Toward a Unified Intercloud Interoperability Conceptual Model
for IaaS Cloud Service
Tahereh Nodehi
1
, Sudeep Ghimire
2
and Ricardo Jardim-Gonçalves
3
1
Departamento de Engenharia Electrotecnica, Faculdade de Ciências e Tecnologia da
Universidade Nova de Lisboa (UNL), Campus de Caparica, Caparica, Portugal
2
UNINOVA, Departamento de Engenharia Electrotecnica, Faculdade de Ciencias e Tecnologia, UNL, Lisboa, Portugal
3
CTS, UNINOVA, Departamento de Engenharia Electrotecnica,
Faculdade de Ciências e Tecnologia, UNL, Lisboa, Portugal
Keywords: Cloud Computing, Intercloud Interoperability, Service Level Agreements (SLA), Model Driven
Architecture (MDA).
Abstract: The concept of interoperation between cloud providers is a recent research challenging objective. Current
cloud systems have been developed without concerns of seamless cloud interconnection, and actually they
do not support intercloud interoperability. The paper proposes a conceptual model for Intercloud
Interoperability, to enable schedule dynamic operation for Infrastructure as a Service (IaaS) between
different clouds. The paper is providing a better understanding of elaborates on the cloud computing
architecture, appropriate metrics for Service Level Agreements (SLA) and Quality of Service (QoS) models
that are required for seamless integration and interoperability between cloud environments. Then, a
conceptual model for the Intercloud Interoperability Framework for Workload Migration is proposed. The
novel component of the framework that provides interoperability is the Transformation Engine that maps
workload between heterogeneous cloud providers, whilst Model Driven Architecture (MDA) is adopted as
an applicable method for developing the Transformation Engine module.
1 INTRODUCTION
Cloud computing is a recent computational
paradigm that many large software industries are
adopting. Current cloud systems include several
individual, but heterogeneous clouds with finite
physical resources. With time, it is expected that
expansion of the application scope of cloud services
would require cooperation between clouds from
different providers that have heterogeneous
functionalities (Jardim-Goncalves, Popplewell, et al.
2012)(Coutinho et al. 2013). This seamless
interworking mechanism between clouds is called
“Intercloud”. Interoperability, and can provide better
Quality of Service (QoS), avoidance of vendor lock-
in, whilst enable inter-cloud Resource Sharing and
reduce power consumption and/or labour costs due
to delivering services from various locations and
different sources. However, most of the current
cloud environment does not support intercloud
interoperability and cloud computing needs more
research work to provide sufficient functions to
enable seamless collaboration between cloud
services (Jardim-Goncalves, Agostinho, et al. 2012).
The paper elaborates on the cloud computing
architecture and analysis relevant requirements to
propose a novel Intercloud Interoperability
framework, addressing cooperation between clouds
that entails negotiated and agreed contract between
intercloud service providers, metrics for Service
Level Agreement (SLA) and QoS for Intercloud
systems. A conceptual model is proposed to support
the Intercloud Interoperability Framework for
Workload Migration, tackling the essential technical
requirements of a cloud operational environment.
One of the important components introduced in the
framework to support interoperability is the
Transformation Engine that is able to map the
workload between heterogeneous cloud providers.
Model Driven Architecture (MDA) is the approach
taken for developing the Transformation Engine
module. The proposed framework is in validation
using simulation experiments.
The rest of this paper is organized as follows.
673
Nodehi T., Ghimire S. and Jardim-Gonçalves R..
Toward a Unified Intercloud Interoperability Conceptual Model for IaaS Cloud Service .
DOI: 10.5220/0004879306730681
In Proceedings of the 2nd International Conference on Model-Driven Engineering and Software Development (MDSE-2014), pages 673-681
ISBN: 978-989-758-007-9
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
After this Introduction in Section 1, Section 2
discusses the current state of the art in Intercloud
Interoperability and the motivation for the present
research, addressing cloud architecture and required
parameters for QoS and SLA. The conceptual model
for Intercloud framework is proposed in section 3.
Section 4 and 5 propose the framework and discuss
implementation possibilities. Section 6 concludes
the paper.
2 INTERCLOUD
INTEROPERABILITY
FOR IAAS CLOUDS
Cloud Computing is one of the fastest evolving
technologies in computer science. There are many
analysis and researches on the development of the
general cloud architecture defined by National
Institute
of Standards and Technology (NIST)
(Grance 2010). An IaaS cloud service provider may
have limited computing resources that can be one
challenge for cloud developers (Bernstein
2009)(Bernstein et al. 2009)(Parameswaran &
Chaddha 2009). The provisioning of the computing
resources using IaaS multi-providers in an inter-
cloud environment can be a powerful approach to
solve this issue (Demchenko et al. 2013). However,
cloud computing needs more research work to
provide sufficient functions to enable seamless
collaboration between IaaS cloud services.
Considering use cases proposed by NIST
(Badger et al. 2010), Lewis (Lewis 2012) identified
“Workload Migration” one of the four main cloud
interoperability use cases that can benefit from
current standards. Intercloud interoperability for
IaaS service cloud providers should be able to allow
IaaS cloud provider to migrate the workload to other
Figure 1: Intercloud Computing Generic Architecture.
MODELSWARD2014-InternationalConferenceonModel-DrivenEngineeringandSoftwareDevelopment
674
selected IaaS providers to execute based on the
appropriate requirements and then collect the results
without a lock-in.
Celesti (Celesti et al. 2010) proposed a three-
phase (discovery, match-making, and authentication)
cross-cloud federation model for a general cloud
architecture.
(Bernstein & Vij 2010) investigated that many-
to-many mechanisms such as Messaging and
Presence Protocol (XMPP) for transport, and
Semantic Web techniques such as Resource
Description Framework (RDF) can be the
appropriate approaches for inter-cloud
environments.
In this paper, the conceptual perspective for
Intercloud Interoperability is studied for the second
use case defined by NIST: Dynamic Operation
Dispatch to IaaS Clouds, where many questions
concerning intercloud interoeprability are still open.
The focus is on the definition of all required
parameters and in the proposal of the conceptual
model for Intercloud Interoperability for workload
migration. In future, we intend to design and
implement the proposed framework followed by
simulation.
2.2 Required Concepts for Intercloud
Interoperability Framework
NIST proposed a cloud computing definition (Mell
& Grance 2009) as follows: “Cloud computing is a
model for enabling convenient, on-demand network
access to a shared pool of configurable computing
resources that can be rapidly provisioned and
released with minimal management effort or service
provider interaction”. Thus, the term “Cloud” is
used to describe the networks that incorporate
various technologies, without the user knowing it.
Considering regular Cloud Architecture,
Intercloud Architecture has to introduce an extra
module for Intercloud Interoperability. Figure 1
depicts the intercloud conceptual model adopted in
this research. The main Service Models are:
Software as a Service (SaaS)
Platform as a Service (PaaS)
Storage as a Service (DaaS)
Communication as a Service (CaaS)
Infrastructure as a Service (IaaS).
The proposed interoperability framework for
IaaS cloud service providers forwards the workload
to selected IaaS cloud providers. Thus, the proposed
conceptual model considers the collected protocols,
standards, formats, and common mechanisms by
Bernstein (Bernstein et al. 2009) that can be useful
for intercloud architecture.
Moreover, this paper refers to other references
that formally describe QoS (Wang et al.
2012)(Salama et al. 2012)(Goyal et al. 2012) and
SLA (Rubach & Sobolewski 2009)(Sun et al. 2013).
Then, it identifies the required parameters and
metrics for SLA and QoS modules that are
fundamental for intercloud interoperability.
2.2.1 Appropriate QoS-SLA Metrics
Numerous cloud services with different pricing and
Quality of Services (QoS) exist in an intercloud
environment which makes it complicated to select
the best composition of services based on consumer
requirements. To distinguish the most appropriate
combination of services, Intercloud Interoperability
framework should consider QoS criteria and Service
level agreements (SLAs) as a contract negotiated
and agreed between the service provider and the
consumer.
Some previous research work have been
studied the appropriate models for QoS in cloud
Figure 2: Required QoS Parameters for IaaS services.
Figure 3: Required SLA Metrics for IaaS over Intercloud.
TowardaUnifiedIntercloudInteroperabilityConceptualModelforIaaSCloudService
675
environment (Wang et al. 2012)(Salama et al.
2012)(Goyal et al. 2012) that can be beneficial to
our proposed model. Additionally, research on
defining a formal model for SLA has been
considered in various systems (Rubach &
Sobolewski 2009)(Sun et al. 2013).
In this paper, we are aiming to present suitable
SLA-QoS metrics for IaaS cloud service providers
and consumers.
In our conceptual model for Intercloud
Interoperability, the following QoS requirements
have been considered: availability, reliability,
performance, security, scalability, data
communication cost, capacity, and latency
parameters for IaaS cloud service (Figure 2).
Moreover, the appropriate SLA metrics for IaaS
cloud services for all types of requirements are listed
in Figure 3. The SLA metrics include Common SLA
Features which are general requirements for all
cloud services and the Specific SLA features which
are required for delivering IaaS cloud services. To
propose appropriate SLA metrics, we investigated
some previous research work (Rubach &
Sobolewski 2009)(Sun et al. 2013) as well as some
dominant IaaS cloud service providers, such as
Amazon's EC2 (Amazon n.d.), Windows Azure
(Microsoft n.d.), and Rackspace Cloud (Rackspace
n.d.).
3 CONCEPTUAL MODEL
OF INTERCLOUD
INTEROPERABILITY
FOR WORKLOAD MIGRATION
Previous sections specified a conceptual model for
cloud architecture and identified different
requirements such as appropriate QoS-SLA metrics
to resolve interoperability incompatibilities between
heterogeneous IaaS cloud service providers.
This section proposes the detailed
interoperability framework to dispatch part of
workload between other selected IaaS cloud service
providers based on the discussion in the section 2
that enhances our previous work (Nodehi et al.
2013). The conceptual model for the intercloud
framework for IaaS is explained in Figure 4 that
includes following fundamental components:
Intercloud Interface Module: The intercloud
framework receives events for workload migration
through Intercloud Interface.
Model Manager Module: Model Manager receives
tasks from Intercloud Interface and provides the
required details of the task (Object Models,
Operation Models, and Data Model) using
Semantic module accordingly.
QoS and SLAs Repository Module: This module
specifies QoS parameters (proposed in previous
section) for the requirements of each task.
Moreover, the SLA criteria between the current
cloud and other IaaS cloud providers and user
profiles are identified in this module.
Process Executor Module: This component is
responsible for the execution of the business
process based on the details and requirements of
all tasks. This module specifies the appropriate
operations which should be executed to achieve
the defined task. The activity of the process model
is evaluated to choose and perform the appropriate
ones for the current work-flow. This component
also keeps track of all the activities and adds
events to the workload queue.
IaaS Resource Discovery Module: This module
provides the functionality for IaaS cloud providers
discovery. It would exploit information offered by
semantic models and SLA agreements and the QoS
specifications in order to find IaaS Cloud
Resources in other available clouds which meet the
current work-flow requirements.
IaaS Resource Selection Module: Resource
selection component selects appropriate providers
from the network of cloud providers. This module
considers information from SLA-QoS requirement
module and discovered resource providers from
Resource Search and Discovery Module to select
the set of clouds for migrating and dispatching
workloads. It also exploits the information from
Model Manager to make the best suited selection.
Transformation Engine Module: Transformation
Engine performs the necessary model
transformation to map the task details obtained in
Model Manager as per the specifications of the
selected IaaS resources that discovered and
selected in Resource Discovered and Selected
modules. It also uses the semantic module to make
the necessary transformations.
Transformation Engine is the key component of our
framework that can provide interoperability
through mapping workload to other selected cloud
providers.
Semantic Module: Intercloud Semantic is the most
essential module of the architecture with three
components: Object Model, Operation Model, and
Data Model. Semantic layer provides the
functionality to maintain and utilize the semantic
models that will be necessary to obtain
interoperability.
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Figure 4: Intercloud Computing Generic Architecture.
Task Scheduling: Considering the conceptual
cloud architecture in Figure 1, this component
exploits the job-scheduling techniques used in the
host IaaS cloud to dispatch all tasks on the other
selected IaaS clouds through IaaS Resource
Selection component.
Task Results Module: This module collects the
results of performing the dispatched tasks from
selected IaaS clouds, performs the necessary
transformations and maps and sends back the
results through an Interface component to host
IaaS cloud.
4 MDA AND INTERCLOUD
INTEROPERABILITY
The proposed framework is under validation through
simulation experiments. In section 3, the
Transformation Engine module is the key
component of our framework that can provide
interoperability through mapping workload to other
selected cloud providers. Based on our research, a
potential architecture for the implementation of
Transformation Engine component is the Model
TowardaUnifiedIntercloudInteroperabilityConceptualModelforIaaSCloudService
677
Driven Architecture (MDA) (Cretan et al. 2012).
MDA is introduced by Object Management Group
(OMG) as a software development approach to
system-specification and interoperability based on
the use of formal models (OMG 2003). MDA
focuses on the development of models rather than
platform-specific code which can be generated when
needed through three levels of modeling abstractions
(shown in Figure 5):
Figure 5: Model Driven Architectures levels.
Computation Independent Model (CIM) represents
what the business actually does or wants to do in
future, independent of technology specifications.
Platform Independent Model (PIM) provides a
formal definition of the functionality of the
software system and defines data, dependencies
and architectural realizations.
Platform Specific Model (PSM) provides the
details that specify how the system uses a
particular type of platform and ease generating
corresponding code from the PIM that fits the
operating platform.
Transformation techniques play a key role in making
the MDA method successful. It can be categorized
based on the type of source and destination they
operate on (Jimenez 2005):
Code to Code: Here the source and target are
textual artifacts.
Model to Code: This kind of transformation can
produce source code from models, such as
converting PSM to code corresponds to the model-
to-code transformation.
Code to Model: Code to model transformations
generate models from textual representations.
Model to Model: It automates the refinement
process between models. This approach can be
categorized into CIM to CIM, CIM to PIM, PIM to
PIM, and PIM to PSM.
Figure 6 shows the basic model transformation
pattern applied at the model level to convert source
model elements to target model elements. Source
model and target model may represent the same data
with two different formats.
Various transformation languages and tool suites
have been developed, although most of them are at
Figure 6: Model transformation pattern (Koch 2007).
experimental stage yet to be applied to industrial
practice. For instance, Query/View/Transformation
(QVT) is defined by the OMG to describe the
requirements of a standard language for the
specification of model transformation (OMG
2011a), or Graph Rewrite And Transformation
language (GReAT) (Agrawal et al. 2005) is a
metamodel-based graph transformation language
that is designed to deal with the high-level
complexity model transformation programs.
A model transformation produces target models
from source models. This process requires specific
transformation techniques called metamodels.
Metamodel defines the abstract syntax of models
and interrelationships between model elements.
Metamodel specifies the structure of an application
to determine models and the model as an instance of
metamodel contains specific details. For instance, a
metamodel can define the models and relationships
of model elements using classes, objects and
methods in UML. Then, according to the specific
platform, the application derived from model runs in
the real world.
Figure 7: The four layer meta-modeling architecture.
In this regard, OMG has introduced a 4-layer
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architecture called the MOF metamodeling stack
(OMG 2011b) as shown in Figure 7 , MOF is a
Domain Specific Language (DSL) to specify
metamodels. M0 describes the real system. Level
M1 is a model to represent the real system which
includes the details of application. Level M2 is the
metamodel to define boundaries of the model in
level M1. Metametammodels are used to define the
concept of metamodels. The metamodel in level M2
conforms to the metametamodel in level M3.
5 VISION FOR INTERCLOUD
INTEROPERABILITY
FRAMEWORK FOR IAAS
CLOUDS
This paper presented the required concepts and QoS-
SLA criteria for a conceptual model for intercloud
interoperability to address workload migration to
IaaS clouds, which is identified by NIST as one
major use case for cloud computing interoperability
(Badger et al. 2010).
Transformation Engine is the key component of
our framework that supports interoperability. As
discussed in section 4, a potential architecture for the
implementation of core Transformation Engine
component is MDA. Figure 8 shows the overall
picture for intercloud interoperability for IaaS
clouds. Cloud “A” schedules and executes the
specified workload on the other IaaS clouds and
receives the results from them exploiting the
interoperability framework. Application accesses the
functionality of the framework through the
interfaces defined by the framework.
As discussed in section 2, XMPP is a transport
protocol and RDF is a standard model for data
interchange both appropriate for the inter-cloud
environments. The proposed conceptual model
makes use of such standards and other
communication infrastructure as the Transport
infrastructure.
6 CONCLUSIONS
Intercloud Interoperability is tempting when
individual clouds have limited computing resources
in a restricted geographic area. Moreover, Intercloud
Interoperability enables cloud providers to deliver
better quality of services, avoid data lock-in, and
reduce scaling/producing costs. Today, existing
cloud environment does not fully support intercloud
interoperability, and defining a conceptual model for
Figure 8: Vision for Intercloud Interoperability Framework.
TowardaUnifiedIntercloudInteroperabilityConceptualModelforIaaSCloudService
679
Intercloud Interoperability to schedule dynamic
operation for IaaS cloud providers is a requirement
to achieve this objective.
Since, SLA and QoS models are important
factors to introduce a comprehensive Intercloud
Interoperability Framework, the paper refers to some
useful references and proposes the essential metrics
for SLA and QoS to integrate with cloud systems.
Then, a conceptual model for the Intercloud
Framework to dispatch workloads between various
clouds is proposed. The Intercloud Framework
receives tasks through Intercloud Interface; specifies
the task details; considers all required SLA/QoS
metrics; discovers and selects the available IaaS
clouds; maps the task according to each offered
cloud formats and requirements; dispatches the tasks
between selected clouds; and finally collects and
maps the results to an understandable format for the
consumer cloud.
The Transformation Engine component of the
framework is a core module to provide intercloud
interoperability by mapping workloads to other
cloud providers. MDA is identified as an appropriate
approach to develop the Transformation Engine
module.
As to continuing the work, it is planned to adjust
the proposed framework according to the results of
simulation experiments. Future work will expand the
Intercloud framework to support interoperability in
data migration and workload management between
cloud providers.
ACKNOWLEDGEMENTS
The authors sincerely acknowledge the financial
support from the grant of the Portuguese Foundation
of Science and Technology (FCT), the EC 7th
Framework Programme under grant agreement n°
FITMAN 604674 (http://www.fitman-fi.eu), and the
Portuguese Projecto Mobilizador QREN
PRODUTECH.
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