1.  Idit Keidar, Technion Intel Academic Seminars, February 20051 Octopus A Fault-Tolerant and Efficient Ad-hoc Routing Protocol Idit Keidar, Technion Joint work with Roie Melamed

2.  Idit Keidar, TechnionIntel Academic Seminars, February 20052 Ad-Hoc Networks A collection of mobile wireless nodes No pre-existing infrastructure Peer-to-peer routing: nodes relay each other's packets toward their ultimate destinations

3.  Idit Keidar, TechnionIntel Academic Seminars, February 20053 Applications of Ad-Hoc Networks Military: tactical communications Rescue missions: without adequate wireless coverage Commercial use: sales presentations Local Area Networks (LANs): in limited- coverage areas

4.  Idit Keidar, TechnionIntel Academic Seminars, February 20054 Challenges in Ad-Hoc Networks Lack of Infrastructure Limited wireless transmission range Rapid movement constantly changing topology Battery constrains Intermittent node disconnections

5.  Idit Keidar, TechnionIntel Academic Seminars, February 20055 Multi-Hop Routing A B C D

6.  Idit Keidar, TechnionIntel Academic Seminars, February 20056 Position-Based Ad-Hoc Routing Each node knows its location e.g., using GPS To send a packet– source discovers target location packets forwarded to this location Knowing location can eliminate flooding, improve scalability

7.  Idit Keidar, TechnionIntel Academic Seminars, February 20057 Location Severs Location servers for node n: nodes storing n’s location need to be updated whenever n moves To lookup t’s location– discover a location server of t All-for-some: each node has some location servers no flooding for update or lookup each node acts as location server for some nodes e.g., Grid Location Service (GLS) [Li et al.]

8.  Idit Keidar, TechnionIntel Academic Seminars, February 20058 Goals and Tradeoffs Low location update overhead want to send few update packets do not want to send many far away (many hops) Fault-tolerance (overcome disconnections) need many location servers need information to be fresh (frequently updated) Challenge: have many fresh location servers without inducing high load

9.  Idit Keidar, TechnionIntel Academic Seminars, February 20059 Observation In most protocols, each location update packet contains the location of a single node, and updates a single location server The key to a better fault-tolerance/overhead tradeoff is aggregation Challenge: locate location servers as to allow efficient aggregation and cheap location discovery

10.  Idit Keidar, Technion Intel Academic Seminars, February 200510 Octopus

11.  Idit Keidar, TechnionIntel Academic Seminars, February 200511 Octopus in a Nutshell Space divided into horizontal and vertical strips Nodes in same strip store each other’s locations Location updates aggregated in each strip Grid can change over time ( unlike GLS)

12.  Idit Keidar, TechnionIntel Academic Seminars, February 200512 Octopus: Key Features Fault tolerant many fresh location servers Efficient aggregation reduces location update overhead Simple Supports dynamically changing area Improved forwarding

13.  Idit Keidar, TechnionIntel Academic Seminars, February 200513 Three Sub-Protocols Location update maintains each node’s location at its designated location servers as well as at its radio range neighbors Location discovery discovers a target location (at an appropriate location server) Forwarding forward data packets to this location

14.  Idit Keidar, TechnionIntel Academic Seminars, February 200514 Location Update I – Neighbor List Periodically, each node broadcasts HELLO message with its identity and location to radio-range neighbors

15.  Idit Keidar, TechnionIntel Academic Seminars, February 200515 Location Update II – End Nodes A north/south end node has no neighbors in direction north/south that reside in its vertical strip Same for east/west horizontal

16.  Idit Keidar, TechnionIntel Academic Seminars, February 200516 Location Update II – Strip Update A-C A-FA-KA-M A-P A-WA-S A-I #messages per node- constant # bits- sqrt

17.  Idit Keidar, TechnionIntel Academic Seminars, February 200517 Location Discovery Take I

18.  Idit Keidar, TechnionIntel Academic Seminars, February 200518 Location Discovery Take II Forwarding Hole Quadratic reduction of failure rate

19.  Idit Keidar, TechnionIntel Academic Seminars, February 200519 Location Discovery Alternatives Two opposite directions at a time north and south concurrently, if fails, west and east concurrently One direction at a time try short direction first (use estimate of grid area) Tradeoff between overhead and latency

20.  Idit Keidar, TechnionIntel Academic Seminars, February 200520 Forwarding: Geographic Greedy Forward packet to neighbor that is closest to target

21.  Idit Keidar, TechnionIntel Academic Seminars, February 200521 Forwarding: Local Maxima Geographic forwarding fails Octopus uses redundant information about strip nodes Forward to strip node closest to target

22.  Idit Keidar, Technion Intel Academic Seminars, February 200522 Evaluation

23.  Idit Keidar, TechnionIntel Academic Seminars, February 200523 NS-2 Simulations Scalability increasing the network size with fixed density increasing the node density Fault-tolerance Data forwarding Comparison with GLS

24.  Idit Keidar, TechnionIntel Academic Seminars, February 200524 Reliability: Query Success Rate

25.  Idit Keidar, TechnionIntel Academic Seminars, February 200525 Message Complexity Scalable!

26.  Idit Keidar, TechnionIntel Academic Seminars, February 200526 Byte Complexity

27.  Idit Keidar, TechnionIntel Academic Seminars, February 200527 Node Density & Reliability

28.  Idit Keidar, TechnionIntel Academic Seminars, February 200528 Node Density & Message Complexity Scalable!

29.  Idit Keidar, TechnionIntel Academic Seminars, February 200529 Node Density & Byte Complexity Scalable!

30.  Idit Keidar, TechnionIntel Academic Seminars, February 200530 Node Disconnections – Simulation Setting Two types of nodes: stable and unstable A stable node is always up An unstable node alternates between being connected and disconnected up 2/3 of the time down 1/3 of the time For a percentage p of unstable nodes we run nodes

31.  Idit Keidar, TechnionIntel Academic Seminars, February 200531 Fault-Tolerance

32.  Idit Keidar, TechnionIntel Academic Seminars, February 200532 Data Forwarding Reliability

33.  Idit Keidar, TechnionIntel Academic Seminars, February 200533 Comparison with GLS Leading solution to date Compare: Reliability Message and byte complexity Fault-tolerance Data forwarding reliability and overhead

34.  Idit Keidar, TechnionIntel Academic Seminars, February 200534 Reliability

35.  Idit Keidar, TechnionIntel Academic Seminars, February 200535 Message Complexity

36.  Idit Keidar, TechnionIntel Academic Seminars, February 200536 Byte Complexity

37.  Idit Keidar, TechnionIntel Academic Seminars, February 200537 Fault-Tolerance

38.  Idit Keidar, TechnionIntel Academic Seminars, February 200538 Data Overhead

39.  Idit Keidar, TechnionIntel Academic Seminars, February 200539 Octopus: Conclusions Highly fault tolerant reliable when all nodes intermittently disconnect many fresh location servers Efficient aggregates: sends much fewer messages saves MACs, hence sends fewer bytes Simple Supports dynamically changing area Forwarding uses location information