14-08-2013, 02:58 PM
Pervasive Computing: Vision and Challenges
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Abstract
This paper discusses the challenges in computer systems research posed by the emerging field of pervasive
computing. It first examines the relationship of this new field to its predecessors: distributed systems and
mobile computing. It then identifies four new research thrusts: effective use of smart spaces, invisibility,
localized scalability, and masking uneven conditioning. Next, it sketches a couple of hypothetical pervasive
computing scenarios, and uses them to identify key capabilities missing from today’s systems. The paper
closes with a discussion of the research necessary to develop these capabilities.
Introduction
‘The most profound technologies are those that disappear. They
weave themselves into the fabric of everyday life until they are
indistinguishable from it.’’ So began Mark Weiser’s seminal 1991
paper [44] that described his vision of ubiquitous computing, now
also called pervasive computing. The essence of that vision was the
creation of environments saturated with computing and
communication capability, yet gracefully integrated with human
users. When articulated, this was a vision too far ahead of its time
— the hardware technology needed to achieve it simply did not
exist. Not surprisingly, the implementation attempted by Weiser
and his colleagues at Xerox PARC fell short.
Localized Scalability
The third research thrust is localized scalability. As smart spaces
grow in sophistication, the intensity of interactions between a
user’s personal computing space and his surroundings increases.
This has severe bandwidth, energy and distraction implications for
a wireless mobile user. The presence of multiple users will further
complicate this problem. Scalability, in the broadest sense, is thus
a critical problem in pervasive computing. Previous work on
scalability has typically ignored physical distance — a web server
or file server should handle as many clients as possible, regardless
of whether they are located next door or across the country. The
situation is very different in pervasive computing. Here, the
density of interactions has to fall off as one moves away —
otherwise both the user and his computing system will be
overwhelmed by distant interactions that are of little relevance.
Although a mobile user far from home will still generate some
distant interactions with sites relevant to him, the preponderance of
his interactions will be local.
Effective Use of Smart Spaces
The first research thrust is the effective use of smart spaces. A
space may be an enclosed area such as a meeting room or corridor,
or it may be a well-defined open area such as a courtyard or a
quadrangle. By embedding computing infrastructure in building
infrastructure, a smart space brings together two worlds that have
been disjoint until now [16]. The fusion of these worlds enables
sensing and control of one world by the other. A simple example
of this is the automatic adjustment of heating, cooling and lighting
levels in a room based on an occupant’s electronic profile.
Influence in the other direction is also possible — software on a
user’s computer may behave differently depending on where the
user is currently located. Smartness may also extend to individual
objects, whether located in a smart space or not.
User Intent
For proactivity to be effective, it is crucial that a pervasive
computing system track user intent. Otherwise, it will be almost
impossible to determine which system actions will help rather than
hinder the user. For example, suppose a user is viewing video over
a network connection whose bandwidth suddenly drops. Should
the system (a) reduce the fidelity of the video, (b) pause briefly to
find another higher-bandwidth connection, or © advise the user
that the task can no longer be accomplished? The correct choice
will depend on what the user is trying to accomplish.
Why then do these scenarios seem like science fiction rather than
reality today? The answer lies in the fact that the whole is much
greater than the sum of its parts. In other words, the real research
is in the seamless integration of component technologies into a
system like Aura. The difficult problems lie in architecture,
component synthesis and system-level engineering. We elaborate
on some of these problems in the next section.
Today’s systems are poor at capturing and exploiting user intent.
On the one hand are generic applications that have no idea what
the user is attempting to do, and can therefore offer little support
for adaptation and proactivity. On the other hand are applications
that try to anticipate user intent but do so very badly — gimmicks
like the Microsoft ‘‘paperclip’’ are often more annoying than
helpful.
High-level Energy Management
Sophisticated capabilities such as proactivity and self-tuning
increase the energy demand of software on a mobile computer in
one’s personal computing space. At the same time, relentless
pressure to make such computers lighter and more compact places
severe restrictions on battery capacity. There is growing consensus
that advances in battery technology and low-power circuit design
cannot, by themselves, reconcile these opposing constraints — the
higher levels of the system must also be involved [10, 25].
Privacy and Trust
Privacy, already a thorny problem in distributed systems and
mobile computing, is greatly complicated by pervasive computing.
Mechanisms such as location tracking, smart spaces, and use of
surrogates imonitor user actions on an almost continuous basis. As
a user becomes more dependent on a pervasive computing system,
it becomes more knowledgeable about that user’s movements,
behavior patterns and habits. Exploiting this information is critical
to successful proactivity and self-tuning. At the same time, unless
use of this information is strictly controlled, it can be put to a
variety of unsavory uses ranging from targeted spam to blackmail.
Indeed, the potential for serious loss of privacy may deter
knowledgeable users from using a pervasive computing system
Conclusion
Pervasive computing will be a fertile source of challenging
research problems in computer systems for many years to come.
Solving these problems will require us to broaden our discourse on
some topics, and to revisit long-standing design assumptions in
others. We will also have to address research challenges in areas
outside computer systems. These areas include human-computer
interaction (especially multi-modal interactions and human-centric
hardware designs), software agents (with specific relevance to
high-level proactive behavior), and expert systems and artificial
intelligence (particularly in the areas of decision making and
planning). Capabilities from these areas will need to be integrated
with the kinds of computer systems capabilities discussed in this
paper. Pervasive computing will thus be the crucible in which
many disjoint areas of research are fused.