Enabling End-to-End Data-Driven Sensor-Based Scientific and Engineering Applications

Authors:
Nanyan Jiang;Manish Parashar
Affiliations:
Center for Autonomic Computing (CAC) & The Applied Software Systems Laboratory (TASSL) Department of Electrical and Computer Engineering, Rutgers University, Piscataway, USA NJ 08855;Center for Autonomic Computing (CAC) & The Applied Software Systems Laboratory (TASSL) Department of Electrical and Computer Engineering, Rutgers University, Piscataway, USA NJ 08855
Venue:
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Year:
2009

Citing 9
Cited 0

TinyDB: an acquisitional query processing system for sensor networks

ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
The Abstract Task Graph: a methodology for architecture-independent programming of networked sensor systems

EESR '05 Proceedings of the 2005 workshop on End-to-end, sense-and-respond systems, applications and services
Models, methods and middleware for grid-enabled multiphysics oil reservoir management

Engineering with Computers
Programming sensor networks using abstract regions

NSDI'04 Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation - Volume 1
The Ring Buffer Network Bus (RBNB) DataTurbine Streaming Data Middleware for Environmental Observing Systems

E-SCIENCE '07 Proceedings of the Third IEEE International Conference on e-Science and Grid Computing
State-Centric Programming for Sensor-Actuator Network Systems

IEEE Pervasive Computing
In-network data estimation for sensor-driven scientific applications

HiPC'08 Proceedings of the 15th international conference on High performance computing
Macro-programming wireless sensor networks using Kairos

DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Towards dynamic data-driven management of the ruby gulch waste repository

ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III

Quantified Score

Hi-index	0.00

Visualization

Abstract

Technical advances are leading to a pervasive computational infrastructure that integrates computational processes with embedded sensors and actuators, and giving rise to a new paradigm for monitoring, understanding, and managing natural and engineered systems --- one that is information/data-driven. However, developing and deploying these applications remains a challenge, primarily due to the lack of programming and runtime support. This paper addresses these challenges and presents a programming system for end-to-end sensor/actuator-based scientific and engineering applications. Specifically, the programming system provides semantically meaningful abstractions and runtime mechanisms for integrating sensor systems with computational models for scientific processes, and for in-network data processing such as aggregation, adaptive interpolation and assimilations. The overall architecture of the programming system and the design of its key components, as well as its prototype implementation are described. An end-to-end dynamic data-driven oil reservoir application that combines reservoir simulation models with sensors/actuators in an instrumented oilfield is used as a case study to demonstrate the operation of the programming system, as well as to experimentally demonstrate its effectiveness and performance.