Towards Intelligent Dynamic Deployment of Mobile Sensors in Complex Resource-Bounded Environments

PDF Version Also Available for Download.

Description

Decision-making in the face of uncertainty requires an understanding of the probabilistic mechanisms that govern the complex behavior of these systems. This issue applies to many domains: financial investments, disease control, military planning and homeland security. In each of these areas, there is a practical need for efficient resource-bounded reasoning capabilities to support optimal decision-making. Specifically, given a highly complex system, with numerous random variables and their dynamic interactions, how do we monitor such a system and detect crucial events that might impact our decision making process? More importantly, how do we perform this reasoning efficiently--to an acceptable degree of ... continued below

Physical Description

PDF-file: 14 pages; size: 0.1 Mbytes

Creation Information

Ng, B M & Hanley, W G May 8, 2007.

Context

This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

Who

People and organizations associated with either the creation of this report or its content.

Publisher

Provided By

UNT Libraries Government Documents Department

Serving as both a federal and a state depository library, the UNT Libraries Government Documents Department maintains millions of items in a variety of formats. The department is a member of the FDLP Content Partnerships Program and an Affiliated Archive of the National Archives.

Contact Us

What

Descriptive information to help identify this report. Follow the links below to find similar items on the Digital Library.

Description

Decision-making in the face of uncertainty requires an understanding of the probabilistic mechanisms that govern the complex behavior of these systems. This issue applies to many domains: financial investments, disease control, military planning and homeland security. In each of these areas, there is a practical need for efficient resource-bounded reasoning capabilities to support optimal decision-making. Specifically, given a highly complex system, with numerous random variables and their dynamic interactions, how do we monitor such a system and detect crucial events that might impact our decision making process? More importantly, how do we perform this reasoning efficiently--to an acceptable degree of accuracy in real time--when there are only limited computational power and sensory capabilities? These questions encapsulate nontrivial key issues faced by many high-profile Laboratory missions: the problem of efficient inference and dynamic sensor deployment for risk/uncertainty reduction. By leveraging solid ideas such as system decomposition into loosely coupled subsystems and smart resource allocation among these subsystems, we can parallelize inference and data acquisition for faster and improved computational performance. In this report, we propose technical approaches for developing algorithmic tools to enable future scientific and engineering endeavors to better achieve the optimal use of limited resources for maximal return of information on a complex system. The result of the proposed research effort will be an efficient reasoning framework that would enable mobile sensors to work collaboratively as teams of adaptive and responsive agents, whose joint goal is to gather useful information that would assist in the inference process.

Physical Description

PDF-file: 14 pages; size: 0.1 Mbytes

Language

Item Type

Identifier

Unique identifying numbers for this report in the Digital Library or other systems.

  • Report No.: UCRL-TR-231422
  • Grant Number: W-7405-ENG-48
  • DOI: 10.2172/919953 | External Link
  • Office of Scientific & Technical Information Report Number: 919953
  • Archival Resource Key: ark:/67531/metadc896620

Collections

This report is part of the following collection of related materials.

Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

What responsibilities do I have when using this report?

When

Dates and time periods associated with this report.

Creation Date

  • May 8, 2007

Added to The UNT Digital Library

  • Sept. 27, 2016, 1:39 a.m.

Description Last Updated

  • Dec. 7, 2016, 11:17 p.m.

Usage Statistics

When was this report last used?

Congratulations! It looks like you are the first person to view this item online.

Interact With This Report

Here are some suggestions for what to do next.

Start Reading

PDF Version Also Available for Download.

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Ng, B M & Hanley, W G. Towards Intelligent Dynamic Deployment of Mobile Sensors in Complex Resource-Bounded Environments, report, May 8, 2007; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc896620/: accessed October 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.