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Programming and Querying in Wireless Sensor Networks

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Programming and Querying. in. Wireless Sensor Networks ... Sybil Attack. Wormholes. HELLO Flood Attack. Countermeasures. Security. Define new trust models ... – PowerPoint PPT presentation

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Title: Programming and Querying in Wireless Sensor Networks


1
Programming and Querying in Wireless Sensor
Networks
Professor Jack Stankovic Department of Computer
Science University of Virginia February 20, 2004
2
Programming Models
  • Environmental
  • EnviroTrack
  • Data/Database Centric
  • SQL
  • Middleware APIs
  • Group Management
  • Virtual Machines
  • Mate
  • Scripts
  • SensorWare
  • Events
  • DSWare
  • Components
  • nesC

3
Sensor/Actuator/Communication
Resource management, team formation, networking,
…
Heterogeneous Homogeneous

Severe constraints power, memory, bandwidth,
cpu, cost, ...
4
Abstractions
  • Program as a whole not individual nodes
  • Hide details (which ones, expose what)
  • Monitoring
  • Single node decisions
  • Asynchrony
  • Race conditions
  • False alarms
  • Retries
  • Physical details
  • Faults
  • Scale
  • Storage locations

5
Environmental Paradigm
  • Current Paradigms
  • Single node abstractions
  • Explicit interactions between nodes
  • Read sensor data fuse data move data
  • Set actuators
  • Environmental Paradigm
  • Aggregation and scale
  • Reflect the physical world directly
  • Virtual world of entities (fire, people,
    vehicles, pesticide, velocity, location, areas, …)

6
EnviroTrack
  • Events measurable environmental activities
  • Events mapped to programming objects
  • Computation is attached to these objects
  • Report location, compute velocity, …
  • Library provides protocols for sensor data
    processing, object maintenance, inter-object
    coordination, aggregation mechanisms, etc.

7
EnviroTrack
8
EnviroTrack
event-object VEHICLE object_creation_conditio
n ferrous object background sound
object_resolution 6 // minimal distance
between //
two events object_function
report.Location object_function
report.Speed
This statement is supported by drivers in a
library
ferrous object background sound
9
Routing Protocol - SPEED
USE VELOCITY
10
Radio Irregularity
DOI 0.2
DOI 0.05
Radio Model DOI Degree of Irregularity
11
Sensing versus Communication
  • Sensing/communication range ratio
  • Sensing/communication/power tradeoffs (sleep)

Communication Range
What if the opposite?
Sensing Range
12
nesC
  • the nesC model
  • interfaces
  • uses
  • provides
  • components
  • modules
  • configurations
  • application graph of components

Application
Component D
Component A
Component C
Component B
Component F
EnviroTrack on top of nesC
Component E
configuration
configuration
13
Data/Database Centric
  • Query Processing Architectures (SQL-based)
  • Process the queries
  • Route the queries
  • Retrieve information efficiently (in time and
    with low energy costs)
  • Storage Architectures
  • How/where to store collected data from sensors
  • In-network storage
  • At local node
  • Data centric name the data and hash to a
    location
  • Multi-resolution (hierarchies)

14
Example of Query
  • Retrieve, every 45 seconds, the rainfall level if
    it is greater than 50 mm

SELECT R.Sensor.getRainfallLevel() FROM RFSensors
R WHERE R.Sensor.getRainfallLevel() gt 50 AND
every(30)
15
Content Dissemination - Caching
Receivers (Refresh Rate, Accuracy)
Goal Find the optimal communication path to send
sensory data from a monitored source to multiple
(mobile) sinks such that energy usage is
minimized.
Data replicas (Placement?)
Information source (Aperiodic updates)
16
Content Dissemination - Storage
  • Tree construction
  • Hierarchical structure
  • Subscription requests
  • Replica Placement
  • Mobility management

17
Middleware APIs
  • Group Management
  • Create
  • Terminate
  • Merge
  • Join/Leave
  • Assign function
  • Track target
  • Classify target
  • Map temperature region
  • Consensus

18
Examples Tracking and Map Regions
Base Station
19
New Concept of Consensus
Classical
New Definitions
  • Termination every correct processor eventually
    decides some value
  • Uniform Agreement no two processors decide
    differently
  • Group Membership join/leave - everyone knows who
    is in the group
  • Termination at least n correct processors
    decide some value by time t
  • Group Agreement at least n processors decide the
    same value within epsilon
  • Area/Function Membership join/leave by area or
    by function

20
Example Consensus
  • Classical consensus all correct processes agree
    on one value
  • No power constraints
  • No real-time constraints
  • Does not scale well to dense networks
  • Approximate agreement (some work here) - on sets
    of values (physical quantities)
  • New Solutions Required with loose semantics

21
Group Management - API
  • Create_Group(name,function,criterion,atleast,accur
    acy) - implicit and explicit
  • Destroy_Group(name)
  • Join()
  • Leave()
  • Merge()
  • Move_COG()
  • Expand() -- to gain sensing confidence
  • Shrink() -- to save power
  • Commit(grp_ID) - to synchronize group
    re-configurations

22
Group Management
IR Camera
Leader
Follower
Member
Node
23
Group Management
IR Camera
Leader
Follower
Member
Node
24
Security
  • Complex, many aspects to consider
  • Opportunity to address this properly from the
    start!
  • New (severe) constraints (memory, bandwidth, cpu
    processing speeds, power, …)
  • Lightweight solutions required
  • Symmetric cryptography (asymmetric is too
    expensive)

25
Security
  • Secure Group Management
  • Authenticate members
  • Data integrity
  • Denial of Service
  • Jamming
  • Secure Routing
  • Physical Node Capture

26
Denial of Service
Ref Denial of Service in Sensor Networks Wood
Stankovic
27
Routing Attacks
  • WSN Routing Attacks
  • Spoofing
  • Selective Forwarding
  • Sinkhole Attack
  • Sybil Attack
  • Wormholes
  • HELLO Flood Attack
  • Countermeasures

28
Security
  • Define new trust models
  • Key Distribution
  • Can solutions exploit
  • Physical properties?
  • Density?
  • Redundancy?
  • HW?

29
Some Key Challenges (implem. programming paradigm)
  • Limit power consumption
  • Sleep-aware solutions
  • Limit underlying communication
  • Other constraint-aware solutions (cpu, memory,
    BW, …)
  • Scale issues
  • Incorporating security

30
Summary
  • Future success of WSN
  • Depends on good programming abstractions
  • Users
  • Scientists
  • Engineers
  • Application developers

31
Summary - Research Issues
  • Correct Abstractions
  • Debugging
  • Code Migration through the Network
  • Aggregation
  • Data/Query Dissemination
  • Storage/Caching
  • Security
  • Mobility
  • Real-Time
  • QoS
  • Scaling
  • Infrastructure Support (scale, energy
    minimization, …)
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