Publications from our Researchers

Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.  

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  • Journal article
    Dustdar S, Guo Y, Han R, Satzger B, Hong-Linh Tet al., 2012,

    Programming Directives for Elastic Computing

    , IEEE INTERNET COMPUTING, Vol: 16, Pages: 72-77, ISSN: 1089-7801
  • Journal article
    Yang X, Han R, Guo Y, Bradley J, Cox B, Dickinson R, Kitney Ret al., 2012,

    Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA

    , Bmc Bioinformatics, Vol: 13, ISSN: 1471-2105
  • Conference paper
    Yang X, Guo Y, Bradley J, 2012,

    An iterative parameter estimation method for biological systems

  • Conference paper
    Wu C, Guo Y, 2012,

    A semantic relatedness service based on folksonomy

    , Pages: 506-511
  • Conference paper
    He S, Guo L, Ghanem M, Guo Yet al., 2012,

    Improving Resource Utilisation in the Cloud Environment Using Multivariate Probabilistic Models

    , Pages: 574-581, ISSN: 2159-6182
  • Conference paper
    Guo Y, Ghanem M, Han R, 2012,

    Does the Cloud Need New Algorithms? An Introduction to Elastic Algorithms

    , 4th IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Publisher: IEEE, ISSN: 2330-2194
  • Book chapter
    Guo Y, Yang X, 2012,

    System Biology Approach to Study Cancer Related Pathway

    , Systems Biology in Cancer Research and Drug Discovery
  • Conference paper
    Holehouse A, Yang X, Adcock I, Guo Yet al., 2012,

    Developing a novel integrated model of p38 MAPK and glucocorticoid signalling pathways

    , Pages: 69-76
  • Conference paper
    Li Y, Guo L, Guo Y, 2012,

    CACSS: Towards a Generic Cloud Storage Service.

  • Conference paper
    Wu C, Guo Y, 2012,

    A New Paradigm for Web App Development, Deployment, Distribution, and Collaboration

  • Conference paper
    Han R, Guo L, Ghanem MM, Guo Yet al., 2012,

    Lightweight Resource Scaling for Cloud Applications

    , Washington, DC, USA, Publisher: IEEE Computer Society, Pages: 644-651
  • Journal article
    Silva D, Ghanem M, Guo Y, 2012,

    WikiSensing: An Online Collaborative Approach for Sensor Data Management

    , Sensors
  • Journal article
    Wu C, Guo Y, Zhou B, 2012,

    Social networking federation: A position paper

    , Computers & Electrical Engineering
  • Conference paper
    Yan S, Wu C, Dai W, Ghanem M, Guo Yet al., 2012,

    Environmental monitoring via compressive sensing

    , New York, NY, USA, Publisher: ACM, Pages: 61-68
  • Conference paper
    He S, Guo L, Guo Y, 2011,

    Elastic Application Container

    , 12th IEEE/ACM International Conference on Grid Computing (GRID), Publisher: IEEE, Pages: 216-217, ISSN: 1550-5510

    The computing resource level architecture allows end-users to directly control its underlying computer resources, such as VM (virtual machine) operations, scaling, networking, etc. However, setting up and maintaining a working environment is complex and time consuming for end-users and resource management is also a heavy-weight task for the providers. In contrast, the application resource level architecture automatically controls its underlying computer resources so that end-users can concentrate on their core business. In this paper, we propose a new architecture called Elastic Application Container (EAC) that enables the end-users to efficiently develop and deliver light-weight, elastic, multi-tenant, and portable applications. The EAC is an abstract representation which hides all its abstractions of the underlying VMs. We believe that our EAC architecture has the potential to become the foundation of future application resource level model in this research area.

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