Funneling-MAC: A Localized, Sink-Oriented MAC For Boosting Fidelity in Sensor Networks

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Funneling-MAC A Localized, Sink-Oriented MAC
For Boosting Fidelity in Sensor Networks
Gahng-Seop Ahn, Emiliano Miluzzo, Andrew T.
Campbell, Se Gi Hong, Francesca Cuomo Columbia
University, Dartmouth College, University La
Sapienza SenSys 2006 Presenter Tsung-Han Lin
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Outline

• Background
• Funneling effect
• Protocol design
• Evaluation
• Conclusion

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MAC in Sensor Nets

• Collision avoidance
• Increase throughput
• Duty cycling
• Energy efficiency
• Latency

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Contention based

• S-MAC (Infocom 2002)
• Coordinated radio on-off
• Energy-latency trade-off
• Looser time sync demand than TDMA
• T-MAC (SenSys 2003)
• Enable longer sleep period of S-MAC if no traffic
  is detected

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Contention based

• B-MAC (SenSys 2004)
• Low power listening
• Flexible check period can be adjusted based on
  app traffic pattern

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Contention based

• SCP-MAC (SenSys 2006)
• Reduce preamble with synchronous check period and
  send time
• Allow ultra-low duty cycle
• X-MAC (SenSys 2006)
• Shorter preamble

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TDMA based

• TRAMA (SenSys 2003)
• Distributed algorithm
• Maintains two-hop neighbors info
• High message overhead
• DESYNC (IPSN 2007)
• Self organized protocol
• Auto adjust slot size
• Very low complexity, high channel utilization

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TDMA/CSMA Hybrid

• Z-MAC (SenSys 2005)
• CSMA in low contention TDMA in high contention
• DRAND distributed coloring algorithm to assign
  slots

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Funneling Effect

• The majority of packet loss occurs within the
  first few hops from the sink

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Quantifying funneling effect
(1.5m)

• Dartmouth testbed 45 Mica2 nodes,16 random
  sources
• Delivery ratio 1 hop neighbor gt 80, 2 hop
  neighbor lt 20
• MintRoute link quality based routing, data-ack
  approach
• B-MAC

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Traffic rate vs. Throughput

• To understand the impact under different network
  load
• 0.2 pps (light), 1 pps (medium), 4 pps(overload)

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Impact of funneling effect

• Overall loss rate 67 to 95
• Hop 1 and 2 have high loss rates
• 80- 90 of losses happen within the first 2 hops
  from the sink!
• Still true for light loaded network

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Any MAC resolves this?

• Z-MAC probably
• High contention TDMA
• However, Z-MAC schedules the whole network, which
  is too costly
• Funneling-MAC
• The scheduling is localized to sink
• Reacting dynamically to network condition

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The idea

• Hybrid TDMA/ CSMA scheme inside the intensity
  region
• Pure CSMA - pure CSMA scheme outside the
  intensity region
• Sink oriented TDMA scheduling
• Maintenance of the intensity region dynamically
  operated by the sink

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Protocol Design

• On-demand beaconing
• Sink-oriented scheduling
• Dynamic-depth tuning
• Meta-schedule advertisement

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On demand beaconing

• To decide the size of intensity region
• To synchronize nodes in the region

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On demand beaconing

1. Sink broadcast beacon periodically

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On demand beaconing

1. Sink broadcast beacon periodically
2. Nodes receive beacon as f-nodes, also synchronize
   the clock

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On demand beaconing

1. Sink broadcast beacon periodically
2. Nodes receive beacon as f-nodes, also synchronize
   the clock
3. Decide path head with data flow

Path heads
Path info is registered in the sink
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On demand beaconing

1. Sink broadcast beacon periodically
2. Nodes receive beacon as f-nodes, also synchronize
   the clock
3. Decide path head with data flow
4. If sink can schedule more f-nodes, increase the
   transmission power

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On demand beaconing

1. Sink broadcast beacon periodically
2. Nodes receive beacon as f-nodes, also synchronize
   the clock
3. Decide path head with data flow
4. If sink can schedule more f-nodes, increase the
   transmission power
5. Repeat (2)

Determined by dynamic depth tuning
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Sink-oriented scheduling

• Assign slots based on path and traffic
• Round robin for each path
• Sink broadcasts the TDMA schedule to every f-node
• Traffic measurement
• pkts / scheduled frame
• Moving average
• Spatial reuse
• The end of this path can share the same slot with
  the head of next path if they are 3-hop away

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Sink-oriented scheduling

• Path A 4-hop
• Path B 4-hop
• Path C 3-hop

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1
2
5
Spatial reuse Path B longer than 3-hop, 1 slot
can be reused
8
3
6
9
10
4
7
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Sink-oriented scheduling
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1
2
5
8
3
6
9
10
4
7
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Sink-oriented scheduling

• If more traffic are presented

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Framing

• The schedule is carried with beacons
• CSMA control pkts, unregistered event data
• Synchronous LPL for f-nodes

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Dynamic-depth tuning

• Schedule more nodes, less loss?
• Probability of collision decrease with hops
• No
• Amount of TDMA slots are limited over scheduling
  still leads to collisions
• An optimal depth lies in between

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Dynamic-depth tuning

• Amax max number of slots that can be assigned
  given the TDMA capacity
• A number of slots required to schedule
  path-heads traffic
• if A lt Amax then sink increases beacon
  transmission power
• if A gt Amax then sink decreases beacon
  transmission power

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Meta-schedule advertisement

• Reduce interference from possible interferer
• Nodes within the intensity region but do not
  receive beacons due to radio reasons
• Nodes close to the boundary of intensity region
• Recover if any intermediate nodes do not receive
  beacon

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Meta-schedule advertisement

• Embed mini schedule in the data packet
• Interferer knows when the CSMA slot starts
• Beacon loss can recover from this
• Only 4-byte
• Superframe, TDMA frame, time left of current
  frame, superframe repititions
• Only in the first packet each beacon interval

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Evaluation

• Depth tuning
• Boundary node interference
• Loss rate distribution
• Multi-hop throughput
• Energy tax and signaling overhead

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Setup

• Compared with B-MAC and Z-MAC
• MintRoute routing

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Impact of depth tuning

• Traffic? optimal depth?
• Dynamic depth tuning is in need

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Impact of boundary node interference

• Fixed power -7dBm
• Variable power -6-8dBm
• 8 nodes in the boundary area

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Loss rate distribution

• Reduce the loss rate in the first two hops

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Throughput

• All 44 nodes as sources with 5 pps (heavy load)
• MintRoute take 20mins to establish paths
• If no path, the data would go broadcast
• Z-MACs performance degrades

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Schedule drift

• DRAND schedule may not be valid over time
• 76.7 nodes have change in neighbor tables.
• The change is around 25-45
• Performance fall back to B-MAC
• Periodic DRAND has large overheads

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Varying workload

• Schedule drift
• More slots to nodes closer to sink

MintRoute fail to setup routing path
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Energy tax

• The total amount of cost to deliver a bit per
  node
• Control overhead
• B-MAC no
• Z-MAC local time sync packet
• Funneling-MAC beacon pkt, schedule pkt, path
  info header, meta-schedule header

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Signaling overhead

• Comparable with Z-MAC

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Conclusion

• Mitigating funneling effect through scheduling in
  the intensity region, even under lightly loaded
  traffic.
• Funneling-MAC outperforms Z-MAC and B-MAC in
  various network conditions

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Reference

• Some slides from Emiliano Miluzzos talk in
  SenSys 2006