REMOTE CONTROL AND TELE-OPERATION IN THE CLOUD
Salvatore F. Pileggi, Carlos Fernandez-Llatas and Vicente Traver
TSB-ITACA, Universidad Politécnica de Valencia, Valencia, Spain
Keywords: Cloud computing, Grid computing, Tele-operation, Remote controls, Distributed systems.
Abstract: Remote controls and tele-operation platforms are object of great commercial interest in several application
domains and disciplines. Reliable and effective platforms could completely change the vision at certain
environments, as well as novel perspectives for production and business models could be a reality. The
cloud environments are constantly increasing their popularity providing competitive and dynamic solutions
for distributed computing and systems. In this paper, remote controls and tele-operation platforms are
considered as composed of pervasive cloud services.
1 INTRODUCTION
Tele-operation indicates operation of a machine at a
distance (Teleoperation, Wikipedia). It is similar in
meaning to the phrase "remote control" but is
usually encountered in research, academic and
technical environments. It is also and most
commonly associated with robotics and mobile
robots but can be applied to a whole range of
circumstances in which a device or machine is
operated by a person from a distance (Teleoperation,
Wikipedia). Tele-operation can be associated to
local environments (clients and machines/devices
are connected to a local communication
infrastructure) or it can be understood as a low-range
distributed environment in which remote client
access and operate remote machines or devices
through Internet. In the first case (local control), the
QoS can be managed and tele-operation platforms
can be designed considering a really low response
time that positively affect the overall performance.
On the other hand, the design of high-scale internet
enabled remote controls implies unpredictable
performances as well as the need of providing
acceptable performances and reliability for time-
critical operations.The last generation of internet
services and applications is been designed according
to a Cloud approach (Mell and Grance,
2009);(Weiss, 2007); (Hayes, 2008). "Cloud
computing is a Web-based processing, whereby
shared resources, software, and information are
provided to computers and other devices on demand
over the Internet" (Cloud Computing, Wikipedia).
Details are abstracted from the users that are
supported by the technology infrastructure "in the
cloud". Cloud computing describes a novel
consumption and delivery model for IT services
enabling dynamic and scalable environments for the
sharing of virtual resources. The term "cloud" is also
used as a metaphor for the Internet. Most cloud
computing infrastructures consist of services
delivered through common centers and built on
servers. Clouds often appear as single points of
access for consumers' computing needs. The last
generation of Cloud Technology allows users to feel
remote resource and software remotely running as
part of its own computation resource. Cloud vision
enables several innovative business scenarios that
assume customers do not own the physical
infrastructure. Cloud Computing has become a
scalable services consumption and delivery platform
in the field of Services Computing. At the moment,
several classes of cloud services can be identified
(Baliga et al., 2011): in a cloud environment,
software, storage and processing can be viewed and
provided as services. The Cloud vision is affecting
the evolution of the great part of systems and
platforms. A consistent example is the relatively
recent application of cloud technologies to increase
the capacity of robots that rely on cloud-computing
infrastructure to access vast amounts of processing
power and data (Guizzo, 2011). This analysis is easy
to be extended to the great part of physical resources
(e.g. sensors (Yuriyama and Kushida, 2010)): they
are available as virtual resource for high-capable
remote processing services that build knowledge on
361
Pileggi S., Fernandez-Llatas C. and Traver V..
REMOTE CONTROL AND TELE-OPERATION IN THE CLOUD.
DOI: 10.5220/0003597103610367
In Proceedings of the 6th International Conference on Software and Database Technologies (IWCCTA-2011), pages 361-367
ISBN: 978-989-8425-76-8
Copyright
c
2011 SCITEPRESS (Science and Technology Publications, Lda.)
the basic data provided by physical resources. An
exhaustive overview on the last generation cloud
technologies, as well as the analysis of current
limitation and potential benefits, is really interesting
but out of paper scope. In this paper, remote controls
and tele-operation is analyzed as cloud services.
First of all, a brief analysis about cloud technologies
and their relationship with grid computing is
proposed (section 3). The section 4 would introduce
the tele-operation as cloud service and, finally, in the
section 5 some experimental results are proposed in
order to provide a first preliminarily overview at
current limitations in terms of performance
considering realistic scenarios.
2 RELATED WORK
Remote controls and tele-operation platforms are
commonly used in the context of several domains
and disciplines. An exhaustive analysis in this sense
is out of paper scopes. The increasing popularity of
cloud environments, supported by high-capable
networks, could progressively extend the current
view at cloud services, including remote controls,
tele-operation and other services potentially affected
by time-critical operations. In the section 5, first
remote operations will be classified in function of
their relationship with the response time; then a
qualitative analysis supported by experimental data
is provided.
3 GRID AND CLOUD
COMPUTING
In the context of this work, the characterization of
the logic and technologic environment can be
approached according to several methodologies. The
idea is providing a modern and dynamic view at
virtual organizations (Foster et al., 2001). In order to
archive this goal, an analysis of the relationship
between grid and cloud computing (Foster et al.,
2008) is proposed in the section.
The Grid approach for the systems development
is explained by the following definition:
A computational grid is a hardware and software
infrastructure that provides dependable, consistent,
pervasive, and inexpensive access to high-end
computational capabilities (Foster, 2002).
Cloud Computing is defined as in the follow:
A large-scale distributed computing paradigm that
is driven by economies of scale, in which a pool of
abstracted, virtualized, dynamically-scalable,
managed computing power, storage, platforms, and
services are delivered on demand to external
customers over the Internet (Mell and Grance,
2009).
Evidently the problems are mostly the same in Grids
and Clouds as well as the vision is really similar
(Foster et al., 2008). On the other hand, there are
significant differences between these solutions in
terms of both business model (project-oriented for
Grid, consumption-based for Cloud) and
computation model (resource-centric for Grid,
platform-centric for Cloud as showed in Figure 1)
(Foster et al., 2008). A deeper analysis of cloud
platforms by a business perspective is provided by
(Chang et al. 2010); a technical perspective should at
least distinguish among:
Infrastructure as a Services (IaaS) that
virtualizes machines according to an approach
similar to Grid.
Figure 1: Relationship between Grid and Cloud Computing.
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Platform as a Service (PaaS) based on the
virtualization of services.
Software as a Service (SaaS) is a software
delivery model in which software and its
associated data are hosted centrally and are
typically accessed by users using a thin client
(Software as a service).
Summarizing, Cloud and Grid have a strong
convergent point even if they are not the same. In
the context of this work, the power of the
virtualization (of resources and/or platforms) on
large scale is the key issue as well as the pervasive
approach to distributed systems.
Clouds and Grids can so referred as the same in
this context.
4 REMOTE CONTROL
AND TELE-OPERATION AS
CLOUD SERVICES
Cloud environments are applied in the context of an
increasing number of applications and disciplines. In
this section, a short discussion on the platform
model that enables remote controls and tele-
operations in the cloud is proposed.
4.1 Virtual Organizations in the Cloud
Page Setup
Cloud models allow innovative and high-competitive
solutions for remote control and tele-operation. The
benefits introduced by the cloud vision can be
analyzed according to a two-side perspective:
Cost/efficiency: support services can be
provided by external and specialized providers.
More concretely, a notable number of
environments generate and need to store
consistent amounts of information. Also high-
performance data processing is often required.
The clear separation between physical
environments and support services could limit
the cost of the maintenance.
Flexibility: virtual environments built on the top
of cloud technologies (Figure 2) and so
composed of pervasive services can be accessed
by any kind of devices because lack of the need
of local computation. In other word, there is a
potential improvement of the capabilities for the
reference virtual organizations.
A further interest points are the appliance approach
to platforms (Epstein et al., 2010) and the mobile
cloud (Kovachev et al., 2010). The resulting Virtual
Organization is composed of several interacting
actors:
Physical Resources: any class of active (e.g.
sensors) or passive (to be controlled) device.
Resources/services in the cloud: common cloud
services such as storage, computing and
software.
Both infrastructure models assume hybrid final
applications (Sotomayor et al. 2009) composed of a
Figure 2: Schematic view of the Cloud Environments for remote control and tele-operation.
REMOTE CONTROL AND TELE-OPERATION IN THE CLOUD
363
set of CORE services (private cloud (Sotomayor et
al. 2009)) for tele-operation and controls and of
external services that provide support functionalities
(data storage, software, computation resource, etc).
Cloud Platforms: orquestration/choreography of
complex services.
Clients: support to final users.
The effective relationship between cloud
platforms and clients could be quite different in
practice and it could depend by several factors such
as concrete business models, application
requirements and technological factors.
4.2 Remote Control and Tele-operation
Model
In order to develop virtual environments able to
support effective remote control and tele-operation
in the cloud, the background model has to be
carefully analyzed. The key issue is the physical
infrastructures that enable physical resource in the
cloud. There are two main approaches:
Centralized Model: single resources are enabled
in the cloud. This model allows improved
centralized management models but it could
propose a certain decreasing of the
performances if the environment (Figure 2)
requires internal interaction among single
resources.
Distributed Model: only environments are
enabled in the Cloud (Figure 3). The resulting
management model is intrinsically more limited
in terms of interaction of services as well as the
background environment needs of its own
management.
5 A PRELIMINARY
EVALUATION: CURRENT
LIMITATIONS
The cloud approach to systems development is
concretely applicable under the assumption of high-
capable networks. Controlled networks allow the
QoS management, on the contrary, consuming
remote services through Internet implies an
unpredictable response time.
Considering a generic distributed environment,
remote operations can be classified in function of
their sensibility to the response time as in the follow:
No-affected: operations that are not affected by
the response time.
QoS-driven: the response time determines the
“quality” of the operation affecting the quality
of service and/or the quality of the experience.
The operation has not a strict functional
requirement in terms of response time. However
considering that the response time determines
Figure 3: Enabling Remote Control/Tele-operation in the Cloud.
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the “goodness” of the operation so that a short
response time is expected.
Time-critical: operations that have a strong
response time requirements. They can be
considered correct operations only if their
response time is inferior to the required.
It is interesting to have an experimental view at the
effective response time using concrete technologies
and environments. This work just proposes a
preliminarily evaluation based on the following
assumptions:
Only one technology (Globus Toolkit 4 (Globus
Toolkit (GT))) is considered. The evaluation
will be extended to more technologies in future
works.
Only IP networks are considered.
The scenarios represented in Figure 4 are
considered: accessing services from local
networks (Scenario a) is a good approximation
for “private” clouds. At the same time, it
provides a key reference for the evaluation of
more complex scenarios (Scenario b) in which
the access network is Internet.
Only basic operations (as defined in Table 1)
are considered. An evaluation of concrete
services is out of paper scope.
The response time is related to the ping time to
assure a relationship with the status of the
network during the experiment.
The proposed analysis is just indicative. An
analytic model that allows a deeper evaluation
is currently a work in progress. The main
assumption is that the overall performance of
the services is proportional to the performance
of the basic operations.
A number of experimental results referring the
Scenario a (Figure 4) are represented in the Figure 5.
As showed, the scenario is characterized by really
short average ping-times: response times are a good
estimation of the best performance allowed.
Obtained results also put in evidence that the
considered basic operations have similar response
times.
If topologies that propose higher ping-times
(scenario b) are considered, performances
fundamentally and intrinsically depend by network
performance. The Figure 6 represents the response
times obtained by random access to services from
different networks under variable conditions. As
showed, the response times have significant
variations respect to the average value and, so, the
relation with the ping time is not clearly defined as
for the previous scenario.
Table 1: Basic remote operations.
Operation Description
Class 1 Change remote variable value
Read remote variable value
Write a value in a remote file system
Class 1(*)
Class 2
Summarizing, the preliminary experimentation
provided the following issues:
Basic operations have similar response times.
The experimentation on local areas is relatively
simple because it allows a direct and consistent
relationship with the average ping time.
The experimentation considering unpredictable
network conditions requires complex models for
the analysis.
Remote controls and tele-operation platforms could
bring benefit from cloud approach: the next
generation of architectures could propose pervasive
environments composed of distributed cloud
Figure 4: Consuming the service through a local network (Scenario a) and through Internet (Scenario b).
REMOTE CONTROL AND TELE-OPERATION IN THE CLOUD
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Figure 5: Response time within local networks (Scenario a).
Figure 6: Response time accessing resource from Internet (Scenario b).
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services able to provide storage, computation and
software services resulting in a high-scalable models
in which heterogeneous resources are bridged
together.
6 CONCLUSIONS
Cloud environments have great possibilities of
exploitation as well as constantly increasing
perspectives of application.
Cloud models allow innovative and scalable
solutions according to high-competitive business
models.
The increasing capabilities of networks make the
massive migration of local applications to cloud-
based architectures next to be a fact.
ACKNOWLEDGEMENTS
An acknowledgment to the FASYS project (CEN
20091034) and to the Universidad Politécnica de
Valencia.
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