@Phdthesis{CitationKey,
author = {Caton, Simon},
title = {{On-Demand Distributed Image Processing Over An Adaptive Campus-Grid}},
school = {School of Computer Science, Cardiff University},
year = {2009},
abstract = {This thesis explores how scientific applications, which are based
upon short jobs (seconds and minutes) can capitalize upon the idle workstations
of a Campus-Grid. These resources are donated on a voluntary basis, and
consequently, the Campus-Grid is constantly adapting and the availability of
workstations changes. Typically, to utilize these resources a Condor system
or equivalent would be used. However, such systems are designed with different
trade-offs and incentives in mind and therefore do not provide intrinsic support
for short jobs. The motivation for creating a provisioning scenario for short
jobs is that Image Processing, as well as other areas of scientific analysis,
are

typically composed of short running jobs, but still require parallel solutions.



Much of the literature in this area comments on the challenges of performing
such analysis efficiently and effectively; even when dedicated resources are
in use. The main challenges are: latency and scheduling penalties, granularity
and the potential for very short jobs. A volunteer Grid retains these challenges
but also adds further challenges. These can be summarized as: unpredictable
resource availability and longevity, multiple machine owners and administrators
who directly affect the operating environment. Ultimately, this creates the
requirement for well conceived and effective fault management strategies. However,
these are tyically not in place to enable transparent fault-free job
administration for the user.



This research demonstrates that these challenges are answerable, and that in
doing so opportunistically sourced Campus-Grid resources can host disparate
applications constituted of short running jobs, of as little as one second in
length. This is demonstrated by the significant improvements in performance
when the system presented here was compared to a well established Condor system.
Here, improvements are increased job efficiency from 60–70% to 95%–100%, up
to a 99% reduction in application makespan and up to a 13000% increase in the
efficiency of resource utilization. The Condor pool in use is approximately
1,600 workstations distributed across 27 administrative domains of Cardiff
University. The application domain of this research is Matlab-based image
processing, and the application area used to demonstrate the approach is the
analysis of Magnetic Resonance Imagery (MRI). However, the presented approach
is generalizable to any application domain with similar characteristics.}}

					

@Article{CitationKey,
author = {Chard, Kyle and Bubendorfer, Kris and Caton, Simon and Rana, Omer},
title = {{Social Cloud Computing: A Vision for Socially Motivated Resource
Sharing}},
journal = {IEEE Transactions on Services Computing},
year = {2011},
volume = {99},
number = {PrePrints},
doi = {http://doi.ieeecomputersociety.org/10.1109/TSC.2011.39},
url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5928319}}

					

@Article{CitationKey,
author = {Caton, Simon and Rana, Omer},
title = {{Towards Autonomic Management for Cloud Services based upon Volunteered
Resources}},
journal = {Concurrency and Computation: Practice and Experience},
year = {2011},
volume = {23},
note = {Special Issue on Autonomic Cloud Computing: Technologies, Services,
and Applications}}

					

@Article{CitationKey,
author = {Rana, Omer and Caton, Simon},
title = {{Business Models for On-line Social Networks: Challenges and
Opportunities}},
journal = {International Journal of Virtual Communities and Social Networking
(IJVCSN)},
year = {2010},
volume = {2},
pages = {31 - 41},
number = {3},
url = {http://www.igi-global.com/Bookstore/Article.aspx?TitleId=49702}}

					

@Article{CitationKey,
author = {Caton, Simon and Rana, Simon and Batchelor, Bruce},
title = {{Distributed Image Processing Over an Adaptive Campus-Grid}},
journal = {Concurrency and Computation: Practice and Experience},
year = {2009},
volume = {21},
pages = {321 -- 336},
number = {3},
note = {Special Issue: The Best of CCGrid'2007: A Snapshot of an ‘Adolescent’
Area},
url = {http://www3.interscience.wiley.com/cgi-bin/fulltext/121357116/PDFSTART},
abstract = {A system implemented in MATLAB is described, which may be deployed
over a Campus Grid utilizing the Condor job management system. Our approach
can re-distribute jobs as node availability changes. The architecture of the
system, its components, and their deployment across the Cardiff University Campus
Grid (consisting of 2500 machines) are presented. Challenges in image processing
applications that can be deployed over such infrastructure are presented, along
with performance results that demonstrate the use of our system alongside a
standard Condor deployment, demonstrating a significant increase in throughput
using our approach.}}

					

@Inproceedings{CitationKey,
author = {Breskovic, Ivan and Haas, Christian and Caton, Simon and Brandic,
Ivona},
title = {{Towards Self-Awareness in Cloud Markets: A Monitoring Methodology}},
booktitle = {Proceedings of the 9th IEEE International Conference on Dependable,
Autonomic and Secure Computing (DASC2011)},
year = {2011},
abstract = {Currently, the Cloud landscape is a fragmented, static and shapeless
market that hinders the paradigm's ability to fulfil its promise of ubiquitious
computing on tap and as a commodity. In this paper, we present our vision of
an autonomic self-aware Cloud market platform, and argue that autonomic market
platforms for Clouds can step up to the challenge of today's status quo. As
our first steps towards achieving this vision, we present a market monitoring
methodology, which includes a series of realistic market goals, sets of
extractable metrics from a market platform and how to map (i.e.

combine and transform) metrics to access goal performance such that autonomic
adaption of the market could be undertaken. We have extended a known market
simulator for distributed infrastructures (GridSim) with relevant sensors. To
demonstrate the usefulness of our approach, we simulate a sudden cease in demand
for goods in our market platform.}}

					

@Inproceedings{CitationKey,
author = {Martin, Jochen and Caton, Simon and Conte, Tobias and Weinhardt,
Christof},
title = {{Financial Planning as a Service}},
booktitle = {Proceedings of the 8th International Conference on Service Computing
(SCC)},
year = {2011},
address = {Washington DC, USA}}

					

@Inproceedings{CitationKey,
author = {Haas, Christian and Caton, Simon and Weinhardt, Christof},
title = {{Engineering Incentives in Social Clouds}},
booktitle = {Proceedings of the 11th IEEE/ACM International Symposium on Cluster,
Cloud and Grid Computing (CCGrid 2011)},
year = {2011},
pages = {572-575},
url = {http://dx.doi.org/10.1109/CCGrid.2011.52}}

					

@Inproceedings{CitationKey,
author = {Michalk, Wibke and Caton, Simon},
title = {{Service Level Management in Dynamic Value Networks}},
booktitle = {INFORMATIK 2010: Service Science - Neue Perspektiven fuer die
Informatik Band 1},
year = {2010},
address = {Leipzig},
pages = {126-131},
volume = {P-175},
publisher = {Gesellschaft fuer Informatik},
note = {ISBN: 978-3-88579-269-7},
abstract = {This paper presents a framework for Service Level Management in
dynamic, heterogeneous environments for service composition. Assumptions to
and the architecture of a framework is introduced that enables risk-aware
decisions in dynamic service composition environments. The implementation in
the project ValueGrids is described.}}

					

@Inproceedings{CitationKey,
author = {Chard, Kyle and Caton, Simon  and Rana, Omer and Bubendorfer, Kris},
title = {{Social Cloud: Cloud Computing in Social Networks}},
booktitle = {Proceedings of the 3rd International Conference on Cloud Computing
IEEE Cloud 2010},
year = {2010},
abstract = {With the increasingly ubiquitous nature of Social

networks and Cloud computing, users are starting to explore new ways to interact
with, and exploit these developing paradigms. Social networks are used to reflect
real world relationships that allow users to share information and form
connections between one another, essentially creating dynamic Virtual
Organizations. We propose leveraging the pre-established trust formed through
friend relationships within a Social network to form a dynamic “Social Cloud”,
enabling friends to share resources within the context of a Social network.
We believe that combining trust relationships with suitable incentive mechanisms
(through financial payments or bartering) could provide much more sustainable
resource sharing mechanisms. This paper outlines our vision of, and experiences
with, creating a Social Storage Cloud, looking specifically at possible market
mechanisms that could be used to create a dynamic Cloud infrastructure in a
Social network environment.}}

					

@Inproceedings{CitationKey,
author = {Borissov, N. and Caton, S. and Rana, O. and Levine, A.},
title = {{Message Protocols for Provisioning and Usage of Computing Services}},
booktitle = {6th International Workshop on Grid Economics and Business Models},
year = {2009},
pages = {160-170},
doi = {10.1007/978-3-642-03864-8_13},
url = {http://www.springerlink.com/content/r28q28757h1j770r}}

					

@Inproceedings{CitationKey,
author = {Caton, Simon and Caan, Matthan and Olabarriaga, Silvia and Rana, Omer
and Batchelor, Bruce },
title = {{Using Dynamic Condor-based Services for Classifying Schizophrenia
in Diffusion Tensor Images}},
booktitle = {CCGRID `08: Proceedings of the Eigth IEEE International Symposium
on Cluster Computing and the Grid},
year = {2008},
pages = {234 - 241},
url =
{http://ieeexplore.ieee.org/iel5/4534181/4534182/04534224.pdf?tp=&arnumber=4534224&isnumber=4534182},
abstract = {Diffusion tensor imaging (DTI) provides insight into the white matter
of the human brain, which is affected by schizophrenia. By comparing a patient
group to a control group, the DTI-images are on average expected to be different
for white matter regions. Principal component analysis (PCA) and linear
discriminant analysis (LDA) are used to classify the groups. In this work, the
number of principal components is optimised for obtaining the minimal
classification error. A robust estimate of this error is computed in a
cross-validation framework, using different compositions of the data into a
training and a testing set Previously, sequential runs were performed in MATLAB,
resulting in long execution times. In this paper we describe an experiment where
this application was run on a grid with minimal modifications and user effort.
We have adopted a service-based approach that autonomously launches image analysis
services onto a campus-wide Condor pool comprising of volunteer resources. This
allows high throughput analysis of our data in a dynamic resource pool. The
challenge in adopting such an approach comes from the nature of the resources,
which change randomly with time and thus require fault tolerance. Through this
approach we have reduced the computation time of each dataset from 90 minutes
to less than 10. A minimal classification error of 22% was obtained, using 15
principal components. }}

					

@Inproceedings{CitationKey,
author = {Caton, Simon and Rana, Omer and Batchelor, Bruce},
title = {{Dynamic Condor-based Services for Distributed Image Analysis}},
booktitle = {CCGRID `07: Proceedings of the Seventh IEEE International Symposium
	on Cluster Computing and the Grid},
year = {2007},
pages = {49 - 56},
note = {Best Paper Finalist},
url =
{http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4215365&isnumber=4215349},
abstract = {Interactive image processing is an important requirement in many
industrial applications, such as the inspection of industrial parts within a
manufacturing environment, or the processing of images from surveillance cameras.
Being able to achieve this quickly and accurately is often essential for the
success of such industrial applications. A service-based approach that
autonomously launches Image Analysis Services (accessible through a Central
Service Manager) onto spare network resources through a Condor system is
presented. This allows high throughput analysis of these images in a dynamic
resource pool. The Central Service Manager reacts to new tasks submitted to
the Image Analysis Services and is able to add new service instances to manage
these tasks dynamically. Each service instance here corresponds to a computational
resource that is able to execute image processing algorithms. New service
instances may be requested by the Central Service Manager from the Condor system,
based on the number of tasks that need to be processed. This enables entire
image repositories to be acted upon interactively and in parallel, as opposed
to the analysis of single images individually. The approach is demonstrated
through a campus-wide test bed utilising a Condor system with 90 machines.}}

					

@Inproceedings{CitationKey,
author = {Batchelor, B. and Caton, S. and Chatburn, L. and Crowther, R. and
Miller, J.},
title = {{Networked vision system using a Prolog controller}},
booktitle = {Proc. SPIE Vol. 5999 Intelligent Systems in Design and Manufacturing
	VI},
year = {2005},
editor = {Bhaskaran Gopalakrishnan},
pages = {151 - 162},
url =
{http://spiedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=PSISDG00599900000159990G000001&idtype=cvips&gifs=yes}}

					

@Inproceedings{CitationKey,
author = {Batchelor, B. and Caton, S. and Chatburn, L and Crowther, R. and Miller,
J.},
title = {{Vision Systems on the Internet}},
booktitle = {Proc. SPIE Vol. 6000 Two- and Three-Dimensional Methods for
Inspectionand 	Metrology III},
year = {2005},
editor = {Kevin G. Harding},
pages = {25 - 39},
url =
{http://spiedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=PSISDG006000000001600003000001&idtype=cvips&gifs=yes},
abstract = {Hitherto, it has been assumed that an industrial Machine Vision
systems is constructed as an integrated unit, with the camera, image processing
unit and control/display console being located close to one another and to the
object/scene being inspected. For several reasons, it may be helpful to separate
them, so that only the camera and its associated lighting units are located
on the factory floor, while other equipment, such as computers and user terminals,
islocated elsewhere, out of harm's way. We describe three systems that allow
multiple cameras and several separate image processing engines, to be controlled
remotely from a single "intelligent" device, or a user working via a standard
web browser. The paper describes and compares several different approaches to
building such a system. Links to the networked vision systems mentioned here
are provided in an accompanying web site. }}

					

@Inproceedings{CitationKey,
author = {Suau, Pablo and Pujol, Mar and Rizo, Ramon and Caton, Simon and Rana,
Omer and Batchelor, Bruce and Pujol, Francisco },
title = {{Agent-based recognition of facial expressions}},
booktitle = {Proceedings of the Fourth International Joint Conference on
Autonomous 	Agents and Multiagent Systems - AAMAS `05},
year = {2005},
pages = {161 - 162},
url =
{http://portal.acm.org/ft_gateway.cfm?id=1082831&type=pdf&coll=GUIDE&dl=GUIDE&CFID=59741016&CFTOKEN=45261109},
abstract = {Description of a system to detect facial expressions using an
agent-based approach is presented. The system utilizes interaction between
Matlab-based image filters and a JADE-based agent implementation. The system
is demonstrated using a feature recognition example. The system however has
a much wider applicability, especially as Matlab is used extensively in other
scientific/numerical computing applications.}}

					

@Misc{CitationKey,
author = {Caton, Simon},
title = {{Social Networks as a Mechanism for Collaborative Computing in: Ferscha,
A. (ed.), Pervasive Adaption Research Agenda for Future and Emerging
Technologies.}},
year = {2011},
url = {http://www.perada.eu/research-agenda#item:76}}