grid: scalable ad hoc wireless networking
Post on 30-Dec-2015
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What is “Ad Hoc”?
• 802.11 “Ad hoc mode”• Single-hop communications
• Bluetooth: master/slave• All communication goes through master device
• We will mean multihop wireless networks without infrastructure, possibly mobile.
Talk Outline
• Motivation• Research Results
• Geographic forwarding • Grid location service (GLS)• Capacity of ad hoc networks• 802.11 performance
• Testbed Implementations• In-building net• Rooftop net
Application: Disaster Services
• Disaster may have damaged phone system etc.• Want to avoid N2 plans for N services to communicate
Design Challenges
• Finding routes
• Cope with mobile nodes
• Conserving battery power
• Coping with malicious/faulty nodes
• Scaling to large networks
Completed Research
• Scalable routing:• Geographic forwarding• Distributed P2P location database
• Low-power forwarding
• Understanding capacity limits
• Avoiding malicious nodes
• Current research: 802.11 link selection
Geographic forwarding (GF)
• Packets addressed to id, location• Next hop is chosen from neighbors to move packet
geographically closer to destination location
• Per-node routing overhead constant as network size (nodes, area) grows
• Requires location service, which adds overhead
N1
N2
N3N4 N5
N3’s radio range
N7
N6
A
EH
G
B
D
FC
J
I K
L
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.
“D?”
Grid Location Service (GLS) overview
level-0
level-1
level-2
level-3
All nodes agree on the global origin of the grid hierarchy
GLS’s Spatial Hierarchy
3 servers per node per leveln
s
s
s
s
s
s
s
s s
Node updates servers with GLS protocol
sibling level-0squares
sibling level-1squares
sibling level-2squares
Queries search for destination’s servers
Queries search with same protocol as updates.Guaranteed to find closest location server.
n
s
s
s
s
s
s
s
s s3
xs2
s1
location query path
• Geographic forwarding is less fragile than source routing.• DSR queries use too much b/w with > 300 nodes.
Fra
cti o
n of
da t
a pa
c ket
s de
l iver
ed s
ucce
ssfu
l ly
Number of nodes
DSR
Grid
GF + GLS performs well
Biggest network simulated:600 nodes, 2900x2900m(4-level grid hierarchy)
GLS properties
• 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
802.11 Capacity
• Enlarge network by adding nodes, area• Constant density
• Ideally, there is more “packet-hop” capacity, due to spatial reuse of spectrum
• But: more nodes producing traffic to be forwarded across network
Per-node capacity depends on traffic patterns
• “Random” traffic patterns won’t scale• Per-node capacity decreases like O(1/sqrt(n))
• “Local” traffic patterns scale, capacity remains constant if number of hops follows a power law distribution (e.g. GLS)
• More details: Li et al., Mobicom 2001
Implementation and Testbeds
• Software distributions for• Linux, BSD• PC, iPAQ
• Works with unmodified Internet software
• Two Grid nets deployed
LCS Grid Net
5
5
55
55 5
5 5 55
6
66 6 6
6
• 17 static nodes on 5th/6th floors• A dozen iPaq hand-helds
wiredgateway
A B
C DE
F
A’s nbrs:B, 1 hop (nh: B)C, 2 hops (nh: B)D, 3 hops (nh: B)…
C, 2 hops (nh: B)
B’s nbrs:A, 1 hop (nh: A)C, 1 hop (nh: C)D, 2 hops (nh: C)…
Distance Vector Protocol
C, 1 hop (nh: C)
*Nodes periodically broadcast route tables
*Nodes choose routewith fewest hops
Implementation
• Click modular software router (userlevel)• Portable: userlevel or kernel • Rich APIs, e.g. Vector, HashMap, etc.
• Any 802.11 card with std. “ad hoc mode”• Aironet 340/350 cards on Linux/BSD• Lucent-based cards on Linux• Best performance with driver support for signal
statistics (minor patches)
Grid Protocol
• All packets have Grid header• Own Ethernet type code (not IP packets)• Transmitter information: ID, location
• Control packets• Route advertisements (broadcasts)• Location queries and replies
• Data packets• Encapsulated IP• Link information is included
Packet Handling
Kernel
Userlevel
eth0
Grid routing process
demux
IPStack
Route lookup
Route tableControl packets (broadcast)
Encapsulated data packets
Grid packets (via pcap)
IP packets(via tun/tap)
Add/remove encapsulation
Applications
Packet Handling: Control
Kernel
Userlevel
eth0
Grid routing process
demux
IPStack
Route lookup
Route tableControl packets (broadcast)
Encapsulated data packets
Grid packets (via pcap)
IP packets(via tun/tap)
Add/remove encapsulation
Applications
Packet Handling: Data
Kernel
Userlevel
eth0
Grid routing process
demux
IPStack
Route lookup
Route tableControl packets (broadcast)
Encapsulated data packets
Grid packets (via pcap)
IP packets(via tun/tap)
Add/remove encapsulation
Applications
Obstacles to Better Routing
• Use low-loss paths, but…
• Loss rate masked by 802.11 re-sends
• Changes quickly with time, motion
• What’s the best metric to minimize?• Expected total packet transmissions
• Fight strong bias towards shortest paths
Current Approach: Measure loss rates
• Receiver measures loss rate of sender
• Receiver ping-pongs loss rate to sender
• Meaured with broadcast• But: each node broadcasts every ~1.3s• What period to measure over?
• How to smooth?• Trying exponentially time-weighted avg.
Grid Summary
• Grid routing protocols are• Self-configuring• Easy to deploy• Scalable
Software etc. at:
http://www.pdos.lcs.mit.edu/grid
References
• GLS: Li et al., “A Scalable Location Service for Geographic Ad Hoc Routing”. Proc. ACM MobiCom, August 2000. pp. 120--130
• Capacity: Li et al., “Capacity of Ad Hoc Wireless Networks”. Proc. ACM MobiCom, July 2001. pp. 61--69
• Link quality: De Couto et al., “Effects of Loss Rate on Ad Hoc Wireless Routing”. MIT LCS TR #836
Application: Disaster Services
• Disaster may have damaged phone system &c• Want to avoid N2 plans for N services to communicate
Design Challenges
• Cope with mobile nodes
• Finding routes
• Conserving battery power
• Coping with malicious/faulty nodes
• Scaling to large networks
Topology Distribution Scales Badly
1. “C can reach A and B.”
AB
C
D
F
3. Data from F to B.
2. “D can reach A, B, and C.”
G
Distributed Location Database
• Each node is DB for a few other nodes
• How to find a node’s location server(s)?
• Every node has an unchanging ID
• hash(ID) maps ID to position in unit square
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