Combining Infrastructure and Ad Hoc Collaboration for Data Management in Mobile Wireless Networks

Abstract

A mobile ad-hoc network is an autonomous system of mobile routers that are self-organizing and completely decentralized with no requirements for dedicated infrastructure support. However, such infrastructure in terms of base stations is available in many popular areas already. These base stations often offer high-speed data connectivity to a wired network. In this paper, we describe an approach where a combination of infrastructure and ad hoc communication can be used to better manage the data needs of a mobile wireless device. In our approach, base stations track user mobility and determine data usage patterns of users passing by. Based on this, future data needs of a mobile device can be predicted. Base stations can collaborate (over the wired network) to identify other mobile devices with spare capacity whose routes intersect that of a needy device and use these carriers to transport data. When such a carrier meets the needy device, they can form ad hoc per-to-peer communities to transfer the carried data. We also present the motivation, architecture and design of NUMI, our framework for supporting combined infrastructure and ad hoc peer-to-peer computing and prototype application built on top of this framework.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2005
Accession Number
ADA440200

Entities

People

  • Anupam Joshi
  • Olga Ratsimor
  • Sethuram B. Kodeswaran
  • Tim Finin
  • Yelena Yesha

Organizations

  • University of Maryland, Baltimore

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Ad Hoc Networks
  • Computer Networks
  • Computer Programming
  • Computer Science
  • Computers
  • Data Links
  • Data Management
  • Load Monitoring
  • Mesh Networks
  • Mobile Computing
  • Mobile Devices
  • Mobile Phones
  • Models
  • Personal Digital Assistants
  • Prototypes
  • Wireless Communications
  • Wireless Networks

Fields of Study

  • Computer science
  • Engineering

Readers

  • Defense Technology Research and Development.
  • Neural Network Machine Learning.
  • Radio communications and signal processing.

Technology Areas

  • Autonomy