MaxProp: Routing for Vehicle-BasedDisruption-Tolerant Networks

John Burgess, Brian Gallagher, David Jensen, �Brian Neil Levine

Department of Computer ScienceUniversity of Massachusetts Amherst

IEEE INFOCOM, April 2006 Supported by DARPA C-36-B82-S1, NSF-0519881, and NSF-0080199

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Networks in Challenged Environments �

§  Challenges�  Sparse deployment�  Short radio range�  System suspension for power management�  Unreliable/non-existent infrastructure�  Node mobility

§  Example scenarios�  Disasters�  Countries with developing infrastructure�  Underwater networking�  Sparse sensor deployments

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Solution: Disruption Tolerant Networks (DTNs) �

§  DTNs lack end-to-end network paths for routing.§  Packets are stored, carried, and forwarded

�  The mobility of nodes provides a path§  Replicating packets is effective for delivery

�  Too much replication causes congestion

§  Our protocol for routing is motivated by our real DTN.�  We wanted real mobility and radio propagation traces

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DieselNet�

•  Deployed hardware on 40 buses.

•  Each bus: Linux; two 802.11 radios; GPS 40GB hard drive

•  Buses transfer data as they pass by each other and via available hot spots.

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Transfers Opportunities �

Bytes transferred

§  Red dots show bus-to-bus transfers§  Duration of transfer opportunities is the limiting resource.

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MaxProp Protocol Assumptions �

§  Vehicle-based DTN resources:�  Plentiful power, storage, and CPU cycles�  Limited bandwidth to peers

§  Unknown physical location§  Expectation of repeated contact with some

subset of all peers§  Nodes enter and exit network without warning

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Prioritized Packet Replication�

§  Problem: what is the order of transmitted packets during a transfer to a peer?

§  Sort outgoing packets by how well peer can deliver to destination (next slide).

§  New packets receive bump in priority�  Unless device has a small buffer

§  Hop-lists prevent redundant transfers.§  Network-wide ACKs clear out old data.

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Deliverability Estimate �

1.  Create a meeting graph of connection events.2.  Assign to each edge between nodes i and j c(i,j)=“likelihood

that next peer i meets will be j”3.  Apply Djikstra’s algorithm to find shortest path via B to D.

All packets to the same destination are assigned the same cost.

§  Peers exchange a running list of meeting frequencies with other peers.

§  When node A meets B:�  A sorts its packets by the

estimated cost of routing the packet to its destination via B.

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Evaluation Goals �

1.  Are all MaxProp protocol components complimentary?

2.  How well does MaxProp perform?�  High percentage of packets delivered�  Low delivery latency

§  Comparison against:�  Random�  Dijkstra with a meeting oracle�  Just our cost estimate (no acks, etc)

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Setup�

§  Trace-based simulation�  DieselNet movements and data transfers�  Node exits cause packet loss

§  In paper: �  varied load�  # of nodes�  radio range

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Q1: Component Performance �

Max Prop (all)

Random+Lists Random+Acks

Random+ACKs+Lists

Random Cost Estimate

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Q2: Protocol performance �

§  2-18 bundles /hr, 10k bundles, unlimited buffer

§  MaxProp has higher delivery rate than other protocols.

Dijkstra (/w meeting oracle)

Cost Estimate

MaxProp Random

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Related Work�DTN routing protocols:§  J. Davis, A. Fagg, and B.N. Levine, "Wearable Computers as Packet Transport

Mechanisms in Highly Partitioned Ad-Hoc Networks", in Proc. Intl Symp on Wearable Computers. October 2001

§  A. Lindgren, A. Doria, O. Schelen, “Probabilistic Routing in Intermittently Connected Networks”. In Proc. Intl Wrkshp on Service Assurance with Partial and Intermittent Resources (SAPIR 2004), August 2004.

§  S. Jain, K. Fall, and R. Patra, “Routing in a Delay Tolerant Network”. In Proc. ACM SIGCOMM, August 2004.

§  B. Burns, O. Brock, and B.N. Levine. “MV routing and capacity building in disruption tolerant networks”. In Proc. IEEE INFOCOM, March 2005.

§  T. Spyropoulos, K. Psounis, and C. Raghavendra, “Spray and Wait: An Efficient Routing Scheme for Intermittently Connected Mobile Networks”. ACM SIGCOMM WDTN 2005.

DTN platforms:§  P. Juang et al. “Energy-efficient computing for wildlife tracking: design tradeoffs and

early experiences with zebranet”. SIGOPS Oper. Syst. Rev., 36(5):96–107, 2002.§  A. Pentland, R. Fletcher, and A. Hasson. “Daknet: Rethinking connectivity in

developing nations”. IEEE Computer, 37(1):78–83, Jan 2004.

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Contributions �

§  DTNs provide networking in challenged environments§  We constructed DieselNet, a vehicle-based DTN testbed§  Transfer duration is the limiting resource§  MaxProp uses several mechanisms to route bundles

�  Routing based on meeting history, age, acks, and hoplists§  Trace-based evaluation using DieselNet

§  Download the traces:http://prisms.cs.umass.edu/diesel/

BEGIN RESERVE SLIDES�

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Setting the Threshold�

§  Average bytes per connection event = x§  Total onboard buffer size = b§  If x < b / 2 then p = x§  If b / 2 ≤ x < b then p = min (x, b - x)§  If x > b then p = 0

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DieselNet Traces�

§  18 bundles /hr, 10k bundles, unlimited buffer

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Measurements �

Transfer duration

Inter-transfer opportunity timeBytes transferred

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Vehicle Simulator Traces �

§  18 bundles /hr, 10k bundles, unlimited buffer

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Software Components �

§  Auto update�  Update onboard software�  Log operational status�  Fault tolerant

§  Live IP�  Neighbor discovery�  Manage network connections

§  GPS update�  Receive and log GPS information

§  DTN daemon�  Store-and-forward DTN bundles

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Trace-based Simulators �

DTN Simulator DieselNet

Connection Events

Routing Protocol

Bundle Generation Parameters

Statistics

•  Needed repeatable experiment

•  Evaluated delivery rate and delay

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Synthesizing Traces �

Vehicle Simulator

GPS Location

logs

Radio Parameters

Bus Movement Parameters

Connection Events

•  Needed to vary number of nodes and radio range

•  Needed experiments with longer duration

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Virtual DTN Topology�

§  Connection events list generated as follows:�  Connection number c chosen for each node pair from

an exponential distribution�  All c below a threshold are set to 0 to reduce direct

peerings�  Time between pair meetings chosen from a Poisson

distribution with mean s / c, where s is the is the duration of the simulation

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Simulation vs. Real Systems �

§  Radio model concerns �  [Kotz et al]

§  Movement model concerns�  [Yoon, Liu, Noble 2003]

§  Real systems provide sanity checks§  Advantages to an operational DTN

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DieselNet Traces�

§  18 bundles /hr, 10k bundles

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Vehicle Simulator Traces �

§  18 bundles /hr, 10k bundles, unlimited buffer

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Virtual DTN Topology Traces�

§  18 bundles /hr, 10k bundles, unlimited buffer§  MaxProp best suited to vehicle-based networks

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Hopcount Delivery Estimation�