Overview of Mesh Networking Research @ MSR Jitendra Padhye Microsoft Research January 23, 2006
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Overview of Mesh Networking Research @ MSR
Jitendra Padhye
Microsoft Research January 23, 2006
What are mesh networks?
• Multi-hop wireless networks • Mostly static nodes • Unplanned node placement • Applications: Disaster relief, Backhaul for city-wide wireless networks, Meeting mesh, Neighborhood Meshes, internet connection sharing • Many startups ….
Three main problems in mesh networking
• Capacity • Capacity • Capacity
Why is capacity a problem?
Source Mesh Router Destination With a single radio, a node can not transmit and receive simultaneously. A two-hop path has half the capacity of a one-hop path. Other interference patterns also possible.
Seminal Result by Gupta and Kumar (2000): Capacity = O(1/sqrt(n))
MSR’s research on Mesh Network Capacity
• Capacity estimation • Capacity improvement using multiple radios and other techniques • Feasibility study using realistic traffic
Mesh Network Capacity Estimation
• New framework for estimating capacity of multi-hop wireless networks – Gupta-Kumar result is asymptotic – Our framework calculates optimal capacity of a given mesh network for given set of flows
MobiCom 2003 (Jain, Padhye, Padmanabhan and Qiu).
• Our framework requires knowledge of which links interfere with one another – Problem of “conflict graph” estimation – N nodes O(N^2) links O(N^4) pairs!
– We developed an approximation technique that takes O(N^2) time
IMC 2005 (Padhye, Agarwal, Padmanabhan, Qiu, Rao and Zill)
Key Insight: Multiple radios necessary to improve capacity
Improving capacity using Multiple Radios
• Select best radio to send each packet using locally available information – Multi-radio unification protocol
IEEE BroadNets 2004: Adya, Bahl, Padhye, Wolman and Zhou)
– Problem: sub-optimal in many cases • Optimize entire path for a given flow – Take into account interference and link capacity along entire path – Implemented in Mesh Connectivity Layer (MCL)
MobiComm 2004: Padhye, Draves, Zill
• If second radio has very low bandwidth, can we use it to offload signaling?
– Simulation-based study of separating control and data into different frequency bands
IEEE BroadNets 2005 (Kyasanur, Padhye, Bahl)
How do we know how much capacity is “enough”?
Feasibility study using realistic traffic
• Collect traffic traces from Microsoft’s wired network • Replay on mesh testbed • Study delay characteristics of replayed traffic • Conclusions: – Factors such as specific card brands, placement of servers have significant impact, routing metrics have less impact.
– 2-radio mesh network likely sufficient for supporting normal office traffic – Some large delay spikes.
•
MobiSys 2006 (Eriksson, Agarwal, Bahl, Padhye)
Ongoing work related to capacity:
• Capacity improvement using network coding • Use of directional antennas to reduce interference • Use of spectrum etiquettes and cognitive radios to improve spectrum utilization
Other challanges:
• Self-management – Network without administrator – is it possible?
– Engineering challenges such as automatic address assignment • Security and Fairness – Freeloaders – Information leakage by observing traffic – Malicious nodes can disrupt routing
Backup slides
Mesh Connectivity Layer (MCL)
Design & Implementation
Design Choice Multi-hop networking at layer 2.5
Framework – NDIS miniport – provides virtual adapter on virtual link – NDIS protocol – binds to physical adapters that provide next-hop connectivity – Inserts a new L2.5 header Why Layer 2.5?
– Works over heterogeneous links (e.g. wireless, powerline) – Transparent to higher layer protocols. • works equally well with IPv4 and IPv6 – ARP etc. continue to work without any changes Features – DSR-like routing with optimizations at virtual link layer – Link Quality Source Routing (LQSR) – Incorporates 5 different link selection metrics: – Hop count, RTT, Packet Pair, ETX, WCETT
Scope: Technical Problems we looked at
Range and Capacity – Off-the-shelf wireless hardware Is severely range limited – Throughput of 802.11 MAC degrades rapidly with the number of hops Our Solution: multi-radio meshbox, directional ant., NLDP, Interference management, Capacity-cal Routing – Network connectivity is highly dynamic – Classical single path & shortest path routing perform poorly in a dense network Our Solution: LQSR & MR-LQSR, WCETT (ETX, PacketPair, RTT,..) Security and Fairness – Mesh is susceptible to freeloaders and malicious users – Achieving “fairness” without topological and traffic information is difficult Our Solution: “ Windows certificate", greedy behavior detection, watchdog mechanism, intrusion detection Self Management – End users are non-technical – A no-network operator model is challenging Our Solution: M 3 , watchdog mechanism, data cleaning, liar detection, on-line network simulation, beacon stuffing, server placement Spectrum Management – Tragedy of the commons – Exploit spectrum white space Our Solution: Control channel, dual-frequency meshes, 700-900 MHz, Spectrum etiquettes
Impact of path length on throughput
Experimental Setup • 23 node testbed • One IEEE 802.11a radio per node (NetGear card) • Randomly selected 100 sender receiver pairs (out of 23x22 = 506) • 3-minute TCP transfer, only one connection at a time 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000 0 0 1 2 3 4
Byte-Averaged Path Length (Hops)
5 If a connection takes multiple paths over lifetime, lengths are byte-averaged Total 506 points
.
6 Solution: Multi-Radio Meshes
Link Selection Metrics
Many metrics have been studied in literature – Hop count – – – – Round trip time Packet pair Expected data transmission count incl. retransmission Weighted cumulative expected transmission time – Signal strength stability – Energy related – Link error rate – Location related – … The ones in red are implemented in MCL
Link Selection Metric for Single Radio: ETX
• Each node periodically broadcasts a probe • The probe carries information about probes received from neighbors Advantages – Explicitly takes loss rate into account – Implicitly takes interference between successive hops into account – Low overhead • Each node can calculate loss rate on forward (P
f
) and reverse (P
r
) link to each neighbor • Selects the path with least total ETX ETX 1 (1 P f ) * (1 P r ) Disadvantages – PHY-layer loss rate of broadcast probe packets is not the same as PHY-layer loss rate of data packets Broadcast probe packets are smaller Broadcast packets are sent at lower data rate – Does not take data rate or link load into account Developed by De Couto et al @ MIT (2003)
Baseline comparison of Metrics
Single Radio Mesh
Experimental Setup • 23 node testbed • One IEEE 802.11a radio per node (NetGear card) • Randomly selected 100 sender-receiver pairs (out of 23x22 = 506) • 3-minute TCP transfer, only one connection at a time Median path length: HOP: 2, ETX: 3.01, RTT: 3.43, PktPair: 3.46
1600 1400 1200 1000 800 600 400 200 0 HOP ETX RTT ETX performs the best PktPair
Link Selection Metric for Multiple Radios: WCETT
State-of-art metrics (shortest path, Packet Pair, RTT, ETX) do not leverage channel, range, data rate diversity Multi-Radio Link Quality Source Routing (MR-LQSR) – Link metric: Expected Transmission Time (ETT) Takes bandwidth and loss rate of the link into account – Path metric: Weighted Cumulative ETTs (WCETT) Combine link ETTs of links along the path Takes channel diversity into account – Incorporates into source routing Developed by Draves, Padhye et al @ MSR(2004)
Expected Transmission Time (ETT)
Given: – Loss rate
p
– Bandwidth B – Mean packet size S – Min backoff window CW min Takes bandwidth and loss rate of the link into account ETT ET xmit ET backoff where, ET xmit S B(1 p) f(p) 1 i i 7 0 2 (i 1) p i ET backoff CW min 2(1 f(p) p)
WCETT = Combines link ETTs
Need to avoid unnecessarily long paths bad for TCP performance - bad for global resources All hops on a path on the same channel interfere – Add ETTs of hops that are on the same channel – Path throughput is dominated by the maximum of these sums Given a
n
hop path, where each hop can be on any one of
k
channels, and two tuning parameters,
a
and
b
: WCETT a* i n 1 ETT i a b* max 1 j k X j b where X j ETT i hop i is on channel j Select the path with min WCETT
Baseline Comparison of Metrics
Two Radio Mesh
Experimental Setup • 23 node testbed • Randomly selected 100 sender-receiver pairs (out of 23x22 = 506) • 3-minute TCP transfer • Two scenarios: – Baseline (Single radio): 802.11a NetGear cards – Two radios 802.11a NetGear cards 802.11g Proxim cards
3500 3000 2500 2000 1500 1000 500 0
Median path length: HOP: 2, ETX: 2.4, WCETT: 3
Median Throughput of 100 transfers 1601 2989.5
1379 1508 Single Radio Two Radios 1155 844 WCETT ETX Shortest Path
WCETT utilizes 2 nd radio better than ETX or shortest path
Path Length and Throughput
Which metric is best?
• • • Experimental Setup 23 node testbed Randomly selected 100 sender receiver pairs (out of 23x22 = 506) 3-minute TCP transfer (transmit as many bytes as possible in 2 minutes, followed by 1 minute of silence) For 1 or 2 hop the choice of metric doesn’t matter 4000 3500 3000 2500 2000 1500 1000 500 0 3.5
3 2.5
2 1.5
1 0.5
0 A WCETT ETX HOP C WCETT D ETX E HOP A C D E
Testbed Configuration
F F
Comparison of Metrics
Wireless Office Scenario
23 node indoor testbed. Two radios (both 802.11a) per node. 11 active clients, 4 servers. 10000 Light Office Traffic 1 hour, 415 sessions, 19.72 MB total 1000 474 100 89 10 11 4 1 WCETT 120 6 4 ETX 82 179 5 3 8 3 HOP PKTPAIR 6 2 RTT 10000 Heavy Office Traffic 1 hour, 308 sessions, 587.5 MB total 1000 590 100 27 10 4 1 WCETT 862 ETX 31 3 943 30 3 HOP PKTPAIR RTT Relatively light traffic means performance is okay for all metrics. WCETT does better under heavy load (worst case delay)
Management:
Resiliency against Liars/Lossy Links
• •
Problem
Identify nodes that report incorrect information (liars) Detect lossy links • •
Assume
Nodes monitor neighboring traffic, build traffic reports and periodically share info.
Most nodes provide reliable information
Challenge
Wireless links are error prone and unstable • • •
Approach
Watchdogs Find the smallest number of lying nodes to explain inconsistency in traffic reports Use the consistent information to estimate link loss rates
Simulation Results Detect liars
1 0.8
0.6
0.4
0.2
0 NL=1 NL=2 NL=5 NL=8 NL=10 NL=15 NL=20 coverage false positive
Detect lossy links
1 0.8
0.6
0.4
0.2
0 NL=1 NL=2 NL=5 NL=8 NL=10 NL=15 NL=20 coverage false positive