QoS Routing in Ad Hoc
Networks
--Literature Survey
Presented by: Li Cheng
Supervisor: Prof. Gregor v. Bochmann
Outline
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QoS routing overview: targets and challenges
Classification of QoS routing protocols
Typical QoS routing protocols
Conclusion and Open Issues
Video frame without QoS Support
Video frame with QoS Support
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Features of MANET
• Mobile Ad-hoc Network
• Definition: a self-configuring network of mobile
routers (and associated hosts) connected by
wireless links—the union of which form an
arbitrary topology (www.wikipedia.org)
• Features
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Dynamic and frequently changed topology
Self-organizing
Nodes behaving as routers
Minimal configuration and quick deployment
Limited resources
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Ad Hoc vs. Cellular Networks
• Multi-hop route vs. One-hop route
– In an Ad Hoc network, every nodes has to behave as a
router
• Self-administration vs. Centralized Administration
– Ad hoc networks are self-creating, self-organizing, and
self-administering
PSTN
OMC
AC
BSC
GMSC
MSC
BSC
HLR
VLR
BSC
MS
BTS
BTS
MS
BTS
Ad Hoc wireless network
Cellular wireless network
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Target of QoS Routing
• To find a feasible path between source and
destination, which
– satisfies the QoS requirements for each admitted
connection and
– Optimizes the use of network resources
<5,4>
<4,5>
A
C
B
<4,2>
<2,4>
<3,3>
D
E
<5,3>
<3,4>
<2,2>
Tuple: <BW,D>
F
<4,4>
G
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QoS requirement: BW≥4
Shortest path
QoS Satisfying path
Challenges of QoS Routing in Ad Hoc Networks
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Dynamic varying network topology
Imprecise state information
Scare resources
Absence of communication infrastructure
Lack of centralized control
Power limitations
Heterogeneous nodes and networks
Error-prone shared radio channel
Hidden terminal problem
Insecure medium
Other layers
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Criteria of QoS Routing Classification
• Routing information update mechanism
– Proactive/table-driven: QOLSR, EAR
– Reactive/On-demand: QoSAODV, PLBQR, TBP
– Hybrid: CEDAR
• Use of information for routing
– Information of past history: QOLSR, QoSAODV, TBP
– Prediction: PLBQR
• State maintenance
– Local: PLBQR, CEDAR
– Global: TDMA_AODV, TBP
• Routing topology
– Flat: QOLSR, QoSAODV, PLBQR, TBP
– Hierarchical: CEDAR
• Interaction with MAC layers
– Independent: PLBQR, QoSAODV, TBP
– Dependent: CEDAR, PAR
• Number of Path Discovered
– Single path: QoSAODV, CEDAR, PLBQR
– Multiple paths: TDMA_AODV, TBP
• Utilization of Specific Resources
– Power aware routing: PAR, EAR
– Geographical information assisted routing: PLBQR
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Typical Routing Mechanism
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Proactive routing: QOLSR
Reactive routing: QoSAODV
Ticket-based Routing: TBP
Hierarchical Routing: CEDAR
Predictive & Location-based routing: PLQBR
Power aware routing
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Proactive QoS Routing: QOLSR
• Optimized Link State Routing[RFC3626]
• Aiming at large and dense MANETs with lower mobility
• Only selected nodes as multi-point relays (MPRs) forwards
broadcasting messages to reduce overhead of flooding
• MPR nodes periodically broadcast its selector list
• QoS extensions
– QOLSR[IETF Draft]: Hello messages and routing tables are
extended with parameters of maximum delay and minimum
bandwidth, and maybe more QoS parameters
• Advantage: ease of integration
in Internet infrastructure
• Disadvantages: Overhead to keep
tables up to date
Black nodes: MPRs
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Reactive QoS Routing: QoS Enabled AODV
• AODV: Ad-hoc On-demand Distance Vector routing[RFC3561]
• Best effort routing protocol
• On need of a route, source node broadcasts route request(RREQ)
packet
• Destination, or an intermediate node with valid route to
destination, responses with a route reply(RREP) packet.
• QoS extensions[IETF Draft]: maximum delay and minimum bandwidth
are appended in RREQ, RREP and routing table entry
• Disadvantages
– No resource reservation, which unable to guarantee QoS
• Improved with bandwidth reservation: TDMA_AODV[7]
– Traversal time is only part of delay
RREQ1
(delay=100)
Source
Node A
RREQ2
(delay=20)
Rejected!
RREQ1
(delay=70)
Node B
Traversal_time=30
Delay(B->D)=80
RREP1
(delay=80)
RREQ1
(delay=20)
Dest.
Node D
Node C
Traversal_time=50
Delay(C->D)=50
RREP1
(delay=50)
RREP1
(delay=0)
QAODV example: Delay Requirement
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Ticket-based Probing[5]: Features
• Objective: To find delay/bandwidth-constrained least-cost
paths
• Source-initiated path discovery, with limited tickets in probe
packets to decrease overhead
• Based on imprecise end-to-end state information
• QoS metrics: Delay and bandwidth
• Redundancy routes for fault tolerance during path break
• Destination initiated Resource Reservation
p1(1)
B
p1(1)
A
C
p2(2)
p3(1)
D
p4(1)
p4(1)
E
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Tickets-relative Issues
• Colored tickets: yellow ones for smallest delay paths, green
ones for least cost paths
• For source node, how many tickets shall be issued?
– more tickets are issued for the connections with tighter or
higher requirements
• For intermediate nodes, how to distribute and forward
tickets?
– the link with less delay or cost gets more tickets
• How to dynamically maintain the multiple paths?
– the techniques of re-routing, path redundancy, and path
repairing are used
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Disadvantages and Enhancement of TBP
• Enhanced TBP Algorithm[13]
– Color-based ticket Distribution
– Ticket optimization using historical probing results
Ticket blocking
Color-based ticket distribution
• Disadvantages
– Based on assumption of relatively stable topologies
– Global state information maintenance with distance
vector protocol incurs huge control overhead
– Queuing delay and processing delay of nodes are not
taken into consideration
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Hierarchical Routing: CEDAR[6]
• Core Extraction Distributed Ad Hoc Routing
• Oriented to small and middle size networks
• Core extraction: A set of nodes is distributivedly and dynamically
selected to form the core, which maintains local topology and
performs route calculations
• Link state propagation: propagating bandwidth availability
information of stable high bandwidth links to all core nodes, while
information of dynamic links or low bandwidth is kept local
• QoS Route Computation:
– A core path is established first from dominator (neighboring core node)
of source to dominator of destination
– Using up-to-date local topology, dominator of source finds a path
satisfying the requested QoS from source to furthest possible core node
– This furthest core node then becomes the source of next iteration.
– The above process repeats until destination is reached or the
computation fails to find a feasible path.
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CEDAR: routing example
G
H
A
B
C
E
Core Node
D
F
S
Links that node B aware of
K
J
Node S informs dominator B
G
H
A
B
C
E
D
F
S
J
Links that node E aware of
Partial Route constructed by B
K
G
Disadvantages of CEDAR:
― Sub-optimal route
― Core nodes being bottleneck
H
A
B
C
E
D
F
S
J
K
Complete, with last 2 nodes determined by E
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Predictive Location-based QoS Routing: PLBQR[8]
• Motivation: to predict a future physical location based on previous
location updates, which in turn to predict future routes
• Update protocol: each node broadcasts its geographical update
and resource information periodically and in case of considerable
Predicted location
change
• Location and delay prediction:
(xp, yp) at tp
v(tp-t2)
– Using similarity of triangles and
(x2, y2) at t2
Pythagoras’ theorem,
Direction of motion
(xp,yp) can be calculated
(x1, y1) at t1
– End-to-end delay from S to D
is predicted to be same as delay of latest update from D to S
• QoS routing
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Neighbor discovery with location-delay prediction
Depth-first search to find candidate routes satisfied QoS requirements
Geographically shortest route is chosen
Route is contained in data packets sent by source
• Disadvantages
– No resource reservation
– Inaccuracy in delay prediction
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Power-aware QoS Routing
• Objective:
– to evenly distribute power consumption of each node
– to minimize overall transmission power for each connection
– to maximize the lifetime of all nodes
• Power-Aware Routing[9]: using power-aware metrics in shortestcost routing
– Minimize cost per packet, with cost as functions of remaining battery
power
– Minimize max node cost of the path to delay node failure
• Maximum battery life routing[10]: Conditional Max-Min Battery
Capacity Routing (CMMBCR)
– To choose shortest path if nodes in possible routes have sufficient
battery
– Avoiding routes going though nodes whose battery capacity is below
threshold
• Energy Aware Routing[11]: selecting path according to its
probability, which is inversely proportional to energy consumption,
using sub-optimal paths to increase network survivability
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Conclusion
• QoS routing is key issue in provision of QoS in Ad Hoc
networks
• Number of QoS routing approaches have been proposed in
literature, focusing on different QoS metrics
• No particular protocol provides overall solution
• Some Open Issues
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QoS metric selection and cost function design
Multi-class traffic
Scheduling mechanism at source
Packet prioritization for control messages
QoS routing that allows preemption
Integration/coordination with MAC layer
Heterogeneous networks
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Primary References
[1] T.Clausen, P.Jacquet, Optimized Link State Routing Protocol(OLSR), IETF RFC3626,
Oct.2993.
[2] H.Badis, K.Agha, Quality of Service for Ad hoc Optimized Link State Routing Protocol
(QOLSR), IETF Draft, Oct.2005
[3] C.Perkins, E. Royer and S. Das, Ad hoc On-Demand Distance Vector (AODV) Routing,
IETF RFC3561, Oct.2993.
[4] C.Perkins, E. Royer and S. Das, Quality of Service for Ad hoc On-Demand Distance
Vector Routing, IETF Draft, Jul.2000.
[5] S.Chen,K.Nahrstedt, Distributed Quality-of-Service Routing in Ad Hoc Network, IEEE
Journal on Selected Areas in Commun, Aug 1999.
[6] R.Sivakumar, P.Sinda and V. Bharghavan, CEDAR: A Core-Extraction Distributed Ad
Hoc Routing Algorithm, IEEE Journal on Selected Areas in Commun, Aug 1999.
[7] C.Zhu, M.Corson, QoS routing for mobile ad hoc networks, IEEE Infocom 2002.
[8] S.Shah, K.Nahrstedt, Predictive Location-Based QoS Routing in Ad Hoc Networks,
IEEE ICC 2002.
[9] S. Singh, M.Woo and C.Raghavendra, Power-aware Routing in Mobile Ad Hoc
Networks, MOBICOM’98.
[10] C. Toh, Maximum Battery Life Routing to Support Ubiquitous Mobile Computing in
Wireless Ad Hoc Networks, IEEE commun, Magazine, Jun 2001.
[11] R Shah, J.Rabaey, Energy Aware Routing for Low Energy Ad Hoc Sensor Networks,
IEEE WCNC 2002.
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Secondary References
[12] S.Chen,K.Nahrstedt, Distributed QoS Routing with Imprecise State Information, IEEE
ICCCN’98.
[13] L.Xiao,J.Wang and K.Nahrstedt, The Enhanced Ticket-based Routing Algorithm,
IEEE ICC, 2002
[14] C.Murthy, B.Manoj, Ad Hoc Wireless Networks, Pentice Hall, 2004
[15] M.Ilyas, I.Mahgoub, Mobile Computing Handbook, Auerbach Publications, 2005
[16] S.Chakrabarti, A.Mishra, QoS Issues in Ad Hoc Wireless Networks, IEEE Commun.
Magzine, Feb. 2001
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Any Questions?
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