Scalable Tracking

1
Scalable Tracking Querying for Wireless Sensor
Networks

• Murat Demirbas
• SUNY Buffalo
• CSE Dept.

2
Sensor networks

• A sensor node (mote)
• 4Mhz processor, 128K flash memory
• magnetism, light, heat, sound, and vibration
  sensors
• wireless communication up to 100m
• costs in bulk 5 (now 80150)
• Applications include
• ecology monitoring, precision agriculture, civil
  engineering
• traffic monitoring, industrial automation,
  military and surveillance
• In OSU, we developed a surveillance service for
  DARPA-NEST
• classify trespassers as car, soldier, civilian
• LiteS 100 nodes in 2003, ExScal 1000 nodes in
  Dec 2004

A. Arora, et al. A Line in the Sand A Wireless
Sensor Network for Target Detection,
Classification, and Tracking. Computer Networks
(Elsevier), 2004.
3
Desiderata for sensor networks

• Scalability
• Large-scale deployment 10K nodes
• Communication-efficient (local) distributed
  programs are needed
• Fault-tolerance
• Message corruptions, nodes fail in complex ways
• Self-healing programs are needed

4
Overview of my research

• Distributed local WSN algorithms
• Tracking local and fault-locally healing
• Querying local and lightweight routing
• Spatial clustering, etc.
• Reliable communication in WSN
• Consensus in WSN Dependable applications
• Reliable broadcast at MAC layer Solving hidden
  terminal problem
• Reliable transactions for WSN A programming
  framework for concurrency-safe real-time control
  applications
• Specification-based design of self-healing
• Scalability wrt code size dependability
  preserving refinement of code

5
Tracking in WSN
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Tracking problem

• Evader strategy is unknown
• Pursuer can only talk to nearby sensor nodes,
  pursuer moves faster than evader
• Design a program for sensor nodes to enable the
  pursuer to catch the evader (despite the
  occurrence of faults)
• Applications battlefield scenarios, border
  patrol, personnel tracking, routing messages to
  mobile processes

M. Demirbas, A. Arora, and M. Gouda.
Pursuer-Evader Tracking in Sensor Networks.
Sensor Network Operations, 2005.
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Evader-centric program
Evader
Pursuer

• Tracking involves two operations
• Move update the tracking structure after evader
  relocates
• Find direct pursuer to reach evader using the
  tracking structure

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STALK Scalable tracking

• Maintain tracking structure
• over fewer number of nodes
• with accuracy inversely proportional to the
  distance from evader
• communication cost of msgj,k distance(j,k),
  delay ddistance(j,k)
• nearby nodes (cheap to update) have recent
  accurate info
• distant nodes (expensive to update) have stale
  rough info
• Local operations
• Cost of move proportional to the distance the
  evader moves
• Cost of find proportional to the distance from
  the evader
• Cost of healing proportional to the size of the
  initial perturbation
• To this end we employ a hierarchical partitioning
  of the network

M. Demirbas, A. Arora, T. Nolte, and N. Lynch. A
Hierarchy-based Fault-local Stabilizing Algorithm
for Tracking in Sensor Networks. OPODIS, 2004.
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Hierarchical clustering
R dilation factor of clustering to determine
size at higher levels Radius at level L is RL
M. Demirbas, A. Arora, V. Mittal, and V.
Kulathumani. Design and Analysis of a Fast Local
Clustering Service for Wireless Sensor Networks.
IEEE Trans. Par.Dist.Sys. 2006.
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Hierarchical tracking path
evader
evader
evader
Grow action for building a tracking
path Shrink action for cleaning unrooted paths
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Local find

• Searching phase
• A find operation at j queries js neighbors js
  clusterhead at increasingly higher levels to find
  the tracking path
• Tracing phase
• Once path is found, operation follows the path to
  its root

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Examples of find
evader
find
find
find

• A find for an evader d away incurs O(d) work/time
  cost
• guaranteed to hit the tracking path at level
  logRd of hierarchy

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A problem for move
evader
evader
evader

• evader dithering between cluster boundaries may
  lead to nonlocal updates

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Local move

• Lateral links to avoid nonlocal updates
• When evader moves to new location j
• a new path is started from j
• the new path checks neighbors at each level to
  see whether insertion of a lateral link is
  possible
• Restricts lateral links to 1 per level in order
  not to deteriorate the tracking path
• otherwise find would not be local since it could
  not hit the path at level logRd for an evader d
  away

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Examples of move
evader
evader
evader
evader
evader
evader
evader

• A move to distance d away incurs O(dlogRd)
  work/time cost
• a level L pointer is updated at every ?iL-1Ri
  distance level L is updated d/?iL-1Ri times
• update at L incurs O(RL) cost

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Local healing

• Local healing means work/time for recovery
  proportional to perturbation size not the
  network size
• In the presence of faults
• a grow can be mistakenly initiated shrink should
  contain grow
• a shrink can be mistakenly initiated grow should
  contain shrink

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Fault-containment

• Give more priority to the action that has more
  recent info regarding the validity of the path
• A shrink or grow action is delayed for longer
  periods as the level of the node executing the
  action gets higher
• j.grow-timer g R lvl(j)
• j.shrink-timer s R lvl(j)
• Catching occurs within a constant number of
  levels
• For g5d, s11d, b11dR
• grow catches shrink in 2 levels
• logR ((bRbsR2gR-dR)/(sR-gR-3d))
• shrink catches grow in 4 levels
• logR ((bRbsRgR-2s3dR)/(gR-s-d))

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Seamless tracking

• Fault-containment does not affect responsiveness
• Total delaying up to l is a constant factor of
  communication delay up to l, dR l
• Concurrent move operations
• move occurs before tracking path is updated
• a complete path is no longer possible
  discontinuity in the path
• give a bound on evader speed to maintain a
  reachable path
• Concurrent find operations
• when find reaches a dead-end, search phase is
  re-executed
• reachability condition guarantees that new path
  is nearby
• Cost of find move unaffected

find
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Querying in WSN
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Querying

• A.k.a information brokerage, or data-centric
  routing
• Static event (rather than dynamic event in
  tracking)
• Two operations
• Publish invoked by the nodes that detect an
  event
• Aims to inform any potential nodes interested in
  the event
• Query invoked by any node in the network
• aims to inform the querying node about a matching
  event and construct a path from the querying node
  to the event
• Centralized solutions are not acceptable due to
  high communication cost
• Locality (distance-sensitivity) should be
  maintained

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Glance

• Distance-sensitive (local) and tunable
• ensures that a query operation invoked within d
  hops of an event intercepts the events publish
  information within ds hops
• s is a stretch-factor tunable by the user
• Easily implemented without localization or
  hier.-clustering
• Lightweight, applicable to a wider range of WSN
• Unifies both modes of operation in WSN monitoring
  app.
• Centralized logging monitoring
• In-network querying (location-dependent querying)

M. Demirbas, A. Arora, and V. Kulathumani.
Glance A Lightweight Querying Service for
Wireless Sensor Networks. In submis. 2006.
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Model

• Multihop dense WSN
• Cost of communication over d hops is O(d)
• Geometric network
• triangle inequality is satisfied
• Distinguished basestation C
• de dist(e,C), e denotes an event
• dq dist(q,C), q denotes a querying node
• d dist(e,q)
• z angle eCq

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Two cases
q

• Case1 zgt threshold angle
• dq is relatively small compared to d
• dq lt ds
• OK for q to learn about e from C
• Case2 zlt threshold angle
• dq is relatively large compared to d
• dq gt ds
• NOT-OK for q to learn about e from C

dq
C
z
d
z
de
dq
e
d
q
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Outline of the solution

• The publish operation advertises the event on a
  cone boundary for some distance. Then goes
  straight to C.
• The query operation goes straight to C.

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Areas where s is satisfied

• For s1, take successively larger circles
  centered at e and C and intersect them.
• A2 is the region where stretch-factor is readily
  satisfied.
• For a querying node in A1 stretch-factor may be
  violated, publish should do local advertisement
  to ensure stretch-factor.

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Areas where s is satisfied

• For s2, similarly, we let a circle with radius r
  centered at e intersect with a circle with radius
  sr centered at C
• Stretch-factor is readily satisfied for A2, A3,
  and A4.
• For A1, s may be violated. A1 is a bounded area,
  since all the circles centered at e are subsumed
  by circles with radius 2r centered at C, for rgtde

• From HCe right-triangle, z is calculated as
  arcsin(1/s)arcsin(0.5)30

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Local advertisement

• The angle for the cone is taken as z. The event
  is advertised on the cone boundary for some
  distance. These account for any querying node in
  A1.
• The lateral advertisements inside the cone are to
  account for the querying nodes in area A1 that
  also fall within the cone boundaries.

A3
H
A4
2d
A1
d
d
d
A2
30
C
e
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Proof

• QK lt sQE
• QLLEcot(xx)ltsQE
• QEcos(w)QEsin(w)cot(xx)ltsQE
• sin(x)cos(w)sin(x)sin(w)cot(xx)lt1
• sin(xwx)ltsin(xx)/sin(x)
• True (for xxlt90 and xxlt180)

xarcsin(1/s) sin(x)1/s
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Avoiding the need for localization

• Glance requires only an approximation for the
  direction to C
• After deployment, C starts a one-time flood that
  annotates each node with its hopcount from C and
  creates a spanning tree rooted at C
• To send the query or publish as a straight line,
  nodes route the message to the parent node along
  a branch in this tree.
• Cone boundary is approximated by occasional
  lateral advertisement

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Spanning tree construction

• Flooding protocols result in a large number of
  anomalous situations
• Stragglers
• Backward links
• Highly clustered nodes
• These are due to collisions, nondeterministic
  non-isotropic nature of radio broadcasts, and
  earliest-first parent selection in the tree

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Optimized spanning tree

• Snooping to deal with stragglers/backward links
• Reactive repairing
• When a node with hopcount x hears a message with
  hopcount x2, it detects a straggler, to correct
  it decides randomly to rebroadcast
• Randomized adoption to deal with highly-clustered
  nodes
• A node with hopcount x may randomly select a node
  with hopcount x-1 as new parent

32
Query costs

• Scalability of average of hops for query
  operation is very good for Glance
• ideally query hops depends only on the distance
  between query and events
• however, since event and query locations are
  selected uniformly, for larger network the
  average distance between the two increases
• Glance does not involve any lateral advertisement
  but it performs very well!

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Publish costs

• The publish hops for Glance is equal to de, the
  cost of going to C, and is proportional to the
  depth of the MST constructed by C.
• the depth of MST scales nicely wrt the network
  size.

34
Stretch-factors

• Stretch-factors are independent of the network
  size
• Both Glance and GlanceP satisfy very low
  stretch-factors (less than 1.2)
• The reason Glance performs well is that MST
  performs significant aggregation
• Using MST, the information from two points e, q
  close to each other are bound to intermingle
• The probability that ancestors of e and q are
  always gt1-hop away rapidly drops to zero due to
  aggregation in MST

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Stretch-factors

• Stretch-factor wrt increasing distance for 30x30
  network
• For 300 gt eCq gt 60 dq is always less than d and
  stretch-factor is less than or equal to 1
• For small distances between e and q, aggregation
  in MST ensures that query-hops remain low

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Open research directions in WSN

• Distributed data structures for nearest-neighbor
  queries, range queries, especially for geometric
  networks
• Mobile WSN
• MAC layer issues
• Adaptive networking algorithms (geometric
  networks)
• WSN-Internet integration
• Genie project from NSF
• Programming frameworks for WSN

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Questions ?

• Distributed local WSN algorithms
• Tracking local and fault-locally healing
• Querying local and lightweight routing
• Spatial clustering, etc.
• Reliable communication in WSN
• Consensus in WSN Dependable applications
• Reliable broadcast at MAC layer Solving hidden
  terminal problem
• Reliable transactions for mobile WSN A
  programming framework for concurrency-safe
  real-time control applications
• Specification-based design of self-healing
• Scalability wrt code size dependability
  preserving refinement of code

38
www.cse.buffalo.edu/demirbas
39
Overview of my research

• Distributed local WSN algorithms
• Tracking local and fault-locally healing
• Querying local and lightweight routing
• Spatial clustering, etc.
• Reliable communication in WSN
• Consensus in WSN Dependable applications
• Reliable broadcast at MAC layer Solving hidden
  terminal problem
• Reliable transactions for mobile WSN A
  programming framework for concurrency-safe
  real-time control applications
• Specification-based design of self-healing
• Scalability wrt code size dependability
  preserving refinement of code

40
Coordinated attack problem

• Two armies waiting to attack the city they need
  to attack together to win
• Each army coordinates with a messenger
• Messenger may be captured by the city
• Can generals reach agreement?
• Agreement is impossible in the presence of
  unreliable channel
• Wireless communication is unreliable due to
  collisions !

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Collision awareness

• Necessary for coping with undetectable message
  loss
• Receiver side monitoring and notification of
  collisions
• No info wrt of lost messages or identities of
  senders
• Completeness Ability to detect collisions
• Majority-complete a collision is detected if a
  majority of messages in a round is lost
• 0-complete collision is detected if all messages
  in a round is lost
• Accuracy No false positives
• Always and eventually accurate CD
• Receiver side collision detection is easily
  implementable in mote and 802.11 platforms

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Vote-Veto algorithm

• Two phases vote and veto
• The algorithm is adaptive, employs active-passive
  service
• Vote phase
• Every active node sends out its vote
• If a node hears no collision, the node updates
  its vote to min of received votes
• If a node hears collision or different votes, it
  decides to veto
• Veto phase
• If no veto messages are received or collisions
  detected, then a node can decide, else nodes
  continue to next round
• Intuition By having a dedicated veto phase,
  effects of collision is detectable

Chockler, Demirbas, Gilbert, Newport PODC 2005
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Proof (for majority-complete CD)

• Let r be the first round any node decides
• Since no node vetoed in r, every node heard only
  a single vote and no collision during vote phase
  in r
• Since maj-?AC detects when half the messages
  are lost, each node received a majority of
  messages broadcasted in vote phase in r
• Since every majority set intersects, every node
  received the same unique vote

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Rumor routing

• Deliver packets to events
• query/configure/command
• No global coordinate system
• Algorithm
• Event sends out agents which leave trails for
  routing info
• Agents do random walk
• If an agent crosses a path to another event, a
  path is established
• Agent also optimizes paths if they find shorter
  ones

Braginsky, Estrin WSNA 2002