Qos Routing In Ad Hoc Networks

QoS Routing in Ad Hoc Networks --Literature Survey Presented by: Li Cheng Supervisor: Prof. Gregor v. Bochmann

Outline • • • •

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 – – – – –

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

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BSC

GMSC

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HLR

VLR

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MS BTS

BTS

Cellular wireless network

MS BTS

Ad Hoc 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>

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QoS requirement: BW≥4 Shortest path QoS Satisfying path

Challenges 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 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 • • • • • •

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 Li Cheng, ELG5125

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[IETFDraft] : 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 Li Cheng, ELG5125

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)

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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. Li Cheng, ELG5125

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CEDAR: routing example

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Links that node B aware of

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Node S informs dominator B G H

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Links that node E aware of Partial Route constructed by B

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

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Complete, with last 2 nodes determined by E Li Cheng, ELG5125

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 change • Location and delay prediction: – Using similarity of triangles and Pythagoras’ theorem, (xp,yp) can be calculated

Predicted location (xp, yp) at tp v(tp-t2) (x2, y2) at t2

Direction of motion – End-to-end delay from S to D is predicted to be same as delay of latest update from D to S (x1, y1) at t1

• 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

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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 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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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 – – – – – – –

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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