A probabilistic-approach based resource allocation algorithm in pervasive computing systems

Mianxiong Dong, Long Zheng, Kaoru Ota, Jun Ma, Song Guo, Minyi Guo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)


Ubiquitous technologies are indispensable for modernizing human daily life more and more. However, the technologies are not easily widespread everywhere in our world through infrastructures and other related techniques. We have worked on a project to meet these challenges with a goal to construct a framework for the coming ubiquitous society. In our previous works, we have proposed UMP-PerComp, a Ubiquitous Multiprocessor-based pipeline Processing architecture, to support development of powerful and pervasive applications. In this paper, we propose an optimized algorithm for the UMP system to improve resource allocation executed by one kind of processing nodes called the Resource Router (RR). Using the optimized algorithm, the RR can effectively find a node in the idle state, which actually processes a task assigned by the RR. As a result, the RR saves the time to search for an idle node so that total performance can be improved. Finally, we evaluate the optimized algorithm with probability analyses to show effectiveness more than the previous algorithm we used.
Original languageEnglish
Title of host publicationICCASM 2010 - 2010 International Conference on Computer Application and System Modeling, Proceedings
Publication statusPublished - 6 Dec 2010
Externally publishedYes
Event2010 International Conference on Computer Application and System Modeling, ICCASM 2010 - Shanxi, Taiyuan, China
Duration: 22 Oct 201024 Oct 2010


Conference2010 International Conference on Computer Application and System Modeling, ICCASM 2010
CityShanxi, Taiyuan


  • Pervasive computing
  • Probabilistic approach
  • Processing elements
  • Resource allocation algorithm

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

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