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Opportunistic Channels: Mobility-Aware Event Delivery

  • Yuan Chen
  • Karsten Schwan
  • Dong Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2672)

Abstract

The delivery of data in pervasive systems has to deal with end host mobility. One problem is how to create appropriate, application-level data provisioning topologies, termed data brokers, to best match underlying network connectivity, end user locations, and the locales of their network access. Another problem is how to balance workloads in such overlay networks, in response to mobility and to changes in available processing and communication resources. This paper improves the performance of data provisioning by dynamically changing broker topologies and end users’ assignments to brokers. Specifically, using publish/ subscribe as a communication paradigm, a new abstraction, termed an opportunistic event channel, enables dynamic broker creation, deletion, and movement. Experimental and simulation results demonstrate the ability of opportunistic channels to optimize event delivery and processing when end users move across di.erent network access points. The technique is to ‘opportunistically’ follow network-level handoffs across network access points with application-level handoffs of a user’s broker functionality to a new, ‘closer’ broker. The potential load imbalances across brokers caused by such handoffs are also addressed. Opportunistic channels are realized with the JECho event infrastructure. Performance advantages attained from their use can be substantial, with the cost of sending a message from a publisher to a mobile subscriber improved by up to 50%. Load balancing improves event delivery even for moderate numbers of event subscribers.

Keywords

Mobile Host Overlay Network Mobile Environment Mobile Client Event Delivery 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© IFIP International Federation for Information Processing 2003

Authors and Affiliations

  • Yuan Chen
    • 1
  • Karsten Schwan
    • 1
  • Dong Zhou
    • 2
  1. 1.Georgia Institute of TechnologyCollege of ComputingAtlantaUSA
  2. 2.DoCoMo USA LabsSan JoseUSA

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