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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    Dalby AR, Emam I, Franke R, 2012,

    Analysis of Gene Expression Data from Non-Small Cell Lung Carcinoma Cell Lines Reveals Distinct Sub-Classes from Those Identified at the Phenotype Level

    , PLOS ONE, Vol: 7, ISSN: 1932-6203
    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
    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
    Guo Y, Yang X, 2012,

    System Biology Approach to Study Cancer Related Pathway

    , Systems Biology in Cancer Research and Drug Discovery
    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
    He S, Guo L, Ghanem M, Guo Yet al., 2012,

    Improving resource utilisation in the cloud environment using multivariate probabilistic models

    , Pages: 574-581

    Resource provisioning based on virtual machine (VM) has been widely accepted and adopted in cloud computing environments. A key problem resulting from using static scheduling approaches for allocating VMs on different physical machines (PMs) is that resources tend to be not fully utilised. Although some existing cloud reconfiguration algorithms have been developed to address the problem, they normally result in high migration costs and low resource utilisation due to ignoring the multi-dimensional characteristics of VMs and PMs. In this paper we present and evaluate a new algorithm for improving resource utilisation for cloud providers. By using a multivariate probabilistic model, our algorithm selects suitable PMs for VM re-allocation which are then used to generate a reconfiguration plan. We also describe two heuristics metrics which can be used in the algorithm to capture the multi-dimensional characteristics of VMs and PMs. By combining these two heuristics metrics in our experiments, we observed that our approach improves the resource utilisation level by around 8% for cloud providers, such as IC Cloud, which accept user-defined VM configurations and 14% for providers, such as Amazon EC2, which only provide limited types of VM configurations. © 2012 IEEE.

    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

    Glucocorticoid (GC) resistance is a key mechanism by which traditional asthma treatments become ineffective for patients, yet the molecular characteristics of the associated regulatory changes are largely unknown. Significant evidence suggests that crosstalk between p38 Mitogen Activated Protein Kinase (MAPK) and GC signalling pathways may contribute to this resistance. Based on a number of studies, a simplified GC signalling pathway model was developed and integrated with a pre-existing model of the p38 MAPK pathway. It is predicted that with experimental data, the validity and use of this model can be confirmed, corrections and updates can be made where necessary, and that through the two pathways' interface points the existence and scale of crosstalk can be examined. © 2012 IEEE.

    Li Y, Guo L, Guo Y, 2012,

    CACSS: Towards a generic cloud storage service

    , Pages: 27-36

    The advent of the cloud era has yielded new ways of storing, accessing and managing data. Cloud storage services enable the storage of data in an inexpensive, secure, fast, reliable and highly scalable manner over the internet. Although giant providers such as Amazon and Google have made a great success of their services, many enterprises and scientists are still unable to make the transition into the cloud environment due to often insurmountable issues of privacy, data protection and vendor lock-in. These issues demand that it be possible for anyone to setup or to build their own storage solutions that are independent of commercially available services. However, the question persists as to how to provide an effective cloud storage service with regards to system architecture, resource management mechanisms, data reliability and durability, as well as to provide proper pricing models. The aim of this research is to present an in-depth understanding and analysis of the key features of generic cloud storage services, and of how such services should be constructed and provided. This is achieved through the demonstration of design rationales and the implementation details of a real cloud storage system (CACSS). The method by which different technologies can be combined to provide a single excellent performance, highly scalable and reliable cloud storage system is also detailed. This research serves as a knowledge source for inexperienced cloud providers, giving them the capability of swiftly setting up their own cloud storage services.

    Silva D, Ghanem M, Guo Y, 2012,

    WikiSensing: An Online Collaborative Approach for Sensor Data Management

    , SENSORS, Vol: 12, Pages: 13295-13332, ISSN: 1424-8220
    Simondetti A, Roberts S, Birch D, 2012,

    A Practical Perspective on Computer Tools for Sustainable Building Design

    , Proceedings of the 2012 International EG-ICE Workshop on Intelligent Computing, Herrsching, Germany
    Simondetti A, Roberts S, Birch D, 2012,

    BEM for Collaborative Design Inception: Harnessing the Power of Clients’ Design Intuition

    , The 2012 International Conference on Modeling, Simulation & Visualization Methods.
    Wu C, Guo Y, 2012,

    A semantic relatedness service based on folksonomy

    , Pages: 506-511

    In this paper, we introduced a new approach of measure the semantic relatedness between terms. The approach utilized the folksonomy data from social tagging, so it had advantages like evolution with social cognition. We built a semantic relatedness measurement service - TagRelated! based on the folksonomy data from Three applications were implemented with TagRelated! to demonstrate its usage and performance. Experiment and user feedback showed the method and service performing well. © 2012 AICIT.

    Wu C, Guo Y, 2012,

    A new paradigm for web app development, deployment, distribution, and collaboration

    , Pages: 433-438

    Web application is getting great prosperous while web browser is becoming one of the most important platforms not only on PCs, but also on mobile devices. And web application producing and consuming are going through a process of transformation sharped by the trends including Cloud computing, social networking, online application store, etc. It's necessary to look at the whole web application paradigm and get vision for its future. In this paper, we gave our insight on the web application paradigm, discussing its aspects of development, deployment, distribution, economic model, cloud platform, social diffusion and so on, and represent both the architecture and implementation based on our understanding.

    Yan S, Wu C, Dai W, Ghanem M, Guo Yet al., 2012,

    Environmental monitoring via compressive sensing

    , Pages: 61-68

    Environmental monitoring aims to describe the state of the environment. It identifies environmental issues to show us how well our environmental objectives are being met. Traditional large-scale sensor networks for environmental monitoring suffers from the problems of high level of resources consumption and complex information management. In this report, we propose a novel environmental monitoring technique, called compressive sensing based monitoring, which employs only a small number of sensors to monitor target environmental signals over a region of interest. The compressive sensing technique is applied to implement our signal construction framework such that a high resolution environmental signal can be accurately reconstructed with undersampling measurements. Copyright 2012 ACM.

    Yang X, Guo Y, Bradley J, 2012,

    An iterative parameter estimation method for biological systems

    , Pages: 65-74

    One difficulty in building a mechanistic model of biological systems lies in determining the correct parameter values. This paper proposes a novel parameter estimation method to infer unknown parameters, such as kinetic rates, from noisy experimental observations. Derived from the Approximate Bayesian Computation (ABC) algorithm, our method can predict the distribution of each parameter rather than a single value. The Sequential Monte Carlo (SMC) method is used in this paper to approximate the real distribution of each parameter via several intermediate distributions. In order to improve the performance of the ABC SMC method, this paper develops a windowing method to reduce the parameter search space that needs to be explored. Moreover, an adaptive sampling weight which is inversely proportional to the distance value is proposed in this paper to further increase the efficiency of ABC SMC parameter estimation. © 2012 ACM.

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