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

 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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364

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).

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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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