A shadow-Like task migration model based on context semantics for mobile and pervasive environments

Feilong Tang, Can Tang, Minyi Guo, Shui Yu, Song Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Pervasive computing is a user-centric mobile computing paradigm, in which tasks should be migrated over different platforms in a shadow-like way when users move around. In this paper, we propose a context-sensitive task migration model that recovers program states and rebinds resources for task migrations based on context semantics through inserting resource description and state description sections in source programs. Based on our model, we design and develop a task migration framework xMozart which extends the Mozart platform in terms of context awareness. Our approach can recover task states and rebind resources in the context-aware way, as well as support multi- modality I/O interactions. The extensive experiments demonstrate that our approach can migrate tasks by resuming them from the last broken points like shadows moving along with the users.
Original languageEnglish
Pages (from-to)1131-1146
Number of pages16
JournalComputing and Informatics
Volume30
Issue number6
Publication statusPublished - 1 Dec 2011
Externally publishedYes

Keywords

  • Context-aware computing
  • Pervasive computing
  • Task migration

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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