phero-trail: a bio-inspired location service for mobile underwater sensor networks
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Phero-Trail: A Bio-Inspired Location Service for Mobile Underwater Sensor Networks. Luiz Filipe M. Vieira † , Uichin Lee ‡ and Mario Gerla * - PowerPoint PPT PresentationTRANSCRIPT
Phero-Trail: A Bio-Inspired Location Service for Mobile Underwater Sensor Networks
Phero-Trail: A Bio-Inspired Location Service for Mobile Underwater Sensor Networks
Luiz Filipe M. Vieira †, Uichin Lee ‡ and Mario Gerla *
† Department of Computer Science, UFMG (米納斯州大學 ) , Brasii‡ Bell Labs, USA
* Department of Computer Science, University of California at Los Angeles, USA
IEEE Journal on Selected Areas in Communications, vol. 28, no. 4, May 2010
OutlineOutline
Introduction
Scenario
Problem & Goal
Phero-Trail
Performance
Conclusion
Page 2
Underwater Comm. CharacteristicsUnderwater Comm. Characteristics
Narrow available bandwidth
- Radio is unsuitable under water
- Must use acoustic channels
- High attenuation
Very slow acoustic signal propagation
- 1.5x103 m / sec vs. 3x108 m / sec
- Causes large propagation delay
Page 3
acoustic links
Sensors can adjust their depths using on-board pressure gauges
Example: Submarine DetectionExample: Submarine Detection
underwater sensor network to detect submarines
Page 4
Buoys
Radio
AcousticAcoustic
Seabed Sensor
Mobile sensor
Data Sink
ScenarioScenario
Protecting critical installation such as harbor, underwater mining facility, and oil rigs.
- Mobile floating sensor nodes
- Mobile Sinks
- Autonomous Underwater Vehicles (AUV) or Submarines
Page 5
Z
X
Y
Node ID z valueN2 z2
N3 z3
N1
N2N3
L
LD1
D2
R
ScenarioScenario
Sensor Equipped Aquatic (SEA) swarm of mobile sensors:
- Enable 4D (space and time) monitoring
- Dynamic monitoring coverage
Sensor nodes notify events to corresponding submarines
Page 6
Z
X
Y
EventType A
EventType B
EventType A
EventType B
Problem StatementsProblem Statements
Mobile sensors report events to submarines
Proactive (OLSR), Reactive Routing (AODV), or Sensor data collection (Directed Diffusion)
- All require route discovery (flooding) and/or maintenance
- Not suitable for bandwidth constrained underwater mobile sensor networks (collision + energy consumption)
Geographical routing is preferable, but requires geo-location service to know the destination’s location
Goal: design an efficient location service protocol for a SEA swarm
Page 7
Related Work – Naïve FloodingRelated Work – Naïve Flooding
Node periodically floods its current position to the entire network
Page 8
Z
X
Y
(AUV)
(sensors)
Related Work – Quorum BasedRelated Work – Quorum Based
Each location update is sent to a subset of nodes (update quorum)
Location query is sent to a subset of nodes (or query quorum)
The query will be resolved when their intersection is non-empty
Page 9
Query
Dst
Up
dat
eSrc
XYLS
Dst
Src
Dst
Up
dat
eSrc
(AUV)
(sensors)
Related Work – HierarchicalRelated Work – Hierarchical
Location servers are chosen via a set of hash functions
Area recursively divided into a hierarchy of smaller grids.
For each node, one or more nodes in each grid at each level of the hierarchy are chosen as its location servers.
Page 10
Level 3
Level 2
Level 1
Hierarchical - ExampleHierarchical - Example
Page 11
Node updating locationServer at level 2Server at level 3
Node requesting location
(AUV)
(sensors)
Protocol AnalysisProtocol Analysis
M: number of hops to travel a width of a network (L); i.e., L / R (communication range)
Quorum-based must store information in a 2D plane; i.e., O(M2)
Page 12
Update Query
Naïve flooding O(M3) O(1)
Quorum-based O(M2) O(M2)
Protocol AnalysisProtocol Analysis
Hierarchical- Must first find a reference point for geographic hashing and propagate this
information to every node.
- Overhead of “periodical” reference point updates dominates the update/query overhead.
Page 13
Reference Point Updates in Hierarchical SchemesReference Point Updates in Hierarchical Schemes
Periodic reference update O/H: O(M3)
Page 14
Location Service in 2DLocation Service in 2D
Store location information in 2D; search and update in 2D
But at the cost of vertical routing O(M) to given a location service plane
Put a 2D plane
- Upper hull
Page 15
Z
X
Y
Node ID z valueN2 z2
N3 z3
N1
N2N3
Location Service in 2D: AnalysisLocation Service in 2D: Analysis
Naïve flooding- update and query costs are O(M2)
Quorum-based- store information in a 1D line
- Update and query costs scale as O(M)
Hierarchical- Reference update, location update and query operations take O(M2) , O(H), and
O(M) respectively.
- Reference point update is still expensive!!!
Page 16
Phero-Trail – Location UpdatePhero-Trail – Location Update
AUV stores the location updates (pheromone) along its projected trajectory on the upper hull
- Periodic updates create a pheromone trail
Page 17
Phero-Trail – Location UpdatePhero-Trail – Location Update
AUV stores the location updates (pheromone) along its projected trajectory on the upper hull
- Periodic updates create a pheromone trail
Page 18
Z
X
Y
Node ID z valueN2 z2
N3 z3
N1
N2N3
D1
DH
D2
O(M)
Phero-Trail – Location QueryPhero-Trail – Location Query
A mobile node first routes a query packet vertically upwards to the node on the projected position of the convex hull plane
Node performs an expanding spiral curve search to find a pheromone trail.
Page 19
Event
1) Search Hull
Event
1) Search Hull
2) Ring Search
Event
1) Search Hull
2) Ring Search
3) Follow Trail
Event
1) Search Hull
2) Ring Search
4) Send Location
3) Follow Trail
Event
1) Search Hull
2) Ring Search
4) Send Location
3) Follow Trail
5) send alert
Simulation ResultsSimulation Results
QualNET 3.9.5
1 Km x 1 Km x 1 Km
Submarine 5 m/s
Vary the network size
Compared with flooding
Number of transmitted messages
Page 21
Simulation ResultsSimulation Results
Page 22
Simulation ResultsSimulation Results
Page 23
ConclusionConclusion
Presented a novel bio-inspired location service (PTLS)
- efficient location service protocol for a SEA swarm
- maintaining location information in a 2D plane is optimal
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