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

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Presentation on theme: "QoS Routing in Ad Hoc Networks --Literature Survey Presented by: Li Cheng Supervisor: Prof. Gregor v. Bochmann."— Presentation transcript:

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

2 Li Cheng, ELG5125 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

3 Li Cheng, ELG5125 Features of MANET Mobile Ad-hoc Network Definition: a self-configuring network of mobile routers (and associated hosts) connected by wireless linksthe union of which form an arbitrary topology ( Features –Dynamic and frequently changed topology –Self-organizing –Nodes behaving as routers –Minimal configuration and quick deployment –Limited resources

4 Li Cheng, ELG5125 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 GMSC MSC OMCAC HLR VLR BSC BTS MS Cellular wireless network Ad Hoc wireless network

5 Li Cheng, ELG5125 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 A B C D EF G Tuple: QoS requirement: BW4 Shortest path QoS Satisfying path

6 Li Cheng, ELG5125 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

7 Li Cheng, ELG5125 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

8 Li Cheng, ELG5125 Typical Routing Mechanism Proactive routing: QOLSR Reactive routing: QoSAODV Ticket-based Routing: TBP Hierarchical Routing: CEDAR Predictive & Location-based routing: PLQBR Power aware routing

9 Li Cheng, ELG5125 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

10 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 [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 Source Node A Node B Traversal_time=30 Delay(B->D)=80 Node C Traversal_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!

11 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 A B C DE p 1 (1) p 2 (2)p 3 (1) p 4 (1) p 1 (1)

12 Li Cheng, ELG5125 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

13 Li Cheng, ELG5125 Disadvantages 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

14 Li Cheng, ELG5125 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.

15 Li Cheng, ELG5125 CEDAR: routing example G H DB F K E J C A S G H DB F K E J C A S G H DB F K E J C A S Links that node E aware of Partial Route constructed by B Core Node Links that node B aware of Complete, with last 2 nodes determined by E Node S informs dominator B Disadvantages of CEDAR: Sub-optimal route Core nodes being bottleneck

16 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, (x p,y p ) 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 Predicted location (x 2, y 2 ) at t 2 (x 1, y 1 ) at t 1 (x p, y p ) at t p v(t p -t 2 )

17 Li Cheng, ELG5125 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

18 Li Cheng, ELG5125 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

19 Li Cheng, ELG5125 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, MOBICOM98. [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.

20 Li Cheng, ELG5125 Secondary References [12] S.Chen,K.Nahrstedt, Distributed QoS Routing with Imprecise State Information, IEEE ICCCN98. [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

21 Li Cheng, ELG5125 Any Questions?

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