Large Random Matrices and Asymptotic Spectrum Characterization;466
11.1.3.2;3.2 Random Matrix Transforms and Freeness;467
11.1.4;4 Main Results and Applications;468
11.1.4.1;4.1 Examples of Applications;470
11.1.5;5 Conclusions;473
11.1.6;References;473
11.2;37 Hybrid Zigbee--RFID Networks for Energy Saving and Lifetime Maximization ;475
11.2.1;1 Introduction;476
11.2.2;2 Zigbee Standard Overview;477
11.2.3;3 RFID Technology;478
11.2.4;4 Hybrid Zigbee--RFID Networks;479
11.2.4.1;4.1 System Model;479
11.2.4.2;4.2 Opnet Simulator Structure;480
11.2.4.3;4.3 Deep Sleep Algorithm;481
11.2.4.4;4.4 Deep Sleep Algorithm with Virtual Spatial Grid;484
11.2.5;5 Performance Analysis;485
11.2.5.1;5.1 Deep Sleep Algorithm;487
11.2.5.2;5.2 Impact of the Virtual Spatial Grid;489
11.2.6;6 Conclusions;491
11.2.7;References;492
11.3;38 A Service-Oriented Wireless Sensor Network for Power Metering ;494
11.3.1;1 Introduction;494
11.3.2;2 System Architecture;495
11.3.3;3 The Gateway;496
11.3.4;4 The WSN Node;497
11.3.5;5 Application Scenario;498
11.3.6;6 Conclusions;500
11.3.7;References;501
11.4;39 Performance Evaluation of a Robust Data Aggregation Approach in Diverse Sensor Networking Environments ;502
11.4.1;1 Introduction;502
11.4.1.1;1.1 Related Work;503
11.4.1.2;1.2 Motivation and Objective;504
11.4.2;2 Framework Overview;505
11.4.3;3 Diverse Application Environments;506
11.4.4;4 Performance Evaluation and Discussion;507
11.4.4.1;4.1 Models and Scenarios;507
11.4.4.2;4.2 Numerical Results;508
11.4.5;5 Conclusions;511
11.4.6;References;511
12;Author Index;513
13;Subject Index;517