ASYNCHRONOUS FORMATION OF NON-HIERARCHICAL BLUETOOTH SCATTERNETS

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1 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

2 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. Minimal Piconet Overlap: Two piconets should be connected by at most one bridge node. b. 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. c. 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. TWO ALTERNATIVE NON-HIERARCHICAL ASYNCHRONOUS ALGORITHMS 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 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).

3 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 INQUIRY- SCAN. 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 (INQUIRY- SCAN). 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 INQUIRY- SCAN search state becomes the slave. The connection setup scheme is derived by the following arguments: 1. 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. 2. 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. 3. 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). 4. 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). 5. 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. 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). 4. 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).

4 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. 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 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, N 0, 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, r conn, defined as r conn = N/N 0 (1) gives a good measure of the overall connectivity provided by the scatternet formation algorithm 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 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 ASP 0 : r asp = ASP/ASP 0 (2) ASP 0 is found by traversing the links of the visibility graph between the scatternet nodes, instead of the links formed by the scatternet algorithm 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, r p, is given by r p = n m /n. Here n m 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, r sd = n sr /n m is the total number of slave-roles n sr per master, derived from the number of pure slaves, n s, the number of slave-slaves, n ss, and the number of master-slaves, n ms, in the scatternet. A too high n s means that piconet bandwidth is shared between unnecessary many slaves, leaving little bandwidth to each slave. A too low n s, 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, r ss = n ss /n m, and the masterslave ratio, r ms = n ms /n m, 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.

5 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 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

6 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]. 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 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 [1] Specification of the Bluetooth System, Bluetooth Special Interest Group document, Dec [2] Salonidis et al. Proximity Awareness and Ad Hoc Network Establishment in Bluetooth, Technical Research Report, [3] Zaruba, G.V., Basagni, S., Chlamtac, I., Bluetrees Scatternet Formation to Enable Bluetooth-Based Ad Hoc Networks, In Proceedings of the IEEE International Conference on Communications (ICC) 2001, Helsinki, Finland, June [4] Wang, Z., Thomas, R.J., Haas, Z., Bluenet a New Scatternet Formation Scheme, 35th Hawaii International Conference on System Science (HICSS-35), Big Island Hawaii, January 7-10, [5] Law, C., Mehta, A.K., Sui, K. -Y., Performance of a New Bluetooth Scatternet Formation Protocol, In Proc. of the ACM Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc) 2001, Long Beach, CA, USA, Oct [6] Tan et al., Forming Scatternets from Bluetooth Personal Area Networks, MIT Technical Report, MIT-LCS-TR- 826, October [7] Bhagwat, P and Rao, S.P., On the characterization of Bluetooth scatternet topologies, MobiHoc 2000, pravin/bluetooth, June 2000.

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