ASYNCHRONOUS FORMATION OF NON-HIERARCHICAL BLUETOOTH
SCATTERNETS
Paal Engelstad, Tore E. Jonvik, Do Van Thanh,
University of Oslo (UniK) / Telenor R&D, 1331 Fornebu, Norway
{Paal.Engelstad, tore-erling.jonvik, thanh-van.do}@telenor.com
ABSTRACT
A Bluetooth ad-hoc network consists of Bluetooth
devices interconnected into piconets and piconets
interconnected into scatternets. The specification has not
yet addressed the issue of algorithms for scatternet
formation. Some algorithms have been proposed, but they
are either synchronous, they work only with strongly
connected topologies, or they are master-slave based and
hierarchical of nature. Instead, we propose two alternative
algorithms - one slave-slave-based and one master-slave
based - as a new non-hierarchical approach to
asynchronous scatternet formation on weakly underlying
topologies. Simulations demonstrate that the nonhierarchical asynchronous algorithms form scatternet
structures that are more efficient than those formed by
existing hierarchical proposals. Furthermore, the slaveslave-based algorithm forms scatternet structures that are
considerably more efficient than structures based on
master-slave bridges.
1.
INTRODUCTION
Bluetooth is an open specification for short-range
wireless communication, and is designed for imposing low
battery drain on the wireless terminal. Originally, it was
intended for cable replacement between two devices, but the
specification has gradually been extended to meet the
demand for ad-hoc networking [1]. Due to low
manufacturing costs (down to 5 USD/ Bluetooth chip)
Bluetooth based networks are expected to be the preferred
solution to build inexpensive ad-hoc networks, including
Personal Area Networks (PANs).
A Bluetooth ad-hoc network consists of Bluetooth
devices interconnected into piconets and piconets
interconnected into scatternets. The Bluetooth specification
outlines how two Bluetooth devices interconnect and form a
piconet. When two devices come into each other’s
communication range, they detect each other by first going
through an INQUIRY phase. The following PAGE phase
allows the devices to start establishing a connection. One of
the devices obtains the role of a master, while the other
becomes a slave. Each piconet consists of one master, and
maximum 255 slaves. However, the number of active slaves
in a piconet cannot exceed seven.
Although a device can be master of maximum one
piconet, it can be slave in a number of different piconets, or
master in one piconet and slave in others. Hence, two
piconets can be interconnected if one piconet master is also
slave of the other piconet (i.e. as a master-slave bridge), or
if one device is slave of both piconets (i.e. as a slave-slave
bridge).
No convincing algorithm exists for scatternet
formation, and it is an issue not yet addressed by the
Bluetooth specification. Scatternet formation algorithms
should be based on the following two basic criteria:
1. Weakly connected underlying topologies: A realistic
scatternet formation algorithm should not assume a
strongly connected underlying topology where each
node may connect to any other node in the scatternet.
Instead, the algorithm should work even when there
might be at least two nodes in the same scatternet that
are out of each other’s radio range.
2. Asynchronous scatternet formation: An algorithm
should not mandate that all nodes start forming the
scatternet at the same time (e.g. in terms of an
algorithm comprising several distinct phases). Such
synchronous formations would probably be difficult to
co-ordinate in real usage scenarios. Instead, Bluetooth
devices should be able to enter or leave the scatternet
one by one and at any time. In these events, topology
changes should be handled locally and not propagated
throughout the scatternet.
A number of algorithms have been proposed, including
Bluetooth Topology Construction Protocol (BTCP) [2],
Bluetrees [3], Bluenets [4], LMS [5] and Tree Scatternet
Formation (TSF) [6]. Unfortunately, all of them, except
TSF, are synchronous algorithms or assume strongly
connected underlying topologies. Furthermore, they are
mainly based on using master-slave bridges to form
hierarchical structures.
In this paper, however, we show that non-hierarchical
scatternets are more efficient. Furthermore, non-hierarchical
scatternets open up for structures that are meshed by using
slave-slave-bridges to interconnect the piconets. Indeed,
many researchers, including Bhagwat and Rao [7], argue
that bridges of the master-slave type is wasteful because all
communication in a piconet mastered by the bridge will be
suspended while the master-slave is in the slave role.
The objective of our work was therefore to develop
non-hierarchical and asynchronous scatternet formation
schemes based entirely on master-slave bridges and on
http://folk.uio.no/paalee/
slave-slave-bridges, and compare them with existing
hierarchical master-slave based algorithms. It was natural to
compare our new schemes with TSF, since this is the only
existing proposal that meets the aforementioned criteria.
2.
FRAMEWORK
In addition to being asynchronous and to
accommodating weakly connected device topologies,
algorithms should be designed by a number of principles
targeted at enhancing the efficiency of the resulting
scatternet [2, 4]:
a.
b.
c.
Minimal Piconet Overlap: Two piconets should be
connected by at most one bridge node.
Minimal Bridge Degree: A bridge node should
participate in at most two piconets, i.e. each slaveslave bridge is slave of exactly two masters, while
each master-slave bridge is slave of exactly one other
master or master-slave.
Piconet Size: The algorithm should limit (and
possibly optimize) the size of piconets, i.e. the
number of slaves assigned to one master. Bluetooth
does not allow more than seven slaves per master.
Based on these assumptions and design principles, we
developed the role-state diagram depicted in Figure 1,
which describes how regular nodes participate in scatternet
formation.
cannot connect to more nodes, as was stated by the Piconet
Size design principle above. Hence, interconnections of
nodes result in transitions along the right-directed arrows of
Figure 1. When a node disconnects (e.g. it moves or shuts
down) the transitions go in reverse, i.e. along the leftdirected arrows of Figure 1.
A role-transition matrix can be used to describe state
transitions in the role-state diagram. The role-transition
matrix in Figure 2, for example, describes the transitions of
the TSF algorithm.
Figure 2: Role-transition matrix for TSF, which generates only ms-bridges
(i.e. no ss-bridges). For simplicity, we have only showed the roletransitions for nodes that interconnects (i.e. represented by the rightdirected arrows in Figure 1.)
TSF allows a free node (F) to connect to other free
nodes as shown in role-transition 1. Furthermore, according
to role-transitions 2, 5, 6 and 21 of Figure 2, a free node is
also allowed to connect to a leaf node (i.e. a slave S) or an
intermediate node (i.e. a master-slave bridge ms) of an
established scatternet tree. The free node then becomes a
new leaf node. If it connects through a leaf node, this node
turns into an intermediate node as shown in role-transition 2
and 6. Furthermore, two scatternet trees can combine into
one scatternet tree only by allowing tree-roots (which are
the only masters in the scatternet forest) to interconnect.
When two roots connect, one remains the root of the
combined tree (i.e. a master M), while the other becomes an
intermediate node (i.e. a master-slave bridge). This is
handled by role-transition 13 (Figure 2).
3.
Figure 1: Role-state diagram for scatternet formation. For right-directed
arrows, x represents the role of the node connected to, i.e. x∈{F, M, S, ms}.
For left-directed arrows, x represents the role of the node that disconnects.
At some point in time every device starts out as a free
node F (Figure 1). When it eventually encounters and
connects to another device it becomes either master (i.e. in
role-state M) or slave (i.e. in role-state S) of the new
connection. When a slave or master connects to a node of
another piconet, it may obtain an additional slave-role or
master-role and become an ss- or ms-bridge between the
two piconets. The Minimal Bridge Degree design principle
prohibits that a node obtains more than two roles. When a
Master or master-slave has connected to seven slaves, it
becomes filled (denoted as M' and ms', respectively) and
http://www.unik.no/personer/paalee
TWO ALTERNATIVE NON-HIERARCHICAL
ASYNCHRONOUS ALGORITHMS
3.1. Master-slave-based Scatternet Formation (MSF)
If one is not bound to the hierarchical approach, one
may let a master (or a root in a TSF scatternet) not only
connect to another master (or root), but also connect to free
nodes, slaves or master-slave bridges. Hence, the resulting
scatternet will not be hierarchical, but highly meshed.
We constructed a non-hierarchical master-slave-based
scatternet formation algorithm by allowing such
connections. To derive non-hierarchical scatternets that are
comparable to those of TSF, we mandated that these
connections never produce slave-slave bridges.
Furthermore, by disallowing connections between
masters, we paved the way for a simple and efficient link
formation scheme (Figure 3). The resulting algorithm is
hereafter referred to as the Master-slave-based Scatternet
Formation algorithm (MSF).
may connect to other nodes as a master, i.e. as a result
of an INQUIRY. Hence, the master-slave (ms) in
Figure 3 has an outgoing arrow.
The role-transition diagram of MSF has been omitted due to
space limitations.
Figure 3. Link formation scheme for MSF. An outgoing arrow denotes that
the type of node may perform INQUIRY, while an incoming arrow denotes
that the type of node may perform INQUIRY-SCAN. Connection setup is
possible by matching incoming and outgoing arrows. (Link connection for
ss-nodes has been included for completeness, although ss-bridges are not
anticipated to be present in a scatternet formed by MSF.)
An outgoing arrow from a node in Figure 3 illustrates a
node that may perform INQUIRY while an incoming arrow
to a node illustrates a node that may perform INQUIRYSCAN. All nodes use the same IAC, e.g. the General
Inquiry Access Code (GIAC) [1]. Hence, a connection is
possible by matching an outgoing arrow (INQUIRY) in
Figure 3, with any other incoming arrow (INQUIRYSCAN).
MSF is realized by mandating - in line with the original
Bluetooth specification - that a node that connects from the
INQUIRY search state becomes the master of the
connection, while a node that connects from the INQUIRYSCAN search state becomes the slave.
The connection setup scheme is derived by the
following arguments:
1.
2.
3.
4.
5.
Free nodes (F) should be able to connect to scatternet
nodes (i.e. slaves, masters and/or master-slaves) as well
as to each other. Hence, free nodes must alternate
between INQUIRY and INQUIRY-SCAN. This is
illustrated in Figure 3 by both an outgoing and an
incoming arrow.
Due to the Maximum Bridge Degree design principle,
slave-slaves, if any, cannot connect to other nodes.
Similarly, masters and master-slaves filled with seven
slaved cannot connect to other nodes. Hence, the ss-,
M'-, and ms'- nodes in Figure 3 has neither an outgoing
nor an incoming arrow.
In a scatternet without ss-bridges, slaves cannot obtain
another slave-role of a connection. However, it may
obtain a master-role (i.e. connect by INQUIRY), and
become a master-slave. This is illustrated in Figure 3
by outgoing arrows pointing out from the slave (S).
In a scatternet generating ms-bridges, masters should
obtain another slave-role when connecting to other
nodes (i.e. by connecting in INQUIRY-SCAN), and
become a master-slave as a result of connection setup.
Figure 3 illustrates this by incoming arrows pointing
towards the master (M).
Due to the Maximum Bridge Degree design principle,
master-slaves cannot obtain another slave-role, but they
3.2. Slave-slave-based Scatternet Formation (SSF)
It was natural to develop also a slave-slave-based
algorithm with nearly the same capabilities as TSF and
MSF. Hence, we constructed an algorithm, which in
contrast to the TSF and MSF algorithms never produces
master-slave bridges. This restriction means that unlike for
MSF, masters have no way of connecting to other masters
or master-slaves, but may connect to slaves. In this case, the
connected master remains a master, while the slave
connected to becomes a slave-slave. The resulting algorithm
is hereafter referred to as the Slave-slave-based Scatternet
Formation algorithm (SSF).
The link formation scheme for SSF (Figure 4) is similar
to the scheme of MSF described above. Hence, a node that
connects from the INQUIRY search state becomes the
master of the connection, while a node that connects from
the INQUIRY-SCAN search state becomes the slave.
Figure 4. The link formation scheme of SSF. An outgoing arrow pointing
from a role-state means that a node in this role-state may enter the
INQUIRY search state. An incoming arrow, on the other hand, means that
it may enter the INQUIRY-SCAN search state. Link formation is possible
by matching incoming and outgoing arrows. (Link formation for ms-nodes
has been included for completeness, although ms-bridges are not
anticipated to be present in a scatternet formed by SSF.)
The link formation scheme for SSF is derived by
similar arguments as for MSF, except:
3.
4.
In a scatternet generating ss-bridges, slaves should
obtain another slave-role when connecting to other
nodes (i.e. by connecting in INQUIRY-SCAN), and
hence become a slave-slave as a result of the
formation of a new link. Figure 4 illustrates this by
incoming arrows pointing towards the slave (S).
In a scatternet without ms-bridges, a master cannot
obtain another slave-role as a result of formation of a
link to another node. However, it may remain a master
of the new connection (i.e. connect by INQUIRY).
Figure 4 illustrates this by outgoing arrows pointing
out from the Master (M).
5.
Due to the Minimal Bridge Degree design principle, a
master-slave, if any, cannot obtain another slave-role,
but it may connect to other nodes as a master, i.e. as a
result of an INQUIRY. Hence, the master-slave (ms)
in Figure 4 has an outgoing arrow. For completeness,
we have shown master-slaves in Figure 4, although a
scatternet formed only by SSF, will not contain any
master-slave bridges.
The role-transition diagram of SSF has been omitted due to
space limitations.
4.
node in the same scatternet, the less is the communication
session’s consumption of network bandwidth and the less is
the delay imposed on the session. Furthermore, fewer hops
on average mean a more meshed network with lower
probability that communicating pairs of nodes communicate
over the same node, i.e. an indication that communication is
spread more evenly throughout the network. Hence, the
average shortest path (ASP) represents a way to assess
scatternet topology with respect to communication
efficiency [4].
The ASP-ratio is defined as the ASP of a scatternet
relative to theoretical minimal limit ASP0:
EVALUATION OF FORMATION ALGORITHMS
4.1. Sets of evaluation criteria
The effectiveness of a specific scatternet formation
scheme comprises two parts. The first part is an assessment
of how efficient the scatternet formation algorithm is in
terms of overhead and delay (i.e. during the process of
scatternet formation). Our proposed schemes do not require
any reconfigurations or coordination throughout the
scatternet. Instead, they are straightforward - and very
efficient - unit-time schemes where overhead and delay are
of little importance.
The second part relates to the efficiency of the
operation of scatternets formed by the algorithm, (i.e. after
and as a result of the topology created by the scatternet
formation process). For the latter part, we have developed
evaluation metrics to assess the topology formed by any
scatternet formation algorithm. We present these evaluation
criteria in the following sub-sections.
4.2. Number of disconnected scatternets (Connectivityratio)
Since the purpose of scatternet formation is to ensure
connectivity for communication between devices, an overall
goal is to maximize connectivity. Thus, an algorithm should
interconnect a given set of nodes into as few N disconnected
scatternets as possible. It is evident that the theoretical
lower limit, N0, of the number of disconnected scatternets
formed by any algorithm, is found by traversing the
visibility graph, as defined in [4], instead of traversing the
links formed by the scatternet algorithm. Hence, the
connectivity-ratio, rconn, defined as
rconn = N/N0
(1)
gives a good measure of the overall connectivity provided
by the scatternet formation algorithm.
4.3. Average Shortest Path (ASP-ratio)
Apart from ensuring connectivity, scatternet formation
algorithm should also ensure efficient communication
between devices within the formed scatternets. The fewer
hops a node must traverse to communicate with another
rasp = ASP/ASP0
(2)
ASP0 is found by traversing the links of the visibility graph
between the scatternet nodes, instead of the links formed by
the scatternet algorithm.
4.4. Scatternet structure (Role-state ratios)
How M-, S-, ss- and ms- roles are distributed
throughout the scatternet nodes might also influence the
communication efficiency in the scatternet.
The piconet density, rp, is given by rp= nm/n. Here nm is
the total number of masters (i.e. the total number of
piconets) and n is the total number of nodes in the
scatternet. Unnecessary high piconet density might result in
more radio interference and less bandwidth to each piconet.
The slave degree, rsd= nsr/nm is the total number of
slave-roles nsr per master, derived from the number of pure
slaves, ns, the number of slave-slaves, nss, and the number of
master-slaves, nms, in the scatternet. A too high ns means
that piconet bandwidth is shared between unnecessary many
slaves, leaving little bandwidth to each slave. A too low ns,
on the other hand, means higher piconet density and higher
radio interference. Wang et al. [4] argue that the optimal
configuration is around five slaves per master.
Finally the slave-slave ratio, rss= nss/nm, and the masterslave ratio, rms= nms/nm, measure the average number of
slave-slaves per piconet and the average number of masterslaves per piconet, respectively.
5.
SIMULATIONS AND COMPARISONS
5.1. Simulations of scatternet formation
By simulations we placed Bluetooth devices on random
locations in a 30m-by-30m square. For simplicity, a node
was allowed to communicate with all other nodes located
within 10m - this is represented by arcs in the visibility
graph - and with no nodes outside this range. Nodes were
placed one by one inside the square. Each time a node
appeared in the square, the scatternet formation algorithm
was run on the node and scatternet configuration in the
square. The resulting scatternet configuration was used as a
starting point when the next node arrived in the square.
Nodes appeared to a maximum of 40 nodes. This simulation
run was repeated 100 times for each scatternet algorithm
simulated. Simulations were done using Matlab.
Upon a node’s arrival in the square, the node detected
and started connecting to an arbitrary of its neighboring
nodes in accordance with the scatternet formation algorithm
simulated. After an arriving node connected and attached to
another node as a free node (F), it continued detecting and
connecting to another arbitrarily selected neighbor, using
the slave (S) or master (M) role it obtained as a result of the
first connection. (Whether it became slave or master
depends on the role of the node it connected to, and could
be read directly from the role transition matrix of the
scatternet formation algorithm simulated.) It continued
detecting and connecting to neighbors until it had tried
connecting to all of its neighbors.
5.2. Comparison by simulations
Simulations showed that TSF had considerably worse
connectivity ratio than both non-hierarchical alternative
algorithms MSF and SSF (Figure 5). The reason is that the
strictly hierarchical approach puts strong restrictions on
how nodes can interconnect, and many forms of
interconnections are prohibited. TSF allows two scatternet
trees to combine into one scatternet tree only by direct
connection between the two scatternet-roots.
of each scatternet. Thus, the more nodes added to an ss-only
system, the better the connectivity! Indeed, the connectivity
ratios of SSF approached 1 as the number of nodes, n,
increased (Figure 5).
Scatternets with bridges only of the master-slave type,
on the other hand, are mainly populated by slaves and
master-slaves. As the number of nodes in the system
increases, a new free node will easily connect to a slave of
an existing scatternet, and become a slave. Hence, it will not
worsen the situation by creating new disconnected
scatternets. However, when the free node has become slave
of one scatternet, it may not connect to slaves or masterslaves of other scatternets and thereby heal
disconnectedness. Indeed, the connectivity ratios for MSF
and TSF flattened out and stabilized as the number of
nodes, n, increased (Figure 5).
For each set of simulations with one scatternet
algorithm we collected all scatternets formed and grouped
them by the number of nodes in the scatternet. For each
group of scatternets, we calculated the average ASP ratio
(Figure 6).
Figure 6. The two non-hierarchical algorithms, MSF and SSF, yield better
shortest path performance than TSF does. The ss-bridge based algorithm,
SSF, performs better than do the ms- based algorithms, TSF and MSF.
Figure 5. The two non-hierarchical algorithms, MSF and SSF, yield better
connectivity performance than the hierarchical TSF algorithm does. The ssbased algorithm, SSF, performs better than do the ms- based algorithms,
TSF and MSF.
Furthermore, we observed that the slave-slave-based
algorithm, SSF, performed better than the master-slavebased algorithms, MSF and TSF (Figure 5). Simulations
showed that scatternets with only ss-bridges are mainly
populated with masters, slaves and slave-slave bridges.
Hence, when a new free node arrives, it may easily
interconnect two disconnected scatternets by connecting to
one slave of each scatternet or by connecting to one master
Figure 6 shows that the non-hierarchical schemes
produce scatternets with
fewer hops between
communicating nodes on average than the hierarchical
algorithm does. The reason is that hierarchical scatternets
force communication along a tree structure, while the nonhierarchical algorithms, MSF and SSF, are more meshed
and can provide more direct paths. Furthermore, the slaveslave-based algorithm produces the flattest and most
efficient scatternet topologies even when compared to the
non-hierarchical ms-based algorithm, MSF (except for
scatternets with between 3 and 6 nodes, where MSF
scatternets performed slightly better).
Simulation also showed that the number of slaves per
master in a scatternet formed by TSF, is comparable with
that of the MSF algorithm, while it is considerably higher
for the SSF algorithm (Figure 7). The main reason is that
the two former algorithms use only ms-bridges and hence
each bridge introduces a new piconet, in contrast to the
latter algorithm, which uses only ss-bridges.
For all algorithms, the number of slaves per piconet is
far below the Bluetooth limit of maximum seven active
slaves per master. However, SSF is closer to the value of 5
slaves per master, which is claimed to be optimal by several
researchers [4].
topologies (i.e. when not all scatternet devices are within
radio range of each other).
Our simulations demonstrated that non-hierarchical
algorithms form scatternet topologies that are considerably
more efficient, in terms of connectivity and average shortest
path, than those formed by comparable master-slave-based
algorithms.
Researchers have emphasized that slave-slave bridges
are probably more optimal than using master slave-bridges,
in terms of efficient bridge management. Our simulations
also supported the advantages of slave-slave based
scatternets. Indeed, the slave-slave based scatternet
formation algorithm proved to have the highest ability to
accommodate connectivity between nodes.
A number of other proposed algorithms have
implemented measures to avoid that piconets are filled with
seven slaves. Our simulations indicate that such measures
might not be necessary.
The work presented in this paper should be extended to
compare with the quite large number of proposed scatternet
formation algorithms other than only TSF. Further work is
also required to translate the ASP-metrics proposed in this
paper into concrete communication performance on a
Bluetooth scatternet.
REFERENCES
Figure 7. Comparing average number of slaves per piconet of SSF with
that of the master-slave-based algorithms TSF and MSF. For all three
algorithms the average number of slaves per master is below the Bluetooth
limit of maximum seven active slaves per master.
Finally, we investigated the importance of the slavedegree limit of maximum seven slaves per master. We
eliminated the slave-degree limit and simulated within a
square of only 7m-by-7m, which corresponds to a strongly
connected topology with the highest probability of filling a
piconet with many slaves.
With 30 nodes, less than 0.1 % of the piconets formed
by TSF and MSF obtained more than seven slaves.
Similarly, only 11% of the piconets formed by SSF with 30
fully connected nodes obtained more than seven slaves.
Hence, the limit of seven slaves per master has little
importance for the asynchronous formation algorithms that
we studied. Many proposed scatternet formation algorithms
are based on reconfiguration of the scatternet when a new
node connects to avoid that a piconet is filled with seven
slaves. Our simulations, however, indicate that
reconfiguration might not be necessary.
6.
CONCLUDING REMARKS
We have argued that a scatternet formation algorithm
should allow for asynchronous scatternet formation, and it
should work well on weakly connected underlying
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