Post on 03-Mar-2023
Grid-Based Decision Support with Pro-Active Mobile Computing
M. Ong, M. Alkarouri, X. Ren, G. Allan, V. Kadirkamanathan,
H.A. Thompson and P.J. Fleming
Rolls-Royce Supported University Technology Centre in Control and Systems Engineering,
Department of Automatic Control and Systems Engineering,
The University of Sheffield, UK.
{M.Ong, M.Alkarouri, X.Ren, G.Allan, Visakan, H.Thompson, P.Fleming}@sheffield.ac.uk
Abstract With the emergence of Grid computing and
service-oriented architectures, computing is
becoming increasingly less confined to traditional
computing platforms. Grid computing promises the
accessibility of vast computing and data resources
across geographically dispersed areas. This
capability is significantly enhanced by establishing support for mobile wireless devices to deliver access
to high-performance computing under demanding
circumstances. Access to the Grid from mobile
devices can be very effective in business
environments where users can access the vast computing power and data repositories on the Grid
while working out on the field. This also enables and
encourages collaborative working environments. A
Grid demonstrator system for distributed aircraft
health monitoring already developed and
implemented in the UK E-Science Grid project, DAME, is introduced. In this demonstrator, CBR
technology for decision support is implemented in a
practical framework that enables Grid-based, pro-
active mobile computing.
1. Introduction
With the recent advances in Grid computing and
service-oriented architectures, computing is
becoming increasingly less confined to the traditional
computing platforms of desktops, servers or
mainframes. While Grid computing itself promises
the accessibility of vast computing and data resources
across geographically dispersed areas, there is
currently a lack of established support for Grid-based
mobile computing. Grid-enabled computing with
mobile devices can be very effective in a multitude of
business environments. Users can have access to the
computing power and data repositories on the Grid
while working out on the field. Mobile Grid access
also enables and encourages distributed,
collaborative problem-solving environments.
A Grid-enabled mobile computing demonstrator
has been developed in the context of the Distributed
Aircraft Maintenance Environment (DAME) project.
The context for the demonstrator developed in
DAME is an aero-engine diagnosis and prognosis
problem (figure 1). This paper focuses on one of the
many DAME system components, the CBR
Maintenance Advisor, as an example of how Grid-
enabled services can be extended to handheld devices
for pro-active mobile computing (figure 2) to support
aircraft fault diagnosis. The developments reported in
this paper complements the developments in
optimisation [13].
Figure 1. Distribution of data in a virtual aircraft maintenance environment
2. Grid Computing
The Grid computing concept, first developed in
the scientific community, was initially aimed to
address the problems of sharing and working with
large datasets. Grid computing is now moving
towards a mainstream challenge of creating reliable,
robust, scaleable and secure distributed systems. The
Grid [2, 3] is an aggregation of geographically
dispersed computing, storage and network resources,
co-ordinated to deliver improved performance,
Proceedings of the 2005 IEEE International Conference on Services Computing (SCC’05) 0-7695-2408-7/05 $20.00 © 2005 IEEE
higher quality of service, better utilisation and easier
access to data. In this project, Grid computing has
enabled collaboration between numerous members of
the “virtual organisation” involved in the aero engine
maintenance scenario. This has enabled the sharing
of applications and data in an open, heterogeneous
environment. Compute-intensive decision support
tools previously considered to be host-centric can
now be distributed throughout a network of powerful
Grid nodes, improving quality of service while also
offering enhanced and improved capabilities. The
emergence of Grid software such as the Globus
Toolkit [4] provides the necessary middleware to
implement a Grid system and includes services that
tackle issues such as accessibility, security and
resource management.
The DAME project was implemented on a key
metropolitan Grid infrastructure, the White Rose
Grid [16], constructed between the partner
institutions Sheffield, Leeds and York at a cost of
£2.8M.
Figure 2. Service structure that enables access to a Grid-enabled service via the Internet on mobile handheld devices and conventional computers
3. Distributed Aircraft Maintenance
Environment (DAME)
Aero-engines are extremely reliable machines and
operational failures are rare. However, currently
great effort is being put into reducing the number of
in-flight engine shutdowns, aborted take-offs and
flight delays through the use of advanced engine
health monitoring technology. This represents a
benefit to society through reduced delays, reduced
anxiety and reduced cost of ownership of aircraft.
This is reflected in a change of emphasis within aero
engine companies where, instead of selling engines
to customers, there is a fundamental shift to adoption
of power-by-the-hour contracts. In these contracts,
airlines make fixed regular payments based on the
hours flown and the engine manufacturer retains
responsibility for maintaining the engine. To support
this new approach, improvements in in-flight
monitoring of engines are being introduced with the
collection of much more detailed data on the
operation of the engine. Advances made in Internet
technologies can provide a worldwide network of
computers that can be used to access and process that
data. The explosion of information within those large
datasets and a variety of diagnostic tools available
also presents it’s own problems. Here, it is necessary
to work on delivering advanced decision support
systems to the aircraft experts in order to aid
identification of useful information in the data and
provide effective diagnostic support between
individual aircraft, airline repair and overhaul bases,
world-wide data warehouses and the engine
manufacturer (figure 1).
The DAME project is a Grid pilot project
supported under the United Kingdom e-Science
research programme in Grid technologies [1,8].
DAME is particularly focused on the notion of proof
of concept, using the Globus toolkit and other
emerging Grid technologies to develop a
demonstration system. This is known as the DAME
Diagnostic/Prognostic Workbench. The demonstrator
Proceedings of the 2005 IEEE International Conference on Services Computing (SCC’05) 0-7695-2408-7/05 $20.00 © 2005 IEEE
system tackles complex issues such as security and
management of distributed and non-homogenous data
repositories within a diagnostic analysis framework
with distributed users and computing resources.
3.1. Diagnostic Scenario
A typical diagnostic scenario is as follows: The
on-wing diagnostic system and its associated ground
based system are used prior to the use of DAME. In
addition to that initial on-wing diagnosis, DAME is
always used to provide an automated diagnosis. This
is desirable because DAME can detect additional
situations, for example:
A recurring errant diagnosis
A new condition that has not been yet been
uploaded to the on-wing monitoring system
A condition that can only be detected using tools
that require extensive ground-based processing
facilities
The resultant automatic diagnoses can then be
assessed. In the vast majority of cases normal
situations are indicated, however, if a condition is
detected with a known cause then appropriate
maintenance action can be planned. Additionally, in
the rare case that a condition is detected without a
clear cause then the situation will be “escalated” to
one of various remote experts who can look into the
matter further. The Maintenance Analysts and
Domain Experts have access to the data from the
current engine flight, can run searches on historical
data, get workflow advice, run signal processing and
simulation tasks to gain an insight into any given
event.
3.2. Decision Support in DAME
It is clear that in order to deal with the explosion
in data available from complex engine health
monitoring systems, it is necessary to design
advanced decision support systems. These need to be
able to identify faults based on knowledge of
previous fault conditions and also perform analysis
across fleets of engines. A variety of on-wing control
system diagnostic techniques and portable
maintenance aid tools have been explored. The
research at the Rolls-Royce supported University
Technology Centre (UTC) at the University of
Sheffield has been based on two fundamental
underpinning technologies, Case-Based Reasoning
and model-based fault detection and isolation [12],
the first of which will be described in more detail.
3.3. Case-Based Reasoning
Case-Based Reasoning (CBR) is a knowledge-
based, problem-solving paradigm (figure 3) that
resolves new problems by adapting the solutions used
to solve problems of a similar nature in the past
[9,10]. A further advantage of this approach is that it
allows consolidation of rule knowledge and provides
a reasoning engine that is capable of probabilistic-
based matching. With CBR technology, development
can take place in an incremental fashion facilitating
rapid prototyping of an initial system. The
development of robust strategies for integration of
multiple health information sources is achieved using
reasoning algorithms of progressively increasing
complexity. In contrast to conventional search
engines, CBR systems contain a knowledge model of
the application domain in which it operates on. It is
therefore not universal but specifically designed for
the domain. Hence, it is possible to develop
intelligent search abilities, which even show
reasonable results when given fuzzy or incomplete
requests. Moreover, the results are ranked and
complemented by variants and alternatives, thus, not
only matches are given but information is valued
with "more suitable" or "less suitable".
Figure 3. CBR problem solving paradigm that builds upon previous knowledge
The work presented here builds on previous
research work which included investigating the use
of CBR techniques for a portable PC-based Flightline
Maintenance Advisor [6,7] to correlate and integrate
fault indicators from the engine monitoring systems,
Built-In Test Equipment (BITE) reports, maintenance
data and dialog with maintenance personnel to allow
troubleshooting of faults (figure 4). The outcomes of
the initiative included the implementation of a
portable Flightline Maintenance Advisor that was
trialed with Singapore Airlines.
Figure 4. Structure of the Flightline Maintenance Advisor
Proceedings of the 2005 IEEE International Conference on Services Computing (SCC’05) 0-7695-2408-7/05 $20.00 © 2005 IEEE
Today, rather than using a portable, stand-alone
computer that needs updating with new data as it
becomes available, it is highly desirable for a fault
diagnosis system to be accessed remotely by
engineers over a computer network. The advantage
of this is that it is easier to support and also allows
search of an extensive casebase of historical
maintenance incidents across an entire fleet of
engines [11] at a global scale. This allows
identification of the most appropriate course of action
to diagnose and rectify an engine problem with a
prescribed set of fault symptoms.
Essential to the CBR system is the casebase that
represents a knowledge repository containing
detailed descriptions of engine faults and the best
practice maintenance advice (solutions) gathered
from engineers and experienced mechanics over the
development and service life of the engine. For a new
engine type, little information is known initially but
the advantage of CBR techniques is that a casebase
of independent records of fault and maintenance
information can be developed in a piecemeal manner
and updated as and when knowledge about the
behaviour of the system is known. More importantly,
the siting of the CBR system within a virtual
maintenance facility also allows the integration of
diagnostic knowledge from multiple health
information sources which are vital in improving the
accuracy and coverage of the CBR knowledge
repository. Useful diagnostic information previously
available from separate monitoring systems, when
brought together into a single system, provides for a
more powerful diagnostic tool.
3.4. Service-based CBR
In support of the demonstrator, an in-house,
reconfigurable service-based CBR application has
been designed and implemented at the Sheffield UTC
as a Grid service. Grid services [5] are essentially
Web services with improved characteristics such as
state and life-cycle management. The CBR service
has been deployed in the DAME Grid computing
environment. Using a Web browser, aircraft
maintenance personnel can access this service via a
secure portal to the service from any computer
connected to the Internet. Fault information can be
submitted to the service directly via the Web browser
window (figure 5) or submitted automatically via an
integrated client such as the one in the DAME
automatic workflow system. The service processes
the fault information on a remote Grid node by
searching and matching across a large history of
cases and returns a set of ranked, closest matching
case.
The service can provide aircraft maintenance
personnel at various levels with access to stores of
accumulated diagnostic knowledge and maintenance
data. It is understood that with CBR, solutions
proposed for an unknown problem may not always
represent the ultimate solution but here it is important
to note that proposed solutions serve as a crucial
starting point for further analysis. At this point, the
user can select another diagnostic tool on the portal
that can utilise readily available Grid resources to aid
the decision-making process.
Figure 5. Web browser window displaying a result list of cases that match a query for a particular engine fault. For each brief case listed, the detailed fault information and maintenance advice can be obtained by retrieving the full case details
4. Mobile Handheld Device for Grid-
based Computing
In addition to the typical diagnostic scenario
described previously, a situation may arise where a
Domain Expert requires an analysis of a currently
occuring problem under demanding circumstances;
i.e. a conventional computer is not available to access
the DAME system. Furthermore, the ability of a
handheld computer to capture information on-site in
various forms and to instantly upload investigative
findings to the system on the Grid greatly increases
the accuracy of CBR in diagnosing the problem. The
rapid sharing of real-time information across the
DAME environment enables several engine experts
at distributed locations to collaboratively solve the
problem, thus reducing aircraft down-time and costs.
A mobile computing device such as the widely
available Personal Digital Assistant (PDA) presents
various problems such as hardware constraints, small
graphical display area and security issues. The
limited local processing power and built-in memory
available means that applications need to be
efficiently implemented and this may mean
excluding the use of complex programming
environments/frameworks. Software development for
mobile handheld devices tend to be more complex to
take into account the device’s operating system and
hardware platforms. A small display area usually
found on such devices can also make presentation of
information to the users a challenging task.
Proceedings of the 2005 IEEE International Conference on Services Computing (SCC’05) 0-7695-2408-7/05 $20.00 © 2005 IEEE
4.1. PDA Demonstrator System
In order to overcome these limitations, a
demonstrator consisting of a PDA that utilises the
previously mentioned Grid-based CBR service was
developed for aero-engine fault diagnosis. The device
itself is a widely available HP iPAQ device that
features a built-in wireless network interface and
Web browser. Using a standard Wi-Fi (802.11b),
Bluetooth or GPRS (over GSM) wireless Internet
connection, the PDA is able to access services
available on the Grid, thus offering the benefits of
distributed, high performance computers required to
achieve the desired tasks (figure 2).
The current capabilities of PDAs make it
impossible to have a complete Globus toolkit
equivalent implementation on the device. This
mandates the use of a proxy that will interact with the
Grid environment while providing suitable access for
the device, and a client for this proxy on the device.
Here, a mini Web portal is used as a proxy, enabling
the device to access the Grid using a standard, built-
in mini Web browser as a client.
The mini Web browser represents the front-end to
the system on the PDA that allows the user to access
the customised Web portal to the Grid service. This
portal is very similar to the standard portal accessed
by conventional desktop computers, the difference
being that the mini-portal is simplified by the
removal of complex script functions normally aimed
to enhance the layout of content on larger displays.
Furthermore, the page layouts are rearranged such
that every page executes a single operation at a time,
both for display purposes and to optimise on
bandwidth usage. The mini portal can deliver a
similar quality of results to the user whilst
minimising the graphical content load on the PDA
display.
When in use, the PDA can search and match a
currently occuring problem, given initial information
about the problem, with a large archive of historical
cases on the Grid. Matching cases (figure 6) can be
adapted to form a new case to represent the current
problem. Additional knowledge gained from further
analysis, such as vibration information (figure 8),
digital photos or even audio/video media can be
appended to the case in real-time as it is being
investigated, making it available across the Grid and
if necessary escalated to an expert at a different
location. It is this model of collaborative problem-
solving that is defined in this paper as pro-active
handling of the currently occuring situation by the
right person, in the right place at the right time.
The identification and successful solution to the
problem can finally be appended to the case via the
same interface and stored on the Grid as “new
knowledge” for future use (figure 7). To support the
diagnostic process, compute-intensive engine
performance simulations, normally a time-consuming
task, can be executed on the Grid and the results
retrieved on the PDA. Figure 9 shows an abnormal
spike identified in the engine data relating to the
occuring problem that was made available to the
engineer via the PDA.
Figure 6. PDA’s Web browser window displaying the result list from a search for cases that match a currently occuring problem
Figure 7. In-depth details and maintenance advice can be retrieved, viewed and appended on the PDA
The software and standards used for this
particular demonstrator system is based on widely
accepted Internet standards thus it is highly feasible
for the system to be implemented across various
other applications areas. The increasing availability
of wireless networks and advances in Grid
Proceedings of the 2005 IEEE International Conference on Services Computing (SCC’05) 0-7695-2408-7/05 $20.00 © 2005 IEEE
technology provide a strong case for wireless, Grid-
enabled decision support with mobile computing
devices.
Figure 8. Time series vibration spectrum data for problem in question is available on the PDA for further investigation.
Figure 9. Spike in engine data from the model simulation indicates the cause of the fault to the diagnostic engineer using the PDA
The capability displayed by the demonstrator
system is particularly important because it offers
aircraft experts, considered as a high-value resource,
the mobility to pro-actively operate on large data and
complex problems under demanding circumstances.
Similar scenarios can occur in many diverse IT
domains such as healthcare, engineering, finance and
environmental sciences. However, regardless of the
application area, the systems share a number of
similar operating and design characteristics, making
it possible to experience similar benefits of Grid-
enabled, pro-active mobile computing. The next
section describes how emerging service-oriented
technologies have been used to support the
framework that enables that.
4.2. Service-Oriented Architecture
Service-oriented architectures (SOA) are
essentially a collection of services, focusing on
interoperability and location transparency. These
services communicate with each other, and can be
seen as unique tools performing different parts of a
complex task. Communication can involve either
simple data passing or it could involve two or more
services co-ordinating some activity. SOAs and
services are about designing and building system
using heterogenous network addressable software
components. An important aspect of the SOA is that
it separates the service’s implementation from its
interface. Web services, are services offered via the
Web.
In the demonstrator scenario, the browser
application initiates a request to the CBR service at a
given Internet address using the SOAP1 protocol over
HTTP2. The CBR service receives the request,
processes it, and returns a response. Based on the
emerging standards such as XML3, SOAP, UDDI
4,
and WSDL5, the CBR service along with other
services in the DAME system form a distributed
environment in which applications, or application
components, can inter-operate seamlessly across the
virtual organisations in a platform-neutral, language-
neutral fashion. The CBR service consumers can
view the service simply as an endpoint that supports
a particular request format or contract. Consumers
need not be concerned with how the CBR service
goes about executing their requests; they expect only
that it will.
Grid computing support for the CBR service is
provided by means of implementing Open Grid
Services Architecture (OGSA) concepts with web
service technologies. The CBR service benefits from
both web service technologies as well as Grid
functionality. Compute-intensive tasks within the
1 SOAP - Simple Object Access Protocol 2 HTTP - Hyper Text Transfer Protocol3 XML - eXtensible Markup Language 4 UDDI - Universal Description, Discovery and Integration 5 WSDL - Web Services Description Language
Proceedings of the 2005 IEEE International Conference on Services Computing (SCC’05) 0-7695-2408-7/05 $20.00 © 2005 IEEE
CBR matching process, previously computed locally,
are now aggregated across the available compute
nodes using Grid middleware, the Grid’s effective
operating system [4]. With this, multiple instances of
the service are created on-demand to allow multiple
consumer requests to be processed simultaneously by
separate nodes of the Grid (figure 10). With the CBR
service as a prime example, the integration of Grid
computing with Web services can provide aircraft
experts at any remote geographical location with
access to powerful diagnostic tools, data repositories
and large computing resources to support that via a
mobile handheld device.
Figure 10. Multiple instances of the CBR service are distributed for processing on Grid nodes, each instance supporting an individual process
4.3. Security
A Grid-enabled decision support system may
contain potentially business-sensitive data and hence
access to data and services should be restricted to
authorised members within the virtual organisation.
For instance, both the CBR knowledge base and
engine models could contain important information
on aero-engine design characteristics and operating
parameters. The use of the Grid Security
Infrastructure (GSI) [14] enables a system for secure
authentication and communication over an open
network. GSI consists of a number of security
services including mutual authentication and single
sign-on. This is based on public key encryption,
X.509 certificates, and Secure Sockets Layer (SSL)
transmission. The implementation of GSI within the
DAME decision support environment is composed of
Globus Toolkit 3 (GT3) security elements
conforming to the Generic Security Service API
(GSS-API), which is a standard API for security
systems promoted by the Internet Engineering Task
Force (IETF).
At the core of the GT3 security infrastructure is
client and host authorisation using X.509 identity
certificates for both the service users and service
hosts. Hence, all users and service hosts need to
acquire a certificate issued by a trusted Certificate
Authority (CA). Because the CA is the heart of the
security system, it is very important that Grid hosts
and users only use their own trusted CA or an
established commercial CA. A CA’s signing policy is
placed in the Grid computing environment to allow
nodes to authenticate users holding valid certificates.
On top of this, users have their user credentials listed
on a Grid-Mapfile. The Grid-Mapfile is a file used to
store mappings between a user identity on the Grid to
a local identity (an account name on the Grid
computer being used). DAME system users are only
allowed to access the decision support services and
Grid resources on any Grid node if their verified
credentials have been registered beforehand by the
Grid administrators.
5. Concluding Remarks
This paper described how Case-Based Reasoning,
one of the core technologies available for health
monitoring in DAME has been developed to extend
the benefits of Grid computing to mobile handheld
devices. Although developed for the aero-engine
problem, the pro-active PDA implementation along
with its service-based architecture is applicable to a
variety of domains involving distributed data sources
and dynamic working environments. The PDA
demonstrator has shown that Grid-enabled computing
from mobile devices can be very effective in a
Proceedings of the 2005 IEEE International Conference on Services Computing (SCC’05) 0-7695-2408-7/05 $20.00 © 2005 IEEE
business environment by providing access to
powerful services and Grid functionality under
demanding circumstances. This also enables and
encourages distributed, collaborative working
environments. In the future, the demonstrator
framework presented in this paper is also highly
applicable within crisis management scenarios where
teams of mobile workers, such as paramedics, police,
firefighters or military personnel need to collaborate
in critical situations. Access to real-time information
and knowledge, simulation of the situation,
optimisation and logistics support can greatly
improve the decision-making processes for pro-active
management of the situation.
Acknowledgements
The authors gratefully acknowledge financial support
of the Engineering and Physical Research Council in
the UK under Grant Number GR/R67668/01 and
contributions from Rolls-Royce plc and Data
Systems & Solutions, LLC.
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Proceedings of the 2005 IEEE International Conference on Services Computing (SCC’05) 0-7695-2408-7/05 $20.00 © 2005 IEEE