Tailoring Configuration to User's Tasks under Uncertainty

Abstract

Currently, the burden of managing the computing environment (devices, applications, and resources) falls on the user. A user must manually start applications and adjust their settings according to the available resources. Assigning such chores of configuration to the user has a number of disadvantages. Ideally, the computing needs of a user are seamlessly matched with the capabilities of the environment: devices, applications, and available resources. The user should enjoy the best possible application quality, without worrying about managing the low-level computing mechanisms. In this dissertation, we describe a novel approach that substantially automates the control of the configuration of the environment for a user's task: finding and starting applications, configuring their runtime settings, and allocating possibly limited resources. Our approach simultaneously satisfies two important requirements: utility and practicality. Utility ensures that configuration decisions take into account user's preferences for specific applications and quality of service. Practicality ensures that configuration has low runtime overhead in terms of the latency of configuration decisions and its usage of resources. First, we model configuration analytically as a problem of optimizing user's utility based on three inputs: (1) user's preferences, (2) application capability, and (3) resource availability. Formally, automating the control of the configuration requires solving an optimization problem, and then using the optimization solution to control the environment. Next, we design a software infrastructure that is based on the analytical model. The infrastructure implements efficient algorithms to solve the problem of configuration, eliminating the need for manual configuration. We validate our approach using experiments and simulation, demonstrating that the infrastructure satisfies the requirements of utility and practicality while substantially automating configuration.

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Document Details

Document Type
Technical Report
Publication Date
Apr 28, 2008
Accession Number
ADA487782

Entities

People

  • Vahe V. Poladyan

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Adaptive Systems
  • Coding
  • Computer Programming
  • Computer Science
  • Computers
  • Control Systems
  • Human Factors Engineering
  • Human Systems Integration
  • Internet
  • Mobile Computing
  • Mobile Devices
  • Network Protocols
  • Operating Systems
  • Software Design
  • Ubiquitous Computing
  • Weather Forecasting
  • Web Browsers

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Operations Research
  • Parallel and Distributed Computing.