Routing In Bluetooth

1
Department of Information Engineering University
of Padova, Italy
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COST273 May 30-31, 2002 Helsinki
TD (02)-062
2
On the performance of AODV and FSR routing
algorithms on Bluetooth scatternets preliminary
results
Department of Information Engineering University
of Padova, Italy
COST273 May 30-31, 2002 Helsinki
TD (02)-062
3
Outline of the contents

• Bluetooth basic
• Ad-hoc routing algorithms
• Ad-hoc On demand Distance Vector (AODV)?
• Fisheye State Routing (FSR)?
• Simulation model
• Experimental results
• Conclusions and future work

4
Bluetooth Technology

• What is Bluetooth?
• A wireless technology
• Proposed as cable replacement for leakage
  portable electronic devices, BT provides
  short-range low-power point-to-(multi)point
  wireless connectivity
• A global industry standard in the making
• Initially developed by Ericsson, now BT is
  promoted by an industry alliance called Special
  Interest Group (SIG)?

5
Bluetooth piconet

• Two up to eight Bluetooth units sharing the same
  channel form a piconet
• In each piconet, a unit acts as master, the
  others act as slaves
• Channel access is based on a centralized polling
  scheme

6
FH TDD

• Each piconet is associated to frequency hopping
  (FH) channel
• The pseudo-random FH sequence is imposed by the
  master
• Time is divided into consecutive time-slots of
  625 ?s
• Each slot corresponds to a different hop
  frequency
• Full-duplex is supported by Time-division-duplex
  (TDD)
• Master-to-slave (downlink) transmissions start on
  odd slots
• Slave-to-Master (uplink) transmissions start on
  even slots

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Bluetooth scatternets

• Piconets can be interconnected by Inter-piconet
  Units (IPUs)?
• IPUs may act as gateways, forwarding traffic
  among adjacent piconets
• IPUs must time-division their presence among the
  piconets
• Time division can be realized by using SNIFF mode

8
Next in the line

• Bluetooth basic
• Ad-hoc routing algorithms
• Ad-hoc On demand Distance Vector (AODV)?
• Fisheye State Routing (FSR)?
• Simulation model
• Experimental results
• Conclusions and future work

9
Motivations of the work

• Bluetooth gets out typical MANET scenario
• Physical proximity does not imply connection
• Connection set-up may take infinite time
• Broadcast is supported only within piconets
• Hence, MANET algorithms have to be tested in
  Bluetooth environment
• Table-driven algorithms LSR, DSDV,WRP,FSR
• On demand algorithms DSR,TORA,AODV?

10
IP-layer routing

• Routing is performed at IP layer, making use of
  IP addresses
• Pros
• No address-mapping
• Independence of the network details
• Cons
• Each node must support IP functionalities
• IP datagrams must be reassembled before forwarding

11
AODV Algorithm (1)?

• Route discovery
• Broadcast Route Request packet (RREQ), containing
  source and destination IP addresses
• Intermediate nodes that receive the RREq for the
  first time
• Increment by one the hop count field in the
  packet
• Add an entry containing source IP, destination
  IP, predecessor IP
• Broadcast the RREQ packet

IP5
IP3
Source node IP1
Destination node IP7
IP4
IP6
IP2
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AODV Algorithm (2)?

• Destination responds to the RREQ by unicasting a
  Route Reply (RREP) packet to the source
• The RREP flows backward along the path traced by
  the RREQ
• Intermediate nodes that process the RREP update
  their entry
• Entries that are not updated expire after a given
  timeout

IP5
IP3
Source node IP1
IP4
IP7 Destination node
IP6
IP2
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AODV Algorithm (3)?

• In case of link failure, AODV propagates a Route
  Error (RERR) message to the upstream nodes
• Receiving an RERR, nodes set to infinity the
  distance to the destination
• If the path is still needed, nodes start a new
  path discovery procedure

IP5
X
IP3
Source node IP1
X
IP4
IP7 Destination node
IP2
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FSR Algorithm (1)?

• Each node maintains link state information for
  every other node
• FSR generates route update on a periodic basis
• Routing information is propagated to neighbours
  only
• Updates occur on the basis of the Fisheye
  algorithm
• Nodes are divided in scopes, on the basis of
  their distance to the source
• Routing information for a given destination is
  updated with a frequency that is inversely
  proportional to the scope of the destination

15
FSR Algorithm (2)?

• Fisheye scope set of nodes within a given number
  of hops
• Closer nodes are update more frequently than
  farther ones

16
FSR Algorithm (3)?

• Getting close to the destination, the routing
  information becomes progressively more accurate

17
Next in the line

• Bluetooth basic
• Ad-hoc routing algorithms
• Ad-hoc On demand Distance Vector (AODV)?
• Fisheye State Routing (FSR)?
• Simulation model
• Experimental results
• Conclusions and future work

18
Simulation platform

• Simulator Tool OPNET Modeler Ver. 8.0
• The simulator does support
• Baseband protocols
• Frequency Hopping, Paging, Inquiry, Scan
• Link manager (LM) protocol
• Link layer control and adaptation protocol
  (L2CAP)
• Connection setup/release, Sniff Mode
• The simulator does not support
• Handover for Bluetooth units
• Multi-slot data packets

19
Model assumptions

• Pre-formed Scatternet
• Roles of master/slave/gateway are preassigned
• Pure Round Robin polling strategy
• Nodes in a piconet have the same priority and get
  polled in cyclic order
• 2 piconets per IPU
• IPU divides it time equally between the piconets
  by means of the sniff mechanism
• IPUs are not coordinated
• Network layer routing algorithms AODV FSR

20
Scatternet topology
21
Next in the line

• Bluetooth basic
• Ad-hoc routing algorithms
• Ad-hoc On demand Distance Vector (AODV)?
• Fisheye State Routing (FSR)?
• Simulation model
• Experimental results
• Conclusions and future work

22
Average end-to-end delay (1)?

• Simulation parameters
• CBR traffic 20 kbit/sec
• 5 hops connection
• 2 gateway units (IPUs)?
• Results
• End-to-end delay grows almost linearly with the
  Sniff period
• Short IP datagrams better exploit the pipeline
  effect

23
Average end-to-end delay (2)?

• Simulation parameters
• Sniff period 100 slots
• 5 hops connection
• Results
• Short IP dtgs achieve lower end-to-end delay but
  saturate earlier
• Long IP dtgs incur in higher end-to-end delay but
  increase capacity utilization

24
AODV route discovery delay (1)?

• Simulation parameters
• Sniff period 100 slots
• Route length increasing
• Results
• Using Link Layer (AODV-LL) messages to refresh
  table entries the discovery time is shorter
• Path discovery query ends one hop earlier
• Route discovery delay grows almost linearly with
  the distance of the destination

25
AODV route discovery delay (2)?

• Simulation parameters
• Sniff period ranges from 50 to 200 slots
• 5 hops connection
• Results
• Route discovery delay grows almost linearly with
  the Sniff period
• AODV-LL shows much better performance than
  AODV-std
• Impact of Sniff period is higher on longer path

26
Fisheye control traffic

• Simulation parameters
• Sniff time 50 slots
• Different Refresh periods
• Different number of scopes
• Remark Scope0 is the Global State Routing
• Results
• As expected, the more the number of scopes the
  less the control traffic
• Refresh Times less than 0.1s absorb more than 10
  of the system capacity
• Refresh time must be longer than 0.1s, but this
  increases the route updating delay

27
Fisheye update delay (1)?

• Simulation parameters
• 5 hops connection
• 2 scopes
• Sniff period 50 slots
• Refresh period ranges from 0.1 to 0.25 s
• Results
• A refresh period of 0.1 s updates nodes 6-hop
  faraway from the source within 1 s

28
Fisheye update delay (2)?

• Simulation parameters
• 2 scopes
• Sniff perriod ranges from 50 to 300 slots
• Refresh period0.25 s
• Path length increasing
• Results
• Update delay mainly due to the path length
• Sniff period has smaller impact

29
Next in the line

• Bluetooth basic
• Ad-hoc routing algorithms
• Ad-hoc On demand Distance Vector (AODV)?
• Fisheye State Routing (FSR)?
• Simulation model
• Experimental results
• Conclusions and future work

30
Final Remarks

• Datagram size and Sniff period have a
  considerable impact on IP end-to-end delay and
  AODV route discovery time
• FSR refresh time must be carefully chosen
• AODV appears suitable in case of
• Sparse connections
• Relaxed latency constraints
• Semi-static topology
• FSR appears more convenient for
• Dense connections
• Dynamic and wide topology

31
Future work

• Coming Soon (maybe)?
• Mathematical analysis of the scatternet
  efficiency
• Simulator enhancements
• Multi-slot packets
• Handover
• Comparison with Link Layer Routing algorithms
• Implementation of dynamic scatternet formation
  algorithms

32
Spare slides
33
Table-Driven algorithms

• Each node maintains one or more tables with
  routing information for every other node
• Nodes periodically exchange tables information
• Algorithms differ for the number of
  routing-related tables and updating strategy
• Examples
• Fisheye State Routing (FSR)
• Hierarchical State Routing (HSR)?
• Wireless Routing Protocol (WRP)?

34
On Demand algorithms

• Nodes maintain route information only to the
  nodes for which there is an actual need
• Routes are built on a demand basis, by means of a
  route discovery mechanism
• Changes on the network topology are propagated
  only to the interested nodes
• Examples
• Ad hoc On demand Distance Vector (AODV)?
• Cluster Based Routing (CBR)?
• Dynamic Source Routing (DSR)
• Associativity Based Routing (ABR)?

35
Routing on Bluetooth scatternet

• Bluetooth baseband packets contain AMA_ADDR
• Temporary and local meaning only
• Routing must be performed above the baseband
  layer!
• Possible approaches
• Data Link Layer Routing performed between L2CAP
  and IP
• Routing Vector Method (RVM)?
• Bluetooth Network Encapsulation Protocol (BNEP)?
• Network Layer routing performed at IP layer
• MANET algorithms

36
Data Link layer routing

• RVM lies above L2CAP and beneath IP
• It uses 3 bit local IDs to identify the piconets
• Routing is performed by means of the routing
  vector mechanism
• Pros simplicity, bandwidth conservation, low
  resources requirement
• Cons Topological changes determine address re-map