Amol B. Bakshi, PhD, is a Research Assistant Professor in the Ming Hsieh Department of Electrical Engineering at the University of Southern California (USC), Los Angeles. He also manages the Integrated Asset Management project at the USC-Chevron Center of Excellence for Research and Academic Training on Interactive Smart Oilfield Technologies. Dr. Bakshi's PhD research was on programming models for networked sensor systems and led to the creation of the ATaG programming model and software synthesis toolkit. His current interests include semantic Web technologies for information integration, smart oilfield technologies, model integrated computing, and sensor networks.Viktor K. Prasanna, PhD, is Charles Lee Powell Chair in Engineering and Professor of Electrical Engineering and Professor of Computer Science at the University of Southern California (USC), Los Angeles. He is also an associate member of the Center for Applied Mathematical Sciences (CAMS) at USC, and a member of the USC-Chevron Center of Excellence for Research and Academic Training on Interactive Smart Oilfield Technologies. He has served on the editorial boards of the Journal of Parallel and Distributed Computing, Proceedings of the IEEE, IEEE Transactions on VLSI Systems, and IEEE Transactions on Parallel and Distributed Systems. He was editor-in-chief of the IEEE Transactions on Computers and was the founding chair of the IEEE Computer Society Technical Committee on Parallel Processing. He is a Fellow of the IEEE and the ACM.

• Preface. Acknowledgments.1. Introduction.1.1 Sensor networks and traditional distributed systems.1.2 Programming of distributed sensor networks.1.2.1 Layers of programming abstraction.1.2.1.1 Service-oriented specification.1.2.1.2 Macroprogramming.1.2.1.3 Node-centric programming.1.2.2 Lessons from parallel and distributed computing.1.3 Macroprogramming: What and Why?1.4 Contributions and Outline.2. The Abstract Task Graph.2.1 Target applications and architectures.2.2 Key Concepts.2.2.1 Data Driven Computing.2.2.1.1 Program flow mechanisms.2.2.1.2 Why data driven?2.2.2 Mixed Imperative-Declarative Specification.2.3 Syntax.2.3.1 The Structure of an ATaG Program.2.3.2 More on Task Annotations.2.3.3 Illustrative examples.2.4 Semantics.2.4.1 Terminology.2.4.2 Firing rules.2.4.3 Task graph execution.2.4.4 get() and put().2.5 Programming idioms.2.5.1 Object tracking.2.5.2 Interaction within local neighborhoods.2.5.3 In-network aggregation.2.5.4 Hierarchical data fusion.2.5.5 Event-triggered behavior instantiation.2.6 Future work.2.6.1 State-based dynamic behaviors.2.6.2 Resource management in the runtime system.2.6.3 Utility based negotiation for task scheduling and resource allocation.2.6.4 Analyzing feasibility of compilation.3. DART:The Data Driven ATaG Runtime.3.1 Design objectives.3.1.1 Support for ATaG semantics.3.1.2 Platform independence.3.1.3 Component-based design.3.1.4 Ease of software synthesis.3.2 Overview.3.3 Components and functionalities.3.3.1 Task, Data, and Channel Declarations.3.3.2 UserTask.3.3.2.1 Service.3.3.2.2 Interactions.3.3.2.3 Implementation.3.3.3 DataPool.3.3.3.1 Service.3.3.3.2 Interactions.3.3.3.3 Implementation.3.3.4 AtagManager.3.3.4.1 Service.3.3.4.2 Interactions.3.3.4.3 Implementation.3.3.5 NetworkStack.3.3.5.1 Service.3.3.5.2 Interactions.3.3.5.3 Implementation.3.3.6 NetworkArchitecture.3.3.6.1 Service.3.3.6.2 Interactions.3.3.6.3 Implementation.3.3.7 Dispatcher.3.3.7.1 Service.3.3.7.2 Interactions.3.3.7.3 Implementation.3.4 Control flow.3.4.1 Startup.3.4.2 get() and put().3.4.3 Illustrative example.3.5 Future work.3.5.1 Lazy compilation of channel annotations.3.5.2 Automatic priority assignment for task scheduling.4. Programming and Software Synthesis.4.1 Terminology.4.2 Meta-modeling for the ATaG domain.4.2.1 Objectives.4.2.2 Application model.4.2.3 Network model.4.3 The programming interface.4.4 Compilation and software synthesis.4.4.1 Translating task annotations.4.4.2 Automatic software synthesis.4.4.3 The ATaG simulator.4.4.4 Initialization.4.4.4.1 Situatedness.4.4.4.2 Network interface.4.4.4.3 Network architecture.4.4.4.4 Sensor interface.4.4.5 Visualizing synthesized application behavior.5 Case Study: Application Development with ATaG.5.1 Overview of the use case.5.2 Designing the macroprograms.5.2.1 Temperature gradient monitoring.5.2.2 Object detection and tracking.5.3 Specifying the declarative portion.5.4 Imperative portion: Temperature gradient monitoring.5.4.1 Abstract data items: Temperature and Fire.5.4.2 Abstract Task: Monitor.5.4.3 Abstract Task: Temperature Sampler.5.4.4 Abstract Task: Alarm Actuator.5.5 Imperative portion: Object detection and tracking.5.5.1 Abstract data items: TargetAlert and TargetInfo.5.5.2 Abstract Task: SampleAndThreshold.5.5.3 Abstract Task: Leader.5.5.4 Abstract Task: Supervisor.5.6 Application Composition.5.7 Software Synthesis.6 Concluding Remarks.6.1 A framework for domain-specific application development.6.2 A framework for compilation and software synthesis.References.

Amol B. Bakshi, PhD, is a Research Assistant Professor in the Ming Hsieh Department of Electrical Engineering at the University of Southern California (USC), Los Angeles. He also manages the Integrated Asset Management project at the USC-Chevron Center of Excellence for Research and Academic Training on Interactive Smart Oilfield Technologies. Dr. Bakshi's PhD research was on programming models for networked sensor systems and led to the creation of the ATaG programming model and software synthesis toolkit. His current interests include semantic Web technologies for information integration, smart oilfield technologies, model integrated computing, and sensor networks.Viktor K. Prasanna, PhD, is Charles Lee Powell Chair in Engineering and Professor of Electrical Engineering and Professor of Computer Science at the University of Southern California (USC), Los Angeles. He is also an associate member of the Center for Applied Mathematical Sciences (CAMS) at USC, and a member of the USC-Chevron Center of Excellence for Research and Academic Training on Interactive Smart Oilfield Technologies. He has served on the editorial boards of the Journal of Parallel and Distributed Computing, Proceedings of the IEEE, IEEE Transactions on VLSI Systems, and IEEE Transactions on Parallel and Distributed Systems. He was editor-in-chief of the IEEE Transactions on Computers and was the founding chair of the IEEE Computer Society Technical Committee on Parallel Processing. He is a Fellow of the IEEE and the ACM.

• Preface. Acknowledgments.1. Introduction.1.1 Sensor networks and traditional distributed systems.1.2 Programming of distributed sensor networks.1.2.1 Layers of programming abstraction.1.2.1.1 Service-oriented specification.1.2.1.2 Macroprogramming.1.2.1.3 Node-centric programming.1.2.2 Lessons from parallel and distributed computing.1.3 Macroprogramming: What and Why?1.4 Contributions and Outline.2. The Abstract Task Graph.2.1 Target applications and architectures.2.2 Key Concepts.2.2.1 Data Driven Computing.2.2.1.1 Program flow mechanisms.2.2.1.2 Why data driven?2.2.2 Mixed Imperative-Declarative Specification.2.3 Syntax.2.3.1 The Structure of an ATaG Program.2.3.2 More on Task Annotations.2.3.3 Illustrative examples.2.4 Semantics.2.4.1 Terminology.2.4.2 Firing rules.2.4.3 Task graph execution.2.4.4 get() and put().2.5 Programming idioms.2.5.1 Object tracking.2.5.2 Interaction within local neighborhoods.2.5.3 In-network aggregation.2.5.4 Hierarchical data fusion.2.5.5 Event-triggered behavior instantiation.2.6 Future work.2.6.1 State-based dynamic behaviors.2.6.2 Resource management in the runtime system.2.6.3 Utility based negotiation for task scheduling and resource allocation.2.6.4 Analyzing feasibility of compilation.3. DART:The Data Driven ATaG Runtime.3.1 Design objectives.3.1.1 Support for ATaG semantics.3.1.2 Platform independence.3.1.3 Component-based design.3.1.4 Ease of software synthesis.3.2 Overview.3.3 Components and functionalities.3.3.1 Task, Data, and Channel Declarations.3.3.2 UserTask.3.3.2.1 Service.3.3.2.2 Interactions.3.3.2.3 Implementation.3.3.3 DataPool.3.3.3.1 Service.3.3.3.2 Interactions.3.3.3.3 Implementation.3.3.4 AtagManager.3.3.4.1 Service.3.3.4.2 Interactions.3.3.4.3 Implementation.3.3.5 NetworkStack.3.3.5.1 Service.3.3.5.2 Interactions.3.3.5.3 Implementation.3.3.6 NetworkArchitecture.3.3.6.1 Service.3.3.6.2 Interactions.3.3.6.3 Implementation.3.3.7 Dispatcher.3.3.7.1 Service.3.3.7.2 Interactions.3.3.7.3 Implementation.3.4 Control flow.3.4.1 Startup.3.4.2 get() and put().3.4.3 Illustrative example.3.5 Future work.3.5.1 Lazy compilation of channel annotations.3.5.2 Automatic priority assignment for task scheduling.4. Programming and Software Synthesis.4.1 Terminology.4.2 Meta-modeling for the ATaG domain.4.2.1 Objectives.4.2.2 Application model.4.2.3 Network model.4.3 The programming interface.4.4 Compilation and software synthesis.4.4.1 Translating task annotations.4.4.2 Automatic software synthesis.4.4.3 The ATaG simulator.4.4.4 Initialization.4.4.4.1 Situatedness.4.4.4.2 Network interface.4.4.4.3 Network architecture.4.4.4.4 Sensor interface.4.4.5 Visualizing synthesized application behavior.5 Case Study: Application Development with ATaG.5.1 Overview of the use case.5.2 Designing the macroprograms.5.2.1 Temperature gradient monitoring.5.2.2 Object detection and tracking.5.3 Specifying the declarative portion.5.4 Imperative portion: Temperature gradient monitoring.5.4.1 Abstract data items: Temperature and Fire.5.4.2 Abstract Task: Monitor.5.4.3 Abstract Task: Temperature Sampler.5.4.4 Abstract Task: Alarm Actuator.5.5 Imperative portion: Object detection and tracking.5.5.1 Abstract data items: TargetAlert and TargetInfo.5.5.2 Abstract Task: SampleAndThreshold.5.5.3 Abstract Task: Leader.5.5.4 Abstract Task: Supervisor.5.6 Application Composition.5.7 Software Synthesis.6 Concluding Remarks.6.1 A framework for domain-specific application development.6.2 A framework for compilation and software synthesis.References.