Autonomic computing is a new computing paradigm which combines multiple disciplines of computer science with the sole aim of developing self-managing computer systems. Dating from early 2001, it is one of the most recent paradigm shifts, and as such it is still in a research-only phase, however, attracting a lot of business investors in the process. The following survey presents in a clear and appropriately detailed manner the problem of computer science which autonomic computing tries to solve, the details of the proposed solution, together with the some of the immediate and long-term benefits it will provide. Moreover, the survey outlines the basic principles which define a system as an autonomic one, and presents a novel method of designing autonomic systems. Closing the survey are two sections which briefly outline the most prominent research projects on autonomic computing, together with a distiled summary of the major challenges which will be faced by businesses in the process of adopting autonomic systems.

1. Autonomic Computing: Vision or Reality
Ivo Neskovic
Department of Computer Science, City College - an International Faculty of the
University of Sheffield
3, Leontos Sofou Street, Thessaloniki 54635, Greece
ineskovic@city.academic.gr
Abstract. Autonomic computing is a new computing paradigm which
combines multiple disciplines of computer science with the sole aim of
developing self-managing computer systems. Dating from early 2001, it is
one of the most recent paradigm shifts, and as such it is still in a research-
only phase, however, attracting a lot of business investors in the process.
The following survey presents in a clear and appropriately detailed man-
ner the problem of computer science which autonomic computing tries to
solve, the details of the proposed solution, together with the some of the
immediate and long-term benefits it will provide. Moreover, the survey
outlines the basic principles which define a system as an autonomic one,
and presents a novel method of designing autonomic systems. Closing the
survey are two sections which briefly outline the most prominent research
projects on autonomic computing, together with a distiled summary of
the major challenges which will be faced by businesses in the process of
adopting autonomic systems.
1 Introduction
At the beginning of the last decade, a prominent computing association pre-
dicted a problem similar to the US telephony problem of 1920 [1]. In 1920, the
rapid adoption of the telephone and its frequent use in households, generated
an uncertainty that there would not be enough telephone operators to work the
switchboards [2]. Similarly, IBM in 2001 pointed out the same problem regarding
the widespread use of computer systems [2, 3]. Their prediction stated that until
the end of the decade the IT sector would need 200 million workers to maintain
trillion devices [2]. As a comparison to the extremes of the predicted numbers,
the whole labor force of the United States is 200 million workers. This pre-
diction spawned the creation of the manifesto of Autonomic Computing where
IBM first introduced and coined the term. According to [3] businesses, humans
and devices require the constant services of the IT industry to maintain them.
Furthermore, the complexity of the systems and their interdependencies create
a lack of professional IT personnel to manage said systems [4]. As human de-
pendency on technology grew exponentially, so will the problem of managing
computer systems.

2. 2 The Problem
Small, fast and cheap computer systems have led to tremendous advances in
Information Technology. The prime concern of computer scientists over the past
few decades has been Moore’s Law, while at the same time questioning the
prolonging of miniaturized system components. Although Moore’s Law is a major
issue, it is not the currently biggest issue threatening the IT industry. The major
problem with computer systems is the ever-increasing complexity. They have
become so complex, that if not for a crucial paradigm shift in designing and
managing computer systems, the shortage of skilled IT administrators will cause
Moore’s Law to seem irrelevant [5].
This scenario is similar to the telephony crisis in the US in the 1920s [6].
It has been predicted that every woman in the US, by the 1980 would need to
operate the manual switchboards. This would have been the case if not for the
invention of the automatic branch exchanges. The estimates are that the demand
for IT administrators will double every six years. It had been predicted that by
the end of 2010, 200 million US citizens would have to be IT administrators [6].
The conclusion derived was that the problem will persist, as long as systems do
not develop self-managing capabilities, in order to guarantee that their users will
not dip into the complexity of the systems.
The increasing complexity of computer systems, together with the lack of
skilled professionals, indicates an inevitable demand towards automating the
plethora of functions associated with the maintenance of computer systems. This
is the exact message that Paul Horn, Senior Vice President of Research at IBM,
delivered to the world in 2001 and has spawned a new generation of computing,
autonomic computing.
3 The Solution
Naturally, the solution to the emerging problem, as proposed by P. Horn, ap-
proaches it from the most important, end user’s perspective. Ideally, the end user
desires two primary properties from computer systems: 1) the interaction has to
be intuitive, and 2) their involvement in the smooth running of the system has
to be minimal to none [3].
As with many other scientific breakthroughs, computer science turned to
nature in a quest for inspiration. The only truly autonomic system known to
mankind is the human central nervous system. The autonomic functions of the
central nervous system includes sending control messages to the organs in the
human body at a sub-conscious level, leaving the actual human being unaware
of this process [3]. Temperature and heart rate control, breathing patterns and
pupil dilation are some of the primary functionalities of the nervous system which
are done without any conscious thought. Equivalently, the same pattern can be
applied to computing: a network of autonomic ’smart’ computing components
which provide the user with the desired functionality anytime, anywhere, without
a conscious effort [3].

3. The term autonomic computing, as coined by IBM, is also inspired by the
autonomic nervous system. The purpose of this new computing paradigm is
to transfer the definition of technology, from computing to data [4]. The main
idea is to allow the users to access information from multiple distributed points,
with great transparency to how this is achieved [7, 8]. Moreover, this shift in
paradigms, as presented by IBM, will need to change the focus of the IT industry,
from increasing the processing speed and storage capacity to developing large
distributed networks which are self-managing [9], self-diagnostic and transparent
to use.
Adopting the autonomic computing paradigm, directly implies that design,
implementation and support of computer systems must adopt three basic prin-
ciples which are vital to the end user [10]:
Flexible. The system must be able to transfer data through a platform and
hardware independent approach.
Accessible. The system muse be always accessible, i.e. it has to be always ’on’.
Transparent. The system will function and will adapt to the users needs with-
out any involvement from the user’s side [11].
4 The Benefits
Autonomic computing exists to diminish the coiling need for skilled, IT literal,
human resources and to steer computing into a new age which makes better use
of the potential to assist higher-order thinking and decision making [12]. The
benefits from the new paradigm will not only have immediate effect, but also a
long-term one.
Most importantly, the human involvement in maintaining complex computer
systems will be one of the most immediate effects of autonomic computing in the
IT industry, together with significantly decreased general costs [4]. The vision
for long-term benefits is the ability for organizations and business to collaborate
on complex problem solving with the aid of autonomic computing [6].
All the benefits of autonomic computing, as predicted by Paul Horn in the
IBM manifesto of autonomic computing can be summarized as:
Short-term IT related benefits
– Simplified user experience through a more responsive, real-time system.
– Cost savings - easily scalable.
– Scaled power, storage and costs that optimize usage across both hardware
and software.
– Full use of idle processing power, including home PC’s, through networked
systems.
– Natural language queries allow deeper and more accurate returns.
– Seamless access to multiple file types. Open standards will allow users to
pull data from all potential sources by re-formatting on the fly.
– Stability. High availability. High security system. Fewer system or network
errors due to self-healing [13].

4. Long-term, Higher Order Benefits
– Realize the vision of enablement by shifting available resources to higher-
order business.
– Embedding autonomic capabilities in client or access devices, servers, stor-
age systems, middleware, and the network itself. Constructing autonomic
federated systems.
– Achieving end-to-end service level management.
– Collaboration and global problem-solving. Distributed computing allows for
more immediate sharing of information and processing power to use complex
mathematics to solve problems.
– Massive simulation - weather, medical - complex calculations like protein
folding, which require processors to run 24/7 for as long as a year at a time.
5 The Eight Elements
Being a fairly new paradigm, the current definition of autonomic computing
is definitely not the final one. As the idea matures and research is done on
that topic, the definition might shift but the fundamental eight principles of
autonomic computing must stay constant. Those are:
1. An autonomic computing system needs to ’know itself’ - its components must
also possess a system identity. Since a system can exist at many levels, an
autonomic system will need detailed knowledge of its components, current
status, ultimate capacity, and all connections to other systems to govern
itself. It will need to know the extent of its owned resources, those it can
borrow or lend, and those that can be shared or should be isolated.
2. An autonomic computing system must configure and reconfigure itself under
varying (and in the future, even unpredictable) conditions [14]. System con-
figuration or setup must occur automatically, as well as dynamic adjustments
to that configuration to best handle changing environments [15].
3. An autonomic computing system never settles for the status quo - it always
looks for ways to optimize its workings [11]. It will monitor its constituent
parts and fine-tune work-flow to achieve predetermined system goals.
4. An autonomic computing system must perform something akin to healing
- it must be able to recover from routine and extraordinary events that
might cause some of its parts to malfunction. It must be able to discover
problems or potential problems, then find an alternate way of using resources
or reconfiguring the system to keep functioning smoothly.
5. A virtual world is no less dangerous than the physical one, so an autonomic
computing system must be an expert in self-protection. It must detect, iden-
tify and protect itself against various types of attacks to maintain overall
system security and integrity.
6. An autonomic computing system must know its environment and the context
surrounding its activity, and act accordingly [15]. It will find and generate
rules for how best to interact with neighboring systems. It will tap available

5. resources, even negotiate the use by other systems of its underutilized ele-
ments, changing both itself and its environment in the process, in a word,
adapting [11].
7. An autonomic computing system cannot exist in a hermetic environment
[15]. While independent in its ability to manage itself [16], it must function
in a heterogeneous world and implement open standards, in other words, an
autonomic computing system cannot, by definition, be a proprietary solution.
8. An autonomic computing system will anticipate the optimized resources
needed while keeping its complexity hidden. It must marshal IT resources to
shrink the gap between the business or personal goals of the user, and the
IT implementation necessary to achieve those goals, without involving the
user in that implementation
6 The Challenges
The effort needed for developing and implementing autonomic computing [10] is
intimidating at least, requiring the conversion of experts from multiple technical
and scientific disciplines together with businesses and institutions, which will
focus their knowledge and expertise on the challenge of autonomic computing
[17].
The greatest challenge is the fact that the central focus behind autonomic
computing is the holistic conceptualization of computing. The problem is not
in the hardware which will support autonomic computing, but in creating the
standards and technology which is a necessity for effective system interaction
[18]. Furthermore, the systems should be able to execute business policies and
to heal [13, 19] and protect themselves with no outside human intervention.
This results in redefining the way computer systems are designed as follows
[20, 14]:
– The computing paradigm will change from one based on computational
power to one driven by data.
– The way we measure computing performance will change from processor
speed to the immediacy of the response.
– Individual computers will become less important than more granular and
dispersed computing attributes.
– The economics of computing will evolve to better reflect actual usage - what
IBM calls e-sourcing.
Moreover, the design of the distinctive components of an autonomic system
will have to change and will include [20, 14]:
– Scalable storage and processing power to accommodate the shifting needs of
individual and multiple autonomic systems.
– Transparency in routing and formatting data to variable devices.
– Evolving chip development to better leverage memory.

6. – Improving network monitoring functions to protect security, detect potential
threats and achieve a level of decision-making that allows for the redirection
of key activities or data [12].
– Smarter microprocessors that can detect errors and anticipate failures.
The above lists are just a part of the indications and emerging challenges of
autonomic computing which are yet to be solved [5]. Few advances have been
made on the above challenges in the last decade, however, the primary one
remains, and that is to develop the open standards and interfaces of computing
systems which will start realizing the vision of autonomic computing [6].
7 Academic Focus
The academia as a whole, has dedicated a substantial amount of research on
autonomic computing and related projects. Most of the work is still exploratory
and experimental, however there are few projects which are well underway and
have provided with amazing results [17]. Following are short summaries of three
of the most popular projects on autonomic computing which are developed at
some of the most prestigious universities like Carnegie Mellon.
7.1 Berkeley University of California: Recovery-Oriented
Computing
The Recovery-Oriented Computing (ROC) project is a joint Berkeley/Stan-
ford research project that is investigating novel techniques for building highly-
dependable Internet services. ROC emphasizes recovery from failures rather than
failure-avoidance. This philosophy is motivated by the observation that even the
most robust systems still occasionally encounter failures due to human operator
error, transient or permanent hardware failure, and software anomalies resulting
from software aging.
7.2 Carnegie Mellon University: Self-securing Storage & Devices
Self-securing storage is an exciting new technology for enhancing intrusion sur-
vival by enabling the storage device to safeguard data even when the client
operating system (OS) is compromised. It capitalizes on the fact that storage
servers (whether file servers, disk array controllers, or even IDE disks) run sep-
arate software on separate hardware. This opens the door to server-embedded
security that cannot be disabled by any software (even the OS) running on
client systems. Of course, such servers have a narrow view of system activity,
so they cannot distinguish legitimate users from clever impostors. But, from be-
hind the thin storage interface, a self-securing storage server can actively look
for suspicious behavior, retain an audit log of all storage requests, and prevent
both destruction and undetectable tampering of stored data. The latter goals
are achieved by retaining all versions of all data - instead of over-writing old

7. data when a write command is issued, the storage server simply creates a new
version and keeps both. Together with the audit log, the server-retained versions
represent a complete history of system activity from the storage systems point
of view.
7.3 Georgia Institute of Technology: Qfabric
Distributed applications require end-to-end Quality of Service (QoS) manage-
ment to ensure that 1) such applications achieve their goals in regard to func-
tionality and performance and 2) system resources (processors, networks, disks,
memory, etc.) are shared in a manner that prevents applications from inter-
fering with each other. QoS-awareness of applications is an approach to allow
them to take part in resource management. This happens through interfaces
that allow applications to specify their desired QoS or monitor the achieved
QoS. The approach is to closely integrate applications and resource managers in
the QoS management. This is achieved by tying applications and resource man-
agers through the same event-based control path. In other words, any control
information exchanged between applications via the control path can be moni-
tored by the underlying resource management. On the other hand, all resource
management activities can be monitored by the application. Furthermore, ap-
plication and resource managers can interact freely to ensure optimal resource
scheduling and adaptations.
8 Business Focus
To enable autonomic computing, businesses must be prepared to evolve almost
every aspect of how they conduct business. Current approaches to managing
internal operations, including defining computer and communications systems
between employees and customers, will need to become more fluid, while still
maintaining rigorous standards of privacy and security. These systems will also
need to adapt in order to integrate with external systems outside of an individual
business, and perhaps even with other systems around the world.
Additionally, the broad design and definition of technology systems will ex-
pand, changing interface design, standards, and the translation of business poli-
cies into IT policy. New business models will evolve to account for the changing
economics of computer systems and IT services, making it easier for businesses
to pay only for what they use.
Consider some major challenges faced by organizations embracing new e-
business technologies.
– As a proliferating range of access devices become part of the corporate infras-
tructure, enterprises must transform both their IT systems and the business
processes to connect with employees, customers and suppliers. No longer
must they only manage desktops, workstations and PCs, but also PDAs, cell
phones, pagers, and other network devices [21]. Annual compound growth of
these devices is expected to exceed 38% over the next three years.

8. – Companies must also manage the very products they produce, such as net-
work enabled cars, washing machines, and entertainment systems, as part
of this integrated system, extending the system concept well beyond tradi-
tional corporate boundaries. This demands a reliable infrastructure that can
accommodate rapid growth and the ability to hide system complexity from
its users - the company’s customers, employees and suppliers.
– Emerging Web services standards promise to make delivery of valuable ser-
vices over the Internet possible. In one recent Infoworld survey, close to
70% of respondents said they would be developing Web services strategies
within the year, and roughly the same percentage felt Web Services likely
to emerge as the next business model of the Internet. IT services, in par-
ticular, are a likely candidate for delivery in a utility-like fashion, a trend
called e-sourcing. However, such services cannot become widespread unless
the IT systems become more automated and allow true economies of scale
for e-sourcing providers.
– Customers must also gain enough confidence in this model to turn over
critical business data and processes. It is unlikely they will develop this
confidence if system reliability remains dependent on an inadequate supply
of IT workers.
– The underlying technologies to enable greater automation of complex sys-
tems management [16] are ripe for the innovation. The emergence of XML
and a host of new standards provides just a glimpse of the glue needed to
bind such self-governing systems, and advances in workload management
and software agents promises possible incremental paths to autonomic com-
puting.
9 Conclusion
Is it possible to meet the grand challenge of autonomic computing?
It is, although it will take time and patience. However, it is more likely to
have less automated realizations of the autonomic computing vision long before
the most challenging problems are solved. Doing so will increase the value of this
systems as autonomic computing technology improves and earns greater trust
and acceptance. A vision this grandiose requires the involvement of experts from
many areas of computer science, as well as disciplines which are beyond the tra-
ditional computing boundaries. More likely than not, for the vision to become
a reality, the autonomic computing ecosystem must seek fresh knowledge from
scientists studying nonlinear dynamics and complexity for new theories of emer-
gent phenomena and robustness. Economists and e-commerce researchers must
provide novel ideas and technologies about negotiation and supply webs. Psychol-
ogists and human factors researches will provide insight into new goal-definition
and visualization paradigms, together with ways to help humans develop their
trust in autonomic systems.
As a final thought, it is crucial to bridge the language and cultural divides
among the many disciplines needed for this endeavor and to harness the diversity

9. with the goal of successful and universal approaches to autonomic computing.
Autonomic computing is still a vision, however reality is just around the corner.
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