Download Grid: Scalable Ad Hoc Networking

6.964 Pervasive Computing
Grid: Scalable Ad Hoc Networking
1 November 2001
Douglas S. J. De Couto
Parallel and Distributed Operating Systems Group
MIT Laboratory For Computer Science
http://www.pdos.lcs.mit.edu/grid
Who are we?
• Grid project in PDOS
• Professor: Robert Morris
• Students:
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Douglas De Couto
Dan Aguayo
Jinyang Li
Ben Chambers
Hu Imm Lee
Outline
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Motivation
“Classic” ad hoc protocol
Geographic forwarding
Grid location service (GLS)
Location proxies
The Grid network
So you want to build a
pervasive network?
• Assumptions
– Wireless, packet-based, mobile
– Bigger than just your living room (multihop)
• Today’s approach: IEEE 802.11 base stations
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Site survey, measure radio performance
Channel Allocation
Inter-base-station network (wiring?)
…
Base-station example
Wired network
B1
B2
3
1
2
4
Ad hoc: a better way
• “Ad hoc” means no infrastructure, no planning
– Normally implies wireless, mobile, multihop
• Place devices (nodes) anywhere
• Constraint: devices should form connected
network
– If not, add “relay nodes”
• Costs less!
Ad hoc example
3
1
r
2
4
Ad hoc scenarios
• Temporary, fast setup
– Emergencies
– Social events
• Rooftop networks
– Connect neighborhoods
– No wires, trenches, etc.
• Developing communities
– Ad hoc is cheaper, more incremental
– Automatic protocols  no technicians needed
Other ad hoc benefits
• Better spectrum reuse (spatial)
• Better scalability
• Possibly better power
Ad hoc challenges
• How do we find multihop routes?
• Is there enough network capacity?
• Does it use too much device power?
– Span: Chen et al., Mobicom 2001
“Classic” protocol
• Dynamic Source Routing (DSR)
– Flooding route discovery finds source routes as
needed
– Aggressive caching helps performance
Why not use DSR?
• Protocol works well with about a hundred
nodes
– Simulation results; vary with movement, data
traffic
• Protocols scales poorly
– Propagates topology information throughout
network
– Overhead grows too fast with network size,
especially with mobility
DSR overhead
Number of nodes
Geographic forwarding (GF)
C’s radio range
A
C
B
D
F
G
E
• Packets addressed to id,location
• Next hop is chosen from neighbors to move packet
geographically closer to destination location
• Routing overhead constant as network size (nodes, area)
grows
GF With a Local Protocol
D
C
A
A’s nbrs:
B, 1 hop (nh: B)
C, 2 hops (nh: B)
B
E
B’s nbrs:
A, 1 hop (nh: A)
C, 1 hop (nh: C)
D, 22 hops
hops (nh:
(nh: C)
C)
D,
F
• Local protocol is 2-hop
distance vector
• A sends packets to F
• dcf > dbf but…
• ddf < dbf and
• C is B’s next hop to D
Geo. forwarding challenges
• How do we find destination locations?
• How do nodes find their own locations?
– Location sensors not always practical
• Topology problems (“holes”)
• General ad hoc problems
– Power, capacity
Grid Location Service (GLS)
overview
E
B
H
L
D
J
G
A
F
“D?”
I
K
C
Each node has a few servers that know its location.
1. Node D sends location updates to its servers (B, H, K).
2. Node J sends a query for D to one of D’s close servers.
Grid Node Identifiers
• Each Grid node has a unique identifier.
– Identifiers are numbers.
– Perhaps a hash of the node’s IP address.
• Identifier X is the “successor” of Y if X is
the smallest identifier greater than Y.
GLS’s Spatial Hierarchy
level-0
level-1
level-2
level-3
All nodes agree on the global origin of the grid hierarchy
3 servers per node per level
sibling level-0
squares
sibling level-1
squares
sibling level-2
squares
s
n s
s
s
s
s
s
s
s
• s is n’s successor in that square.
(Successor is the node with “least ID greater than” n )
Queries search for
destination’s successors
s
n s
s
s
Each query step:
visit n’s successor at
increasing level.
s
s
s
s1
s2
s
s3
location query path
x
GF + GLS performs well
Grid
DSR
Biggest network simulated:
600 nodes, 2900x2900m
(4-level grid hierarchy)
Number of nodes
• Geographic forwarding is less fragile than source routing.
• DSR queries use too much b/w with > 300 nodes.
GLS properties
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Spreads load evenly over all nodes
Degrades gracefully as nodes fail
Queries for nearby nodes stay local
Per-node storage and communication
costs grow slowly as the network size
grows: O(log n), n nodes
• More details: Li et al, Mobicom 2000
Geo. forwarding challenges
• How do we find destination locations?
• How do nodes find their own locations?
– Location sensors not always practical
Location Proxies
• Nodes that know their location can act as location
proxies
• Location proxies can communicate with each
other using geographic forwarding and the local
routing protocol
• Nodes without location select proxies, and
communicate through them using the local
protocol
• Nodes advertise proxy locations as their own
• Proxies not special besides knowing locations
Proxies Increase Delivery Rate
The Grid network
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Red: 5th floor
Blue: 6th floor
> 20 “relay” nodes
About 2 to 4 hops across each floor
Current Grid services
• IP routing, including Internet gateway
– E.g. supports traceroute
• Grid specific information
– Who can my radio talk to?
– Who do I have routes to?
Grid services “in progress”
• Location service
– Where is node X?
• Geocast
– Send message m to every node in region R
• Position estimation protocol
– I don’t have a position sensor
– Where am I?
Grid Applications
• What is a “Grid application”
– Uses unique Grid services
• Under development: Grid chat
– Regular text + voice chat
– Who’s nearby? (ask Grid)
– Who’s at the student center? (ask Grid)
Grid details
• Protocol software implemented in the Click modular
router
– Runs at userlevel, easy to interface to applications
– Very portable
• Nodes:
– Mobile: iPaqs + 802.11 PCMCIA + Linux
– “Relay” : small PCs + 802.11 PCI cards + OpenBSD
• Global distance vector (DV), or k-hop DV + GF
Grid Summary
• Grid routing protocols are:
– Self-configuring
– Easy to deploy
– Scalable
http://www.pdos.lcs.mit.edu/grid
ipkg: http://www.pdos.lcs.mit.edu/~decouto/grid-feed
ipkg install grid