Database Reference
In-Depth Information
number of internet connected devices was a small fraction of this number.
With an increasing number of devices being connected to the internet,
and with each requiring its IP-address (for full peer-to-peer communi-
cation and functionality), the available IP-addresses are in short supply.
As of 2008, the number of internet connected devices exceeded the total
number of people on the planet. Fortunately, the new IPv6 protocol
which is being adopted has 128-bit addressability, and therefore has an
address space of 2
128
. This is likely to solve the addressability bottleneck
being faced by the internet of things phenomenon.
It is clear that from a data centric perspective,
scalability
,
distributed
processing
,and
real time analytics
will be critical for effective enable-
ment. The large number of devices simultaneously producing data in
an automated way will greatly dwarf the information which individu-
als can enter manually. Humans are constrained by time and physical
limits in terms of how much a single human can enter into the sys-
tem manually, and this constraint is unlikely to change very much over
time. On the other hand, the physical limitations on how much data
can be effectively collected from embedded sensor devices have steadily
been increasing with advances in hardware technology. Furthermore,
with increasing numbers of devices which are connected to the internet,
the number of such streams also continue to increase in time. Simply
speaking, automated sensor data is likely to greatly overwhelm the data
which are available from more traditional human-centered sources such
as social media. In fact, it is the trend towards ubiquitous and pervasive
computing, which is the greatest driving force towards
big data analytics
.
Aside from scalability issues, privacy continues to be a challenge for
data collection [40, 58-62, 69, 71, 78, 81, 82, 111]. Since the individual
objects can be tracked, they can also lead to privacy concerns, when
these objects are associated with individuals. A common example in
the case of RFID technology is one in which a tagged object (such as
clothing) is bought by an individual, and then the individual can be
tracked because of the presence of the tag on their person. In cases,
where such information is available on the internet, the individual can
be tracked from almost anywhere, which could lead to unprecedented
violations of privacy.
The material in this chapter is closely related to two other chapters
[8, 9] in this topic corresponding to
social sensing
and
RFID processing
respectively. However, we have devoted a separate chapter to the inter-
net of things, since it is a somewhat separate concept in its own right,
though it is related to the afore-mentioned technologies in the following
ways:
