A practical implementation of 6LoWPAN for metropolitan sized
networks.
Joseph A. Knapp and Nicolas Sornin
Semtech Corporation
Abstract
This paper will illustrate a practical application of 6LoWPAN
networking in a metropolitan sized network at Sub-GHz bands. The
application will be based on off-the-shelf components adapted to a
wireless metropolitan network of 1000s of sensors. Details such as
network capacity and coverage area will be considered. It will be
shown that a software defined radio gateway can enable a star
network topology and eliminate the issues of mesh routing in such a
6LoWPAN network.
Introduction and Problem Statement
The deployment of the internet of things will not be limited to
consumer devices, home networks, or even local area networks.
Municipalities are already seeing the benefits of real time status
of their distributed assets such as lighting, parking meters, and
mobile equipment. Additionally, utility companies have for many
years relied on wireless networks to lower their operational costs
in both urban and rural environments. For both of these markets,
battery powered sensors are mandatory, and battery life in the range
of 15 years is expected.
The ability to leverage off of
standardized IPv6 addressing and IP protocols will enable device
vendors and users of these markets the ability to quickly deploy and
reuse applications built upon portable software libraries.
However, the continued use of early 20th-century radio modulation
technology makes the realization of this metropolitan area network
(MAN) of smart devices extremely difficult.
This paper will illustrate how an off-the-shelf radio transceiver
using modern signal processing techniques, such as spread spectrum
can enable a practical application of a wireless MAN.
Possible Solutions
Mesh Network:
The mesh topology provides a reliable and scalable network.
Generally, each node of a mesh network can act as a relay to enable
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messages to “hop” from one node to another. In this way the nodes
can be placed out of range of the network gateway. However, this
method drains battery power due to its inherent requirement for
every node to forward messages not intended for the listening node,
increasing the amount of data the node must process and transmit.
Additionally, it creates network latency due to the need to “hop” a
message thru several nodes. Lastly, for many service providers the
lack of a predictable battery life eliminates the possibility to use
battery powered sensor nodes in a mesh topology. Specifically, the
node’s current consumption depends on the physical location of the
node relative to other nodes, the number of nodes in the mesh, and
the amount of data to be forwarded as a consequence of other nodes.
Star Network:
This is a simple topology with nodes only able to communicate to
base stations (“gateways”). The star network features are well
described by Mr. Garg, Mr. Saroha, and Mrs. Lochab;
The advantage of this type of network for wireless sensor
networks is in its simplicity and the ability to keep the
remote node’s power consumption to a minimum. It also
allows for low latency communications between the remote
node and the base station. The disadvantage of such a
network is that the base station must be within radio
transmission range of all the individual nodes and is not
as robust as other networks due to its dependency on a
single node to manage the network.i
However, newly available radios from Semtech address the issue of
radio transmission range by providing better link performance,
better
co-channel
interferer
rejection,
multi-frequency
communication, and link rate adaptation due to their use of modern
spread spectrum modulation.
Additionally, by moving the network management from the gateways to
a dedicated network manager controlling all the gateways, we can
provide communication redundancy and easily support roaming sensor
nodes.
Physical Layer Description
What might this new physical layer look like when these radio
improvements are applied to the star network topology previously
mentioned?
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Figure 1
illustrates
the radio portion of
this new star network
with its gateways and
sensor
nodes.
The
gateways
provide
a
link between the radio
medium
and
the
internet in order to
transfer node data to
the final application.
Specifically,
the
gateways forward all
the packets received
on any of their radio
channels to a single
network manager that
will
provide
the
communications
protocol. In this way
the
gateways
are
simple
bridges
translating
between
Figure 1 - Illustration of network
two physical layers.
The achievable performance of the proposed star network with the use
of the new radio technology can be modeled and visualized. In the
following figures the modeled gateways are placed on a regular 500
meter grid and the modeled sensor nodes are randomly dispersed on
the grid at a density of 1000 per square kilometer. The link loss of
each node to each gateway is computed using the well-established
COST-WI (Walsh- Ikegami) model. The model setup simulates a dense
urban environment with
12m high buildings and
gateways placed on lamp
posts of 7m height. One
of the outputs of the
model
is
a
map
indicating the location
of connected and unconnected nodes due to
link attenuation versus
the
maximum
possible
link margin.
Figure 2 represents a
map of the gateways and
nodes when used in a
Figure 2 - GFSK network map with unconnected nodes
classical GFSK system
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at a fixed data rate of 2.4Kbps with a sensitivity of -120dBm and
radiating +14dBm in the 868MHz ISM band.
The model predicts that under the conditions described, more than 6%
of nodes will not be able to communicate with any gateway. As
expected, the model reveals that the unconnected nodes are furthest
from the gateways.
In comparison, Figure 3 illustrates the capabilities of the new radio
systems that provide greater link margins and variable data rates.
The
maximum
radiated
power is unchanged, at
+14dBm. Specifically, in
Figure 3 we have applied
radio
link
margins
varying from 151dB (This
corresponds
to
a
sensitivity of -137dBm at
the minimum data rate) to
136dB
(-125dBm
sensitivity
at
maximum
data
rate
with
+11dBm
radiated).
Consequently,
all the sensor nodes are
able to connect to the
gateways.
Furthermore,
Figure 3 - Spread spectrum network map
each
node
uses
the
highest possible data rate given its link attenuation to the closest
gateway maintaining a 10dB demodulation margin. This 10dB margin is
called the installation margin and is one of the parameters set by
the network manager.
The model provides a few more details regarding
network. At the left
of
Figure 4
is
a
histogram
of
link
losses
between
all
the nodes and
the
gateway providing the
best
link.
Most
nodes’ link loss is
dominated by line of
site loss. However, a
significant
portion
of nodes appear to be
shaded
by
modeled
buildings.
At
the
right of Figure 4 is a
histogram
of
the Figure 4 - Attenuation and Data Rate histograms
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the
new
radio
enumerated data rates used by the nodes in our model.
The model also indicates that 50% of the nodes in our new star
network will be received by two (2) or more gateways. This will
allow the network to have some redundancy should one of our gateways
fail. For safety critical nodes the link rate adaptation layer can
be adjusted so that gateway redundancy is always achieved. This can
be achieved at the expense of a lower data rate for those nodes
(hence
longer
radio
range).
Gateways
implement
a
configurable
radio
front-end
able
to
constantly
monitor
several radio channels
(up
to
8)
and
to
demodulate
simultaneously several
packets
on
several
channels using any of
the
available
data
rates.
This
is
accomplished
with
an
FPGA-based Figure 5 - Number of reachable gateways
radio
system
that
implements the multi-channel multi-modem receiver and transmitter.
The multi-channel SDR enables the nodes to randomly select a new
channel for each transmission. This adds protection against RF
jammers and other RF channel effects that may limit the gateways
ability to receive packets from the sensor nodes without requiring
any prior synchronization between the nodes and the gateways. This
also implies that nodes are free to move throughout the network from
one gateway to another, and that nodes do not need to be associated
to a specific gateway while keeping the advantage and robustness of
frequency hopping.
To further examine the operation of this proposed network, the model
will be applied to a wireless parking monitoring use case. Applying
the same parameters as before there will be 1000 parking sensor
nodes per square kilometer. These parking sensor nodes may want to
report battery voltage, health of the node, mode of operation, etc.,
a few times per day. The nodes will also want to reliably alert the
application when a parking space becomes occupied or free. In
general these devices would want to update their status only when
something has changed. What portion of the network capacity does
this use case require?
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The physical link model previously used can also simulate the
capacity of the network. Assuming that each parking sensor node
needs to send a message every hour, and that each message is at
maximum , 128 octets, the model reveals that a single channel GFSK
system would incur a 3% duty cycle. This means that averaged over a
long period of time the radio channel is used in average 3% of the
time by the application. Clearly there is sufficient capacity, but
this GFSK system also has no redundancy and 6.6% of nodes are not
connected.
Applying the new radio technology, 50% of the nodes are now received
by two or more gateways. Additionally the traffic from nodes to
gateways is now spread over multiple radio channels and on each
channel, multiple data rates. Assuming the SDR system provides four
(4) simultaneous receive channels, the resulting duty cycle becomes
1.7% per channel, with 100% of sensor nodes able to communicate with
the gateways and more than half of the nodes having a redundant
link.
The multiple receptions also enable a very basic localization. By
utilizing the signal strength of the received transmissions by the
multiple gateways, the system can localize a sensor node to within a
quadrant, e.g. North, South, East or West of a specific gateway.
This enables tracking of sensor nodes attached to mobile assets like
portable electronic traffic signs.
Link Layer Description
So far it has been shown how a star network with variable data rates
should have sufficient capacity for upstream status data sent at
random times. However, there may be messages that cannot operate
without guaranteed delivery. By using a single network manager, as
illustrated in figure 1, we can dynamically select the optimal
downstream data path for each node and provide just in time
acknowledgement when required.
Typical Usage:
Most of the time, perhaps 16 hours per day, the parking sensor will
only need to update the end application on its battery health and
affirm that it is still operational. This type of messaging can be
implemented by a simple 6LoWPAN compressed UDP type packet
transmitted to a multicast address assigned to our network.
For every transmission of this status message, the sensor chooses a
random RF channel and performs a channel activity detect of the
wireless medium. Once the medium is free (typically) the node sends
its status and returns to deep sleep.
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This type of fixed interval, fixed length communication in a star
network enables simple battery life estimation that is not possible
with a mesh network topology.
Alternatively, the parking space sensor may need to alert the
application when the parking space becomes occupied or free. These
alert messages indicate a transient state of the parking sensor and
require a reliable delivery of the message to ensure that the end
application has the correct state of the parking space, i.e. free or
occupied.
For this alert message scenario, the sensor selects a random RF
channel to use for its upstream message to the gateway as normal.
The radio of the sensor does a quick channel activity detect and
upon determining the medium to be free, transmits its 6LoWPAN
compressed UDP multicast packet.
As shown earlier, the transmission may actually be received by two
or more gateways. Packets are tagged by each gateway with received
data rate, channel, signal to noise ratio, RSSI, and Time-ofArrival. Both gateways relay their message to the network manager.
The network manager recognizes the duplicate messages received by
the separate gateways and provides one copy of the message to the
application layer, while updating its routing table based on the
received RF information provided by each gateway. In this manner
there is only a transitory association of a sensor node with a
specific gateway based on the last RF channel measurements. The
network manager may also determine that a change in the sensor
node’s data rate or output power is appropriate to optimize network
operation and may append commands to any downstream messages to be
sent to the node.
Meanwhile the node has returned to the sleep state. It will sleep in
a low power state for a predetermined duration before awakening and
listening for an acknowledgment.
Before the 5 seconds from the initial transmission expires, the
application layer has determined that an acknowledgement message is
required. It prepares a response and provides that response to the
network manager with the IPv6 address of the destination node. The
network manager compresses the address to the 6LoWPAN format, and
then appends any commands for the node to the UDP packet provided in
addition to the precise time at which the acknowledgement should be
sent. This concatenated message is sent to the gateway with the best
radio link for the targeted node, along with the requirements for
data rate, channel and output RF power level.
The gateway receives the message with the commands and at the
prescribed time begins transmitting with the requested power and
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data rate on the requested channel. Meanwhile the sensor node will
switch from sleep to listening state and receive the unicast 6LoWPAN
compressed UDP message sent from the application along with any
network manager commands appended to the UDP message.
Should the node awake and not receive an acknowledgement it will
retry the full procedure again after some random back-off.
Network Management:
While it has been shown how rate and power adaptation can be
handled in unicast downstream messages, it may also be desirable to
provide broadcast type messaging to minimize the RF channel
utilization by the gateways. The difficulty in providing broadcast
messaging in this scenario is a consequence of our need to have
battery powered sensor nodes that are normally sleeping. By simply
providing a pre-determined time for downstream broadcasts of
aggregated packets, the network can provide this functionality.
However, to address the large quantities of sensor nodes, the system
must utilize some additional features of the new radio system and
SDR gateways. Specifically, the new radio system provides for
orthogonal data rates. The consequence is that the gateways can
transmit multiple packets simultaneously on a single RF channel. In
this manner the gateways can send multiple high speed downstream
packets to nearby nodes while sending a low speed packet to the
sensor nodes with the greatest link attenuation. Specifically, if
the system uses four different data rates, then 5000 bytes of data
can be sent in just 6.5 seconds, i.e. each node serviced by a
gateway could parse 20 bytes of directed data from the aggregated
packet transmissions while using less than 0.2% of the medium per
hour.
Figure 6 - Illustration of orthogonal variable spreading factor
Conclusion
It has been shown that with the development of long range,
interferer-tolerant advanced modulation radio systems, and with the
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deployment of a single network manager that the disadvantages of a
star network can be overcome.
The practical system described supports many desirable features in a
metropolitan area network including mobile nodes, link rate
adaptation, and a predictable battery life. Unlike a cellular
system, this network does not require any frequency planning and
behaves as a single cell for all nodes. It should also be clear that
the examples illustrated can be applied to other applications such
as AMR, lighting, alarm systems, etc.
It has also been shown that a simple localization service can be
provided by these new radio systems and centralized management. In
fact, the modulation used by these new radio transceivers can
provide nano-second accurate time-of-arrival at the gateways. In the
future, the network manager will be able to use the accuracy of this
timing to accurately pin point the origin of wireless packets.
References
i
Garg, Punet, et al. “Review of Wireless Sensor Networks –
Architecture and Applications.” International Journal of
Computer Science & Management Studies May 2011:35-36.
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