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					                    Market-Oriented Cloud Computing:
  Vision, Hype, and Reality for Delivering IT Services as Computing Utilities

                          Rajkumar Buyya1,2, Chee Shin Yeo1, and Srikumar Venugopal1

                          1
                              Grid Computing and Distributed Systems (GRIDS) Laboratory
                               Department of Computer Science and Software Engineering
                                       The University of Melbourne, Australia
                                  Email: {raj, csyeo, srikumar}@csse.unimelb.edu.au
                                      2
                                          Manjrasoft Pty Ltd, Melbourne, Australia


                      Abstract                                  sophisticated, we will probably see the spread of
    This keynote paper: presents a 21st century vision          ‘computer utilities’ which, like present electric and
of computing; identifies various computing paradigms            telephone utilities, will service individual homes and
promising to deliver the vision of computing utilities;         offices across the country.” This vision of the
defines Cloud computing and provides the architecture           computing utility based on the service provisioning
for creating market-oriented Clouds by leveraging               model anticipates the massive transformation of the
technologies such as VMs; provides thoughts on                  entire computing industry in the 21st century whereby
market-based resource management strategies that                computing services will be readily available on
encompass both customer-driven service management               demand, like other utility services available in today’s
and computational risk management to sustain SLA-               society.    Similarly,    computing      service   users
oriented    resource    allocation;    presents   some          (consumers) need to pay providers only when they
representative Cloud platforms especially those                 access computing services. In addition, consumers no
developed in industries along with our current work             longer need to invest heavily or encounter difficulties
towards realising market-oriented resource allocation           in building and maintaining complex IT infrastructure.
of Clouds by leveraging the 3rd generation Aneka                   Software practitioners are facing numerous new
enterprise Grid technology; reveals our early thoughts          challenges toward creating software for millions of
on interconnecting Clouds for dynamically creating an           consumers to use as a service rather than to run on their
atmospheric computing environment along with                    individual computers. Over the years, new computing
pointers to future community research; and concludes            paradigms have been proposed and adopted, with the
with the need for convergence of competing IT                   emergence of technological advances such as multi-
paradigms for delivering our 21st century vision.               core     processors     and     networked       computing
                                                                environments, to edge closer toward achieving this
1. Introduction                                                 grand vision. As shown in Figure 1, these new
With the advancement of the modern human society,               computing paradigms include cluster computing, Grid
basic essential services are commonly provided such             computing, P2P computing, service computing,
that everyone can easily obtain access to them. Today,          market-oriented computing, and most recently Cloud
utility services, such as water, electricity, gas, and          computing. All these paradigms promise to provide
telephony are deemed necessary for fulfilling daily life        certain attributes or capabilities in order to realize the
routines. These utility services are accessed so                possibly 1 trillion dollars worth of the utility/pervasive
frequently that they need to be available whenever the          computing industry as quoted by Sun Microsystems
consumer requires them at any time. Consumers are               co-founder Bill Joy [2]. Computing services need to be
then able to pay service providers based on their usage         highly reliable, scalable, and autonomic to support
of these utility services.                                      ubiquitous      access,    dynamic      discovery     and
                                                                composability. In particular, consumers can determine
    In 1969, Leonard Kleinrock [1], one of the chief            the required service level through Quality of Service
scientists of the original Advanced Research Projects           (QoS) parameters and Service Level Agreements
Agency Network (ARPANET) project which seeded                   (SLAs). Of all these computing paradigms, the two
the Internet, said: “As of now, computer networks are           most promising ones appear to be Grid computing and
still in their infancy, but as they grow up and become          Cloud computing.
                                     } ?
                Web
                Data Centres
                Utility Computing
                Service Computing
                Grid Computing                                       +
                P2P Computing
                Cloud Computing
                Market-Oriented
                                                            •Ubiquitous
                Computing                                    access
                                                                                  -Trillion $ business
                …                                           •Reliability           - Who will own it?
                                                            •Scalability
               Paradigms                                    •Autonomic
                                                            •Dynamic
                                                             discovery
                                                            •Composability
                                                            •QoS
                                                            •SLA
                                                            •…
                                                     Attributes/Capabilities

                          Figure 1: Various paradigms promising to deliver IT as services.

   A Grid [3] enables the sharing, selection, and           Cloud infrastructure is very robust and will always be
aggregation of a wide variety of geographically             available at any time.
distributed resources including supercomputers,
storage systems, data sources, and specialized devices      1.1 Definition and Trends
owned by different organizations for solving large-
                                                            A number of computing researchers and practitioners
scale resource-intensive problems in science,
                                                            have attempted to define Clouds in various ways [6].
engineering, and commerce. Inspired by the electrical
                                                            Based on our observation of the essence of what
power Grid’s pervasiveness, ease of use, and reliability
                                                            Clouds are promising to be, we propose the following
[4], the motivation of Grid computing was initially
                                                            definition:
driven by large-scale, resource (computational and
data)-intensive scientific applications that required            •       "A Cloud is a type of parallel and distributed
more resources than a single computer (PC,                               system consisting of a collection of inter-
workstation, supercomputer, or cluster) could have                       connected and virtualised computers that are
provided in a single administrative domain. Due to its                   dynamically provisioned and presented as one
potential to make impact on the 21st century as much                     or more unified computing resources based on
as the electric power Grid did on the 20th century, Grid                 service-level agreements established through
computing has been hailed as the next revolution after                   negotiation between the service provider and
the Internet and the Web.                                                consumers.”
    Today, the latest paradigm to emerge is that of            At a cursory glance, Clouds appear to be a
Cloud computing [5] which promises reliable services        combination of clusters and Grids. However, this is not
delivered through next-generation data centers that are     the case. Clouds are clearly next-generation data
built on compute and storage virtualization                 centers with nodes “virtualized” through hypervisor
technologies. Consumers will be able to access              technologies such as VMs, dynamically “provisioned”
applications and data from a “Cloud” anywhere in the        on demand as a personalized resource collection to
world on demand. In other words, the Cloud appears to       meet a specific service-level agreement, which is
be a single point of access for all the computing needs     established through a “negotiation” and accessible as a
of consumers. The consumers are assured that the            composable service via “Web 2.0” technologies.
       grid


            cloud



                                            cluster
                                                                 cloud


                         Legend: Cluster computing, Grid computing, Cloud computing

                               Figure 2: Google search trends for the last 12 months.

1.2 Web Search Trends                                       2. Market-Oriented Cloud Architecture
The popularity of different paradigms varies with time.
                                                            As consumers rely on Cloud providers to supply all
The Web search popularity, as measured by the Google
                                                            their computing needs, they will require specific QoS
search trends during the last 12 months, for terms
                                                            to be maintained by their providers in order to meet
“cluster computing”, “Grid computing”, and “Cloud
                                                            their objectives and sustain their operations. Cloud
computing” is shown in Figure 2. From the Google
                                                            providers will need to consider and meet different QoS
trends, it can be observed that cluster computing was a
                                                            parameters of each individual consumer as negotiated
popular term during 1990s, from early 2000 Grid
                                                            in specific SLAs. To achieve this, Cloud providers can
computing become popular, and recently Cloud
                                                            no longer continue to deploy traditional system-centric
computing started gaining popularity.
                                                            resource management architecture that do not provide
    Spot points in Figure 2 indicate the release of news    incentives for them to share their resources and still
related to Cloud computing as follows:                      regard all service requests to be of equal importance.
    IBM Introduces 'Blue Cloud' Computing, CIO              Instead, market-oriented resource management [7] is
   Today - Nov 15 2007                                      necessary to regulate the supply and demand of Cloud
   IBM, EU Launch RESERVOIR Research Initiative             resources at market equilibrium, provide feedback in
   for Cloud Computing, IT News Online - Feb 7              terms of economic incentives for both Cloud
   2008                                                     consumers and providers, and promote QoS-based
                                                            resource allocation mechanisms that differentiate
   Google and Salesforce.com in Cloud computing             service requests based on their utility.
   deal, Siliconrepublic.com - Apr 14 2008
                                                                Figure 3 shows the high-level architecture for
    Demystifying Cloud        Computing,     Intelligent    supporting market-oriented resource allocation in Data
   Enterprise - Jun 11 2008                                 Centers and Clouds. There are basically four main
   Yahoo realigns to support Cloud computing, 'core         entities involved:
   strategies', San Antonio Business Journal - Jun 27            • Users/Brokers: Users or brokers acting on
   2008                                                               their behalf submit service requests from
   Merrill Lynch Estimates "Cloud Computing" To                       anywhere in the world to the Data Center and
   Be $100 Billion Market, SYS-CON Media - Jul 8                      Cloud to be processed.
   2008
                                                                 •   SLA Resource Allocator: The SLA Resource
                                                                     Allocator acts as the interface between the
                                                                     Data Center/Cloud service provider and
                    Figure 3: High-level market-oriented cloud architecture.

external users/brokers. It requires the                             effectively. Then, it assigns requests
interaction of the following mechanisms to                          to VMs and determines resource
support SLA-oriented resource management:                           entitlements for allocated VMs.
    o   Service Request Examiner and                            o   Pricing: The Pricing mechanism
        Admission Control: When a service                           decides how service requests are
        request is first submitted, the Service                     charged. For instance, requests can
        Request Examiner and Admission                              be charged based on submission time
        Control mechanism interprets the                            (peak/off-peak),      pricing   rates
        submitted       request    for     QoS                      (fixed/changing) or availability of
        requirements before determining                             resources (supply/demand). Pricing
        whether to accept or reject the                             serves as a basis for managing the
        request. Thus, it ensures that there is                     supply and demand of computing
        no overloading of resources whereby                         resources within the Data Center and
        many service requests cannot be                             facilitates in prioritizing resource
        fulfilled successfully due to limited                       allocations effectively.
        resources available. It also needs the
                                                                o   Accounting:      The      Accounting
        latest status information regarding
                                                                    mechanism maintains the actual
        resource availability (from VM
                                                                    usage of resources by requests so
        Monitor mechanism) and workload                             that the final cost can be computed
        processing (from Service Request
                                                                    and charged to the users. In addition,
        Monitor mechanism) in order to
                                                                    the maintained historical usage
        make resource allocation decisions
                                                                    information can be utilized by the
                   Service Request Examiner and                    •   support customer-driven service management
                   Admission Control mechanism to                      based on customer profiles and requested
                   improve    resource   allocation                    service requirements,
                   decisions.
                                                                   •   define computational risk management tactics
              o    VM Monitor: The VM Monitor                          to identify, assess, and manage risks involved
                   mechanism keeps track of the                        in the execution of applications with regards
                   availability of VMs and their                       to service requirements and customer needs,
                   resource entitlements.
                                                                   •   derive appropriate market-based resource
              o    Dispatcher:      The   Dispatcher                   management strategies that encompass both
                   mechanism starts the execution of                   customer-driven service management and
                   accepted    service requests on                     computational risk management to sustain
                   allocated VMs.                                      SLA-oriented resource allocation,
              o    Service Request Monitor: The                    •   incorporate autonomic resource management
                   Service Request Monitor mechanism                   models that effectively self-manage changes
                   keeps track of the execution progress               in service requirements to satisfy both new
                   of service requests.                                service demands and existing service
    •    VMs: Multiple VMs can be started and                          obligations, and
         stopped dynamically on a single physical                  •   leverage VM technology to dynamically
         machine to meet accepted service requests,                    assign resource shares according to service
         hence providing maximum flexibility to                        requirements.
         configure various partitions of resources on
         the same physical machine to different
         specific requirements of service requests. In         3. Emerging Cloud Platforms
         addition, multiple VMs can concurrently run           Industry analysts have made bullish projections on how
         applications based on different operating             Cloud computing will transform the entire computing
         system environments on a single physical              industry. According to a recent Merrill Lynch research
         machine since every VM is completely                  note [9], Cloud computing is expected to be a “$160-
         isolated from one another on the same                 billion addressable market opportunity, including $95-
         physical machine.                                     billion in business and productivity applications, and
                                                               another $65-billion in online advertising”. Another
    •     Physical Machines: The Data Center
                                                               research study by Morgan Stanley [10] has also
          comprises multiple computing servers that
                                                               identified Cloud computing as one of the prominent
          provide resources to meet service demands.
                                                               technology trends. As the computing industry shifts
    In the case of a Cloud as a commercial offering to         toward providing Platform as a Service (PaaS) and
enable crucial business operations of companies, there         Software as a Service (SaaS) for consumers and
are critical QoS parameters to consider in a service           enterprises to access on demand regardless of time and
request, such as time, cost, reliability and trust/security.   location, there will be an increase in the number of
In particular, QoS requirements cannot be static and           Cloud platforms available. Recently, several academic
need to be dynamically updated over time due to                and industrial organisations have started investigating
continuing changes in business operations and                  and developing technologies and infrastructure for
operating environments. In short, there should be              Cloud Computing. Academic efforts include Virtual
greater importance on customers since they pay for             Workspaces [11] and OpenNebula [12]. In this section,
accessing services in Clouds. In addition, the state-of-       we compare six representative Cloud platforms with
the-art in Cloud computing has no or limited support           industrial linkages in Table 1.
for dynamic negotiation of SLAs between participants
and mechanisms for automatic allocation of resources              Amazon Elastic Compute Cloud (EC2) [13]
to multiple competing requests. Recently, we have              provides a virtual computing environment that enables
developed negotiation mechanisms based on alternate            a user to run Linux-based applications. The user can
offers protocol for establishing SLAs [8]. These have          either create a new Amazon Machine Image (AMI)
high potential for their adoption in Cloud computing           containing the applications, libraries, data and
systems built using VMs.                                       associated configuration settings, or select from a
                                                               library of globally available AMIs. The user then needs
   Commercial offerings of market-oriented Clouds
                                                               to upload the created or selected AMIs to Amazon
must be able to:
                              Table 1: Comparison of some representative Cloud platforms.
               System
                            Amazon                                                 Sun
                                                Google         Microsoft                          GRIDS Lab
                        Elastic Compute                                        Network.com
                                              App Engine       Live Mesh                            Aneka
                          Cloud (EC2)                                           (Sun Grid)
       Property
                                                                                                Software
                                                                                                Platform for
       Focus            Infrastructure      Platform         Infrastructure    Infrastructure
                                                                                                enterprise
                                                                                                Clouds
                        Compute, Storage    Web
       Service Type                                          Storage           Compute          Compute
                        (Amazon S3)         application
                                                                               Job
                        OS Level running                                                        Resource
                                            Application                        management
       Virtualisation   on a Xen                             OS level                           Manager and
                                            container                          system (Sun
                        hypervisor                                                              Scheduler
                                                                               Grid Engine)
       Dynamic                                                                                  SLA-based
       Negotiation of                                                                           Resource
                        None                None             None              None
       QoS                                                                                      Reservation on
       Parameters                                                                               Aneka side.
                                                             Web-based
                                                                               Job submission
                        Amazon EC2          Web-based        Live Desktop                       Workbench,
       User Access                                                             scripts, Sun
                        Command-line        Administration   and any devices                    Web-based
       Interface                                                               Grid Web
                        Tools               Console          with Live Mesh                     portal
                                                                               portal
                                                             installed
       Web APIs         Yes                 Yes              Unknown           Yes              Yes

       Value-added
       Service          Yes                 No               No                Yes              No
       Providers
                                                                                                APIs supporting
                                                                                                different
                        Customizable
                                                                               Solaris OS,      programming
       Programming      Linux-based
                                            Python           Not applicable    Java, C, C++,    models in C#
       Framework        Amazon Machine
                                                                               FORTRAN          and other .Net
                        Image (AMI)
                                                                                                supported
                                                                                                languages
Simple Storage Service (S3), before he can start, stop,       data that can be accessed across required devices (such
and monitor instances of the uploaded AMIs. Amazon            as computers and mobile phones) from anywhere in the
EC2 charges the user for the time when the instance is        world. The user is able to access the uploaded
alive, while Amazon S3 charges for any data transfer          applications and data through a Web-based Live
(both upload and download).                                   Dekstop or his own devices with Live Mesh software
   Google App Engine [14] allows a user to run Web            installed. Each user’s Live Mesh is password-protected
applications written using the Python programming             and authenticated via his Windows Live Login, while
language. Other than supporting the Python standard           all file transfers are protected using Secure Socket
library, Google App Engine also supports Application          Layers (SSL).
Programming Interfaces (APIs) for the datastore,                 Sun network.com (Sun Grid) [16] enables the user
Google Accounts, URL fetch, image manipulation, and           to run Solaris OS, Java, C, C++, and FORTRAN based
email services. Google App Engine also provides a             applications. First, the user has to build and debug his
Web-based Administration Console for the user to              applications and runtime scripts in a local development
easily manage his running Web applications.                   environment that is configured to be similar to that on
Currently, Google App Engine is free to use with up to        the Sun Grid. Then, he needs to create a bundled zip
500MB of storage and about 5 million page views per           archive (containing all the related scripts, libraries,
month.                                                        executable binaries and input data) and upload it to Sun
   Microsoft Live Mesh [15] aims to provide a                 Grid. Finally, he can execute and monitor the
centralized location for a user to store applications and     application using the Sun Grid Web portal or API.
After the completion of the application, the user will        provider and sub-leasing these to the consumers. A
need to download the execution results to his local           broker can accept requests from many users who have
development environment for viewing.                          a choice of submitting their requirements to different
   GRIDS Lab Aneka [17], which is being                       brokers. Consumers, brokers and providers are bound
commercialized through Manjrasoft, is a .NET-based            to their requirements and related compensations
service-oriented platform for constructing enterprise         through SLAs. An SLA specifies the details of the
Grids. It is designed to support multiple application         service to be provided in terms of metrics agreed upon
models, persistence and security solutions, and               by all parties, and penalties for meeting and violating
communication protocols such that the preferred               the expectations, respectively.
selection can be changed at anytime without affecting            Such markets can bridge disparate Clouds allowing
an existing Aneka ecosystem. To create an enterprise          consumers to choose a provider that suits their
Grid, the service provider only needs to start an             requirements by either executing SLAs in advance or
instance of the configurable Aneka container hosting          by buying capacity on the spot. Providers can use the
required services on each selected desktop computer.          markets in order to perform effective capacity
The purpose of the Aneka container is to initialize           planning. A provider is equipped with a price-setting
services and acts as a single point for interaction with      mechanism which sets the current price for the
the rest of the enterprise Grid. Aneka provides SLA           resource based on market conditions, user demand, and
support such that the user can specify QoS                    current level of utilization of the resource. Pricing can
requirements such as deadline (maximum time period            be either fixed or variable depending on the market
which the application needs to be completed in) and           conditions. An admission-control mechanism at a
budget (maximum cost that the user is willing to pay          provider’s end selects the auctions to participate in or
for meeting the deadline). The user can access the            the brokers to negotiate with, based on an initial
Aneka Enterprise Grid remotely through the Gridbus            estimate of the utility. The negotiation process
broker. The Gridbus broker also enables the user to           proceeds until an SLA is formed or the participants
negotiate and agree upon the QoS requirements to be           decide to break off. These mechanisms interface with
provided by the service provider.                             the resource management systems of the provider in
                                                              order to guarantee the allocation being offered or
4. Global Cloud Exchange and Markets                          negotiated can be reclaimed, so that SLA violations do
                                                              not occur. The resource management system also
Enterprises currently employ Cloud services in order to       provides functionalities such as advance reservations
improve the scalability of their services and to deal         that enable guaranteed provisioning of resource
with bursts in resource demands. However, at present,         capacity.
service providers have inflexible pricing, generally
limited to flat rates or tariffs based on usage thresholds,      Brokers gain their utility through the difference
and consumers are restricted to offerings from a single       between the price paid by the consumers for gaining
provider at a time. Also, many providers have                 resource shares and that paid to the providers for
proprietary interfaces to their services thus restricting     leasing their resources. Therefore, a broker has to
the ability of consumers to swap one provider for             choose those users whose applications can provide it
another.                                                      maximum utility. A broker interacts with resource
                                                              providers and other brokers to gain or to trade resource
   For Cloud computing to mature, it is required that         shares. A broker is equipped with a negotiation module
the services follow standard interfaces. This would           that is informed by the current conditions of the
enable services to be commoditised and thus, would            resources and the current demand to make its
pave the way for the creation of a market infrastructure      decisions.
for trading in services. An example of such a market
system, modeled on real-world exchanges, is shown in             Consumers have their own utility functions that
Figure 4. The market directory allows participants to         cover factors such as deadlines, fidelity of results, and
locate providers or consumers with the right offers.          turnaround time of applications. They are also
Auctioneers periodically clear bids and asks received         constrained by the amount of resources that they can
from market participants. The banking system ensures          request at any time, usually by a limited budget.
that financial transactions pertaining to agreements          Consumers also have their own limited IT
between participants are carried out.                         infrastructure that is generally not completely exposed
                                                              to the Internet. Therefore, a consumer participates in
   Brokers perform the same function in such a market         the utility market through a resource management
as they do in real-world markets: they mediate between        proxy that selects a set of brokers based on their
consumers and providers by buying capacity from the
                                                                                                   Compute Cloud


                                                                                                          Storage Cloud
                                              Broker 1

                                        Request    Negotiate/Bid             Publish Offers
                                        Capacity

                                                              Directory
                                               .
                                               .                           Bank
                                               .              Auctioneer
                           Enterprise          .
                           Resource
                           Manager
                            (Proxy)       Broker N
                                                            Global Cloud                                       Compute
                                                                                                               Cloud
                                                               Market
         Enterprise IT Consumer

                                                                                              Storage Cloud

                  Figure 4: Global Cloud exchange and market infrastructure for trading services.
offerings. He then forms SLAs with the brokers that                obtain restitution in case an SLA is violated. This
bind the latter to provide the guaranteed resources. The           motivates the need for a legal framework for
enterprise consumer then deploys his own environment               agreements in such markets, a research issue that is out
on the leased resources or uses the provider’s                     of scope of themes pursued in this paper.
interfaces in order to scale his applications.
   The idea of utility markets for computing resources             5. Summary and Conclusion
has been around for a long time. Recently, many
research projects such as SHARP [18], Tycoon [19],                 Cloud computing is a new and promising paradigm
Bellagio [20], and Shirako [21] have come up with                  delivering IT services as computing utilities. As
market structures for trading in resource allocations.             Clouds are designed to provide services to external
These have particularly focused on trading in VM-                  users, providers need to be compensated for sharing
based resource slices on networked infrastructures such            their resources and capabilities. In this paper, we have
as PlanetLab. As mentioned before, the Gridbus project             proposed architecture for market-oriented allocation of
has created a resource broker that is able to negotiate            resources within Clouds. We have discussed some
with resource providers. Thus, the technology for                  representative platforms for Cloud computing covering
enabling utility markets is already present and ready to           the state-of-the-art. We have also presented a vision for
be deployed.                                                       the creation of global Cloud exchange for trading
                                                                   services.
   However, significant challenges persist in the
universal application of such markets. Enterprises                    The state-of-the-art Cloud technologies have limited
currently employ conservative IT strategies and are                support for market-oriented resource management and
unwilling to shift from the traditional controlled                 they need to be extended to support: negotiation of
environments. Cloud computing uptake has only                      QoS between users and providers to establish SLAs;
recently begun and many systems are in the proof-of-               mechanisms and algorithms for allocation of VM
concept stage. Regulatory pressures also mean that                 resources to meet SLAs; and manage risks associated
enterprises have to be careful about where their data              with the violation of SLAs. Furthermore, interaction
gets processed, and therefore, are not able to employ              protocols needs to be extended to support
Cloud services from an open market. This could be                  interoperability between different Cloud service
mitigated through SLAs that specify strict constraints             providers.
on the location of the resources. However, another                    As Cloud platforms become ubiquitous, we expect
open issue is how the participants in such a market can
the need for internetworking them to create a market-        [10]   Morgan Stanley. Technology Trends. 12 June
oriented global Cloud exchange for trading services.                2008.
Several challenges need to be addressed to realize this             http://www.morganstanley.com/institutional/tec
vision. They include: market-maker for bringing                     hresearch/pdfs/TechTrends062008.pdf [18 July
service providers and consumers; market registry for                2008]
publishing and discovering Cloud service providers           [11]   K. Keahey, I. Foster, T. Freeman, and X.
and their services; clearing house and brokers for                  Zhang. Virtual workspaces: Achieving quality
mapping service requests to providers who can meet                  of service and quality of life in the Grid.
QoS expectations; and payment management and                        Scientific Programming, 13(4):265-275,
accounting infrastructure for trading services. Finally,            October 2005.
we need to address regulatory and legal issues, which
                                                             [12]   I. Llorente, OpenNebula Project.
go beyond technical issues.
                                                                    http://www.opennebula.org/ [23 July 2008]
                                                             [13]   Amazon Elastic Compute Cloud (EC2),
Acknowledgements                                                    http://www.amazon.com/ec2/ [18 July 2008]
This work is partially supported by the Australian
                                                             [14]   Google App Engine,
Department of Innovation, Industry, Science and
                                                                    http://appengine.google.com [18 July 2008]
Research (DIISR) through International Science
Linkage program.                                             [15]   Microsoft Live Mesh, http://www.mesh.com
                                                                    [18 July 2008]
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Description: distributed grid,cloud computing