Supporting terminal mobility by means of self-adaptive communication object migration

ABSTRACT

Mobile devices, like PDAs or smart phones, exhibit limited capabilities in terms of processing power and memory. Supported by advanced WLAN hotspot grid infrastructures, mobile terminals may enhance their computing capabilities significantly by utilizing remote resources in virtually shared spaces. Due to privacy and performance issues, the shared communication objects should be kept in proximity to the roaming owner which requires object migration.We propose a novel self-adaptive decision algorithm for object migration based on a cost-benefit function. This function considers parameters describing the expected latency caused by migration and the expected response time saved by local access. The importance of each parameter is determined by a weight and adapted using Bayesian concept learning. The feasibility of the approach is demonstrated by a prototypical implementation for PDAs based on the space-based middleware CORSO. We further investigate the decision algorithm by means of simulation.

REFERENCES

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INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.4 Distributed Systems
          Subjects: Distributed applications

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.6 Learning
          Subjects: Concept learning

General Terms:
Algorithms, Design, Performance

Keywords:
mobile grid computing, object migration, self-adaptiveness, terminal mobility