RPL Router Discovery for Supporting
Energy-Efficient Transmission in Single-hop
6LoWPAN
Wilawan Rukpakavong, Iain Phillips, Lin Guan, George Oikonomou
Department of Computer Science, Loughborough University, Leics, UK
Email: {W.Rukpakavong,I.W.Phillips,L.Guan,G.Oikinomou}@lboro.ac.uk
Abstract—In Wireless Sensor Networks (WSNs), controlling
transmission power is a commonly used technique to extend battery life. This paper describes a novel mechanism using measured
RSS (Received Signal Strength) to calculate optimal transmission
power. This technique works in multipath environments and
with nodes with differing transmission capability. Our technique
achieves automatic configuration employing modifications to RPL
(Routing Protocol for Low-power and lossy networks) router discovery without requiring extra steps or messages. Consequently,
each node can send packets with ideal transmission power, which
will usually be lower than maximum power and will help to
prolong its lifetime. We evaluate the effectiveness of the proposed
scheme, using performance metrics such as energy consumption
and packet loss, on an WSN testbed. Several factors that impact
the RSS, such as antenna, multipath environment, output power
and the node’s capabilities are also investigated. Moreover, two
RSS estimation techniques are evaluated and compared to the
average measured RSS. The experimental results show that
energy consumption is reduced by using the proposed technique.
Index Terms—Wireless Sensor Networks, Energy Consumption, RPL, RSS, Energy-Efficient Transmission, 6LoWPAN, IEEE
802.15.4.
I. I NTRODUCTION
A wireless sensor network (WSN) consists of a large
number of individual nodes employing IPv6 for addressing.
This provides enough address space to integrate the Internet
and WSNs without the need for address translation. However,
it is necessary to reduce the complexity and the header length
of IP because sensor nodes have low speed, low memory,
limited processing and a small frame size at the data link layer:
the Maximum Transfer Unit (MTU) is only 127 bytes. As a
result, the IETF proposed a standard, 6LoWPAN (IPv6 over
Low power Wireless Personal Area Network), which includes
mechanisms that effectively compress IPv6 addresses over
IEEE 802.15.4 [1], [2]. Additionally, the IETF proposed RPL
(IPv6 Routing Protocol for Low-power and lossy networks)
to provide efficient selection of routing paths across a WSN
[3]. A simple 6LoWPAN is connected to the Internet through
a node, called border router. Other nodes may play the role of
router or host, with host also called leaf node. If a node is not
adjacent to the border router, one or more other nodes (known
in this context as routers) will relay messages as appropriate.
The first step for a 6LoWPAN WSN is for its nodes to
discover the neighbouring routers. One of several ways for
router discovery is using a subset of the RPL protocol [3]
which specifies a set of new ICMPv6 (Internet Control Message Protocol version 6) messages to exchange between nodes.
Using RPL, a node has to join a Destination Oriented Directed
Acyclic Graph (DODAG). In the initial step, the RPL root (or
border router) advertises a DODAG Information Object (DIO)
message which includes the graph information for selecting
DODAG parents. After receiving the DIO message, a node
makes a decision to join the graph or not. After joining a
graph, the root becomes the parent of the node. If the node is
configured as a router, it then advertises the DIO message to
its neighbours to form its sub-DODAG. In contrast, it does not
send the DIO message, if the node is a host. There are some
optional steps after choosing the parent node. For supporting
both upward (sensors-to-border router) and downward (border
router-to-sensors) routing, a node sends a DAO (DODAG
Destination Advertisement Object) message to its parent to
inform its presence and reachability. Then the parent may send
a DAO acknowledgement back to that node if an acknowledge
bit is set in the DAO message. After that, that node can send
and receive messages to and from the border router via its
parent. DIO and DAO message exchanges are subsequently
used for route maintenance.
Unlike nodes in traditional IP networks, sensor nodes have
limited battery power. Therefore, reducing energy consumption is an important issue in prolonging the lifetime of a WSN.
Transmission power control is one of the techniques used to
achieve this. The ideal power level for transmission is the
minimum required for successful reception by the intended
destination. This paper uses an equation-based method to
calculate the minimal energy for transmission. Moreover, this
technique is used with a modification to RPL that does not
require additional steps in the protocol. This technique can
be used for optimal transmission power estimation covering
factors that affect delivery such as antenna, transmission
capability and the multipath environment.
This paper presents the related work in the next section.
Section III describes the system design including the investigation of RSS impact factors, the comparison of two RSS
estimation techniques and the experimental verification over a
single-hop 6LoWPAN. In section IV, the results and discussion
are presented. Finally, the conclusion and plans of future work
are proposed.
II. R ELATED W ORK
In WSNs, energy is the scarcest resource because all nodes
need to operate unattended for a long periods of time. Communication is the part which consumes the highest of energy.
Therefore, many researchers focus on minimising communication energy consumption. Transmission power adjustment
is a commonly used technique. One direction to find the
minimal transmission power is based on the distance between
the sender and receiver nodes [4], [5]. For this method,
the research works focused on path loss model which is a
function of distance. However, the distances between nodes
are difficult to determine, for examples, each node may need
a pre-configured position or an attached positioning device
like GPS (Global Positioning System). Moreover, in reality,
it is not always true that the path loss increases if distance
increases for some cases, such as in multipath environment [6],
[7]. Therefore, distance alone is inappropriate for transmission
power estimation.
Another direction proposed the discovery technique for
finding the minimal transmission power [6], [8]. For this
direction, each node performs neighbour discovery by broadcasting messages with different transmission power levels. All
neighbouring nodes that receive these broadcast messages,
reply to the sender. Then, the sender can record the minimal
transmission power for each neighbour. However, using this
technique prolongs discovery time, since every node has to
broadcast using all transmission power levels during the discovery phase. As a result, the discovery process exhibits high
energy consumption. Furthermore, if the process of neighbour
discovery finishes late, it will cause the delay start of other
processes.
Our previous work [7] proposed the basic idea of sending only one message during discovery all neighbours for
estimating minimal transmission power. In this paper, however, we focus on 6LoWPAN RPL. A modification of RPL
router discovery is proposed which does not affect the power
consumption and does not require more time spent in the
discovery process. Moreover, several impact factors for RSS
estimation are investigated.
III. S YSTEM D ESIGN
The relation between transmission power and received signal strength (RSS) in decibels can be described as [9]:
RSS = PT − LP
(1)
where PT and LP are power used for transmission and path
loss respectively. RSSI (Received Signal Strength Indicator)
is a measured and estimated value for RSS provided by
modern wireless radio transceivers. For example, for the Texas
Instruments CC2420 RF hardware [10], the RSSI value is
averaged over 8 symbol periods (128 µs) and RSSI accuracy
is specified as ± 6 dB. However, many studies assume that
RSSI can represent RSS with a 100% accuracy. The RSS-RSSI
mapping is shown in (2).
RSS = RSSI + N F
(2)
where NF is the noise floor and usually constant, for example,
CC2420 reports as -45 dBm. If Pmax denotes the maximum
transmission power, Px as the transmission power X decibels,
then (1) is transformed to (3) and (4) by replacing PT with
Pmax and Px . Thus, RSSmax and RSSx are the received
power at the destination for transmission with Pmax and Px ,
respectively.
RSSmax = Pmax − LP
(3)
RSSx = Px − LP
(4)
If LP is the same for all transmission powers, the new
equation (5) is written by combining (3) and (4) as:
RSSx = Px + RSSmax − Pmax
(5)
If RSSx is replaced by the receiver sensitivity (RSSmin ), Px
will be the minimum power required for transmission (Pmin )
which can be calculated as:
Pmin = RSSmin − RSSmax + Pmax
(6)
Values for both receiver sensitivity (RSSmin ) and maximum
transmission power (Pmax ) can be obtained from sensor node
data sheet, e.g., for CC2431 these values are -92 dBm and
0 dBm, respectively [11]. The measured RSSmax can be
obtained from RSSI later during the discovery process.
To embed the idea to the RPL router discovery process, the
details within a few steps are modified. It is assumed that RPL
is configured to support both upward and downward traffic and
that the DAO acknowledgement is always requested. While a
node sends a DAO message to its parent, it uses the maximum
transmission power. In receiving a DAO message, the parent
also reads the measured RSSI value of that DAO message
and converts to RSS (based on equation 2). This measured
RSS (RSSmax ) is attached by placing in the reserved byte of
DAOack message. Therefore, no extra byte is required for the
acknowledgement message. Then, the node can calculate the
minimal power for transmission of any packets to the parent
later by using equation (6).
A. Antenna, Path Loss (LP ) and Multipath Effect
To investigate the impact of antenna on RSS, we set up
an experiment where a sender sends 100 UDP-packets with
maximum transmission power with and without an attached
antenna. These experiments use Sensinode N740 NanoSensors,
equipped with a CC2431 System-on-Chip, an IEEE 802.15.4
compliant 2.4 GHz RF transceiver and λ/2-dipole antennas.
Free space path loss for λ/2-dipole antenna in decibels can be
calculated as [9]:
2
LP = 20 log(λ) + 20 log(d) − 10 log(GT HT2 GR HR
/π 2 ) (7)
where λ and d are the wavelength (m) and distance between
sender and receiver (m), GT and HT are the antenna gain
(dBm) and length (m) of the transmitting antenna, GR and HR
are the antenna gain and length of the receiving antenna. The
experiments operate at channel 24. Therefore, the frequency
of this channel is 2.47 GHz with approximately 12.15 cm
Transmission Power (dBm)
0
-0.4 -2.7 -4.0 -5.7 -7.9 -10.8 -15.4 -18.6 -25.2
20
RSS (dBm)
MeasuredRSSw
40
CalculatedRSSw(EQ1)
CalculatedRSSw(EQ5)
60
MeasuredRSSwo
CalculatedRSSwo(EQ1)
80
100
CalculatedRSSwo(EQ5)
Receiver Sensitivity
120
(a)
0
Fig. 1. Comparison between Measured RSSmax and Calculated RSSmax
for With- and Without-Antenna Experiments
Transmission Power (dBm)
-0.4 -2.7 -4.0 -5.7 -7.9 -10.8 -15.4 -18.6 -25.2
20
MeasuredRSSw
Receiver
direct signal
indirect signal
1m
2m
RSS (dBm)
Sender
40
CalculatedRSSw(EQ1)
CalculatedRSSw(EQ5)
60
MeasuredRSSwo
CalculatedRSSwo(EQ1)
80
CalculatedRSSwo(EQ5)
Fig. 2.
Signal Reflection
100
Receiver Sensitivity
120
wavelength (λ). The required length of λ/2-dipole antenna for
this wavelength is around 6.1 cm with 1.64 dBm antenna gain
[9], [12]. Since the same antennas are used for the sender
and receiver, GT and GR are 1.64 dBm. For without-antenna,
the length of transmitting antenna for calculation is around
1.22 mm. Fig 1 shows the comparison between calculated
values based on equation (1) and the average measured values
of RSS for with-antenna experiment (RSSw ) and withoutantenna experiment (RSSwo ). Results in Fig 1 show that
signal strength increases due to antenna capacity. However,
this does not affect RSS estimation. Calculated RSS values
are close to (±4) the measured RSS values except at the
distance of 2 metres. Generally, RSS decreases as the distance
increases. However, the average measured RSS values at a
distance of 2 metres are higher than those at a distance of
1 metre for both experiments with and without-antenna. In
this case, path loss is different at the distance of 2 metres
due to multipath signals which are reflected by objects (i.e., a
table) as shown in Fig 2. Depending on phase, indirect path
signals can amplify the direct signal as well as weaken it.
At a 2 metre distance, indirect signals arrive in phase with
the direct one, increasing its amplitude and making it appear
stronger on the receiving end. Even though signal strength is
high, it exhibits low quality and high fluctuations. Another
reason for signal fluctuation is noise and interfering signals.
The amount of interference will degrade the signal strength,
especially for the weak signals. This effect is inconsistent,
which is the reason why a slight increase of fluctuation
occurs at distances of 8, 10 and16 metres for with-antenna
experiment. For without-antenna experiment, instead of signal
strength degrading or more signal fluctuations, loss rates of
13% and 30% are encountered at 8 and 10 metre the distances
because the average signal strength values are close to the
receiver sensitivity.
(b)
Fig. 3. Comparison between Measured and Calculated RSS by Equation (1)
and Equation (5) for With- and Without-Antenna Experiment at Distances of
2 (a) and 8 (b) Metres
B. Transmission Power
To investigate the relationship between RSS and transmission power, the sender sends out 100 UDP-packets with different transmission powers. By using path loss in equation (7),
RSS can be estimated for each transmission power based on
equation (1). Instead of using path loss value, RSS for each
transmission power can also be calculated by using an average
measured RSSmax at each distance as in (5). Fig 3 illustrates
the comparison between average measured RSS and calculated
RSS based on (1) and (5) for both with- and without-antenna
experiments. Regarding to the results in Fig 3, estimated RSS
values based on equation (1) at the distance of 2 metres are
much different from mean measured values owing to multipath
reflection effect as described in the previous subsection, while
estimated RSS values based on equation (5) are still close
to mean measured values. Normally, calculated RSS values
based on both equations (1) and (5) are within ±4 dBm of
the mean measured values if the calculated values are higher
than the receiver sensitivity (-90 dBm). It can be concluded
that these estimated RSS values are acceptable because their
accuracy is still in the range of the specified RSSI accuracy
(±6 dBm) from the hardware data sheet (Note that CC2430/31
data sheet [11], [12] does not provide any details about the
RSSI accuracy, therefore it is assumed that the CC2431 has a
similar RSSI accuracy as the CC2420). However, if calculated
values are lower than the sensitivity threshold value, measured
values are unpredictable because they include much noise or
interference due to very weak signals.
(
Transmission Power (dBm)
)
E. Testbed Implementation
The testbed is designed to test the effectiveness of the
proposed idea. This testbed consists of 5 N740 Nanosensors running Loughborough University Contiki Sensinode/CC2430 [13]. One of 5 nodes is configured as the border
router (the RPL root) while the remaining 4 nodes operate
as hosts that joined a routing tree using ContikiRPL. The
experiments are conducted indoors. All nodes are static and 4
hosts are placed at the distances of 1, 2, 4, 8 and 16 metres
from the border router for with-antenna experiment, and 1,
2, 4, 8 and 10 metres for without-antenna experiment. To
aviod collision, each node starts at different times. However,
collision might occur due to RPL message exchanges for route
establishment and maintenance. The experiment period is 10
minutes for each distance and these experiments are repeated
5 times. Every two seconds, all hosts send a UDP-message
by using the minimal output power as in equation (6). After
router discovery process, a few more DAO messages, e.g.,
4-5 messages, have been exchanged between a host and the
router for route maintenance during the experiment period, the
average of RSS value is simply calculated as:
0
-0.4 -2.7 -4.0 -5.7 -7.9 -10.8 -15.4 -18.6 -25.2
20
20
RSSS(dBm)
40
MeasuredRSSwo
60
CalculatedRSSwo(EQ1)
CalculatedRSSwo(EQ5)
80
100
Receiver Sensitivity
120
(a)
0
Transmission Power (dBm)
-0.4 -2.7 -4.0 -5.7 -7.9 -10.8 -15.4 -18.6 -25.2
20
RSSS(dBm)
40
40
MeasuredRSSwo
60
CalculatedRSSwo(EQ1)
CalculatedRSSwo(EQ5)
80
100
Receiver Sensitivity
120
120
(b)
RSS = 0.75 ∗ RSSc + 0.25 ∗ RSSc
Fig. 4. Comparison between Measured and Calculated RSS by Equation (1)
and Equation (5) at Distance of 1 Metre for Without-Antenna Experiment of
Node 1 (a) and Node 2 (b)
C. Transmission Capability
To investigate the effect of node’s transmission capability,
two nodes (Node 1 and Node 2) without-antenna send 100
UDP-packets with different transmission powers at the distance of 1 metre. As in Fig 4, all estimated values by equation (1) of Node 1 are a bit higher than the average measured
values, while they are a bit lower for Node 2. Therefore, it can
be concluded that the same path loss model cannot be used
for all sensors even they have the same hardware. It needs to
be adjusted depending on each node’s capability. However, by
using equation (5), the estimated values are still close to the
mean of the measured values for both Nodes 1 and 2.
D. Energy Consumption for Sending a Packet
To find the energy consumption in joule, the formula is:
E =V ∗I ∗T
(8)
where V is the voltage in the node, I is the current consumption, and T is the time spent for running.Then, the formula
for calculating energy consumption for sending a packet is:
ET X = V ∗ IT X ∗ (L/Trate )
(9)
where IT X is the current transmission consumption cost for
the specific power level, L is the packet length, and Trate
is the transmission rate of the node. In this testbed, 3 volts
is used as the static energy source, the speed of transmission
rate is 250 Kbps, and the packet length is 50 bytes. Therefore,
if the IT X is reduced, the transmission energy consumption
will be reduced.
(10)
where RSSc and RSSc are the current average RSSmax
and the current attached RSSmax in the DAOack messages.
The minimal transmission power is computed and adjusted to
the closest power level which is greater than or equal to the
computed one. Nine transmission power levels are used in the
experiments: -0.4, -2.7, -4.0, -5.7, -7.9, -10.8, -15.4, -18.6 and
-25.2 dBm. The current consumption of those levels are 26.9,
23.6, 22.8, 21.9, 21.0, 20.1, 19.2, 18.8, 18.3 mA, respectively
[12]. Although the CC2431 data sheet [11] indicates that the
receiver sensitivity is -92 dBm, it is observed that the minimum
signal strength should be around -90 dBm for good receiving.
Therefore, this testbed uses -90 dBm instead of -92 dBm as
the minimum signal strength threshold at the receiver.
IV. R ESULTS AND D ISCUSSION
The results of four nodes are almost the same because
node’s transmission capability does not affect our transmission
power calculation. Tables I and II are the results of one
observed node. The differences between average measured
RSSmax used in section III-B and average measured RSSmax
attached in DAOack are -4 to +2 dBm for with-antenna
experiment and +2 dBm for without-antenna experiment. It
might be due to only few DAO message exchanges (i.e., 4-5),
RSSI-estimation accuracy by hardware, or signal fluctuation.
Comparing to sending with the maximum transmission power,
sending with calculated transmission power will decrease
transmission energy consumption, i.e., 32% for with-antenna
and 12-30% for without-antenna. However, more signal fluctuation, especially when the signal strength falls near the receiver
sensitivity, significantly affects the efficiency of calculating
power for transmission. If the higher RSSmax has been found
instead of the lower one during DAO message exchanges, the
calculated transmission power will be lower and result in lower
TABLE I
E XPERIMENTAL R ESULT W ITH -A NTENNA
Distance(m)
RSSmax
RSSmax (from DAOack )
Calculated TX Power
Used TX Power
Current (mA)
Energy Reduce(%)
Packet Loss (%)
1
2
4
8
16
-37
-40
-50.4
-25.2
18.3
32
0
-32
-32
-58.4
-25.2
18.3
32
0
-47
-45
-45.4
-25.2
18.3
32
0
-55
-59
-31.4
-25.2
18.3
32
0
-63
-64
-26.4
-25.2
18.3
32
0
TABLE II
E XPERIMENTAL R ESULT W ITHOUT-A NTENNA
Distance(m)
RSSmax
RSSmax (from DAOack )
Calculated TX Power
Used TX Power
Current(mA)
Energy Reduce(%)
Packet Loss (%)
1
2
4
8
10
-77
-76
-14.4
-10.8
20.1
25
0
-66
-67
-23.4
-18.6
18.8
30
0
-82
-81
-9.4
-7.9
21.0
22
0
-85
-84
-6.4
-5.7
21.9
19
+7
-89
-87
-3.4
-2.7
23.6
12
+3
energy consumption. On the other hand, low transmission
power might lead to a weak signal which is near the receiver
sensitivity and might cause packet loss. That is why packet
losses increase 3-7% at the distances of 8 and 10 metres for
without-antenna experiment. However, packet losses still can
occur at these two distances even if all packets are sent with the
maximum transmission power and they can be caused by many
other reasons, such as absorption fading for long-distance,
hardware problems, line of sight obstruction and collision.
This makes it difficult to predict or analyse packet losses,
especially in sensor network. To avoid packet losses caused
by power adjustment, equation (6) should be adjusted to make
sure that the estimated signal strength is always higher than
the receiver sensitivity plus the accuracy in RSS estimation.
Therefore, it is necessary to include some factors, such as the
accuracy of hardware measurement and the maximum RSSI
variation due to noise and interference in estimating minimum
transmission power. In the worst-case, the transmission energy
consumption for sending with calculated power will be equal
to power consumption for sending with the maximum power.
V. C ONCLUSIONS AND F UTURE W ORK
The RSS value for each transmission power level can
be estimated by using either path loss model or measured
RSSmax value. To estimate RSS, four impact factors on
received signal strength which are multipath, antenna, transmission powers and node capability are analysed. By using
a path loss model as in (1), antenna and transmission power
levels have no effect on RSS estimation, while node capability and multipath do. However, none of these four factors
have an effect on RSS estimation when using equation (5).
Experimental results show that RSS estimation by using the
path loss model may need to be adjusted for each node’s
capabilities and multipath environments which are normally
found in real world situations. Moreover, it requires many
complex factors to compute, such as the distance between
sender and receiver, antenna length and gain, radio frequency
and so on. In contrast, another equation, as proposed in our
paper, uses only the measured RSSmax value for calculation.
This measured RSSmax can be automatically obtained during
router discovery in a 6LoWPAN network. To achieve the
target, exchanging DAO messages of the RPL router discovery
process has been modified for providing RSS values without
adding new steps or messages. The average of those RSS
values is then used to estimate minimum required transmission
power. According to our results, the accuracy of this equation
is acceptable for multipath environments and different node
transmission capability. However, if the RSS signal is very
weak and heavily fluctuating, it significantly affects in finding
the optimal power transmission and may raise the packet loss
rate. Therefore, the proposed equation should be adjusted by
adding the accuracy in RSS estimation and signal variations
for avoiding packet losses.
This paper focuses only on a single-hop 6LoWPAN. Next
step is extending to multi-hop environment by adding transmission power as one of routing metrics for RPL path selection. Moreover, other performance metrics such as delay and
throughput will be investigated.
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