QoS Routing in Ad Hoc QoS Routing in Ad Hoc NetworksNetworks

--Literature Survey--Literature Survey

Presented by: Li ChengPresented by: Li ChengSupervisor: Prof. Gregor v. BochmannSupervisor: Prof. Gregor v. Bochmann

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OutlineOutline• 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 MANETFeatures 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– 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 NetworksAd 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

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Cellular wireless networkAd Hoc wireless network

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Target of QoS RoutingTarget 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

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Tuple: <BW,D>

QoS requirement: BW≥4

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<5,3><4,2>

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Shortest path

QoS Satisfying path

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Challenges of QoS Routing in Ad Hoc NetworksChallenges of QoS Routing in Ad Hoc Networks• 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 ClassificationCriteria 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 MechanismTypical Routing Mechanism• 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: QOLSRProactive 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 AODVReactive 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

SourceNode A

Node BTraversal_time=30

Delay(B->D)=80

Node CTraversal_time=50

Dest. Node D

RREQ1(delay=100) RREQ1

(delay=70)RREQ1

(delay=20)

RREP1(delay=0)

RREP1(delay=50)

RREP1(delay=80)

Delay(C->D)=50

QAODV example: Delay Requirement

RREQ2(delay=20)Rejected!

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Ticket-based ProbingTicket-based Probing[5][5]: Features: 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

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p1(1)

p2(2) p3(1)

p4(1)

p4(1)

p1(1)

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Tickets-relative IssuesTickets-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 TBPDisadvantages and Enhancement of TBP• Enhanced TBP Algorithm[13]

– Color-based ticket Distribution– Ticket optimization using historical probing results

• 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

Ticket blocking Color-based ticket distribution

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Hierarchical Routing: CEDARHierarchical Routing: CEDAR[6][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 exampleCEDAR: routing exampleG

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Links that node E aware of Partial Route constructed by B

Core Node

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Node S informs dominator B

Disadvantages of CEDAR: ― Sub-optimal route― Core nodes being bottleneck

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Predictive Location-based QoS Routing: PLBQRPredictive Location-based QoS Routing: PLBQR[8][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 change• Location and delay prediction:

– Using similarity of triangles and Pythagoras’ theorem, (xp,yp) can be calculated– End-to-end delay from S to D is predicted to be same as delay of latest update from D to S

• QoS routing– 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

Direction of motion

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(x2, y2) at t2

(x1, y1) at t1

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v(tp-t2)

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Power-aware QoS RoutingPower-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 shortest-cost 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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ConclusionConclusion• 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

– 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 ReferencesPrimary 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 ReferencesSecondary 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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