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

 Idit Keidar, TechnionIntel Academic Seminars, February 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

 Idit Keidar, TechnionIntel Academic Seminars, February 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

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

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

 Idit Keidar, TechnionIntel Academic Seminars, February 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

 Idit Keidar, TechnionIntel Academic Seminars, February 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.]

 Idit Keidar, TechnionIntel Academic Seminars, February 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

 Idit Keidar, TechnionIntel Academic Seminars, February 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

 Idit Keidar, Technion Intel Academic Seminars, February Octopus

 Idit Keidar, TechnionIntel Academic Seminars, February 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)

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

 Idit Keidar, TechnionIntel Academic Seminars, February 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

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

 Idit Keidar, TechnionIntel Academic Seminars, February 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

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

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

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

 Idit Keidar, TechnionIntel Academic Seminars, February 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

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

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

 Idit Keidar, Technion Intel Academic Seminars, February Evaluation

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

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

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

 Idit Keidar, TechnionIntel Academic Seminars, February Byte Complexity

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

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

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

 Idit Keidar, TechnionIntel Academic Seminars, February 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

 Idit Keidar, TechnionIntel Academic Seminars, February Fault-Tolerance

 Idit Keidar, TechnionIntel Academic Seminars, February Data Forwarding Reliability

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

 Idit Keidar, TechnionIntel Academic Seminars, February Reliability

 Idit Keidar, TechnionIntel Academic Seminars, February Message Complexity

 Idit Keidar, TechnionIntel Academic Seminars, February Byte Complexity

 Idit Keidar, TechnionIntel Academic Seminars, February Fault-Tolerance

 Idit Keidar, TechnionIntel Academic Seminars, February Data Overhead

 Idit Keidar, TechnionIntel Academic Seminars, February 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