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CS 851 Wireless Sensor Networks Introductory Lecture. Professor Jack Stankovic Department of Computer Science University of Virginia September 2003. Purpose of this Lecture. Get you to think differently Regardless of whether you are new to WSN or have been working with them - PowerPoint PPT Presentation
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CS 851Wireless Sensor Networks
Introductory Lecture
Professor Jack Stankovic
Department of Computer Science
University of Virginia
September 2003
Purpose of this LecturePurpose of this Lecture
• Get you to think differently– Regardless of whether you are new to WSN or
have been working with them
• Introduce the basic key issues and their implications
• Reduce work to its essence
Motivation
• 1998– 100 million processors for workstations
– 6.4 billion for embedded systems
– approximately - 2% for workstations
• 2003– approximately 0%
• Ubiquitous computing (seemless, invisible, pervasive, amorphous, …)– wireless sensor networks
The field is exploding
Smart SpacesSmart Spaces
Smart School
Smart CitySmart Factory
Other Applications• Battlefields/Surveillance• Earthquake areas• Environmental Monitoring• Airport security• Emergency Response• Location Services
More Applications More Applications
• Interface with the Internet
• Handheld PDAs/laptops
• Element in pervasive computing
From your reading did you find interestingapplications or ideas about applications that wereSurprising?
Ad Hoc Wireless Sensor Networks
Ad Hoc Wireless Sensor Networks
• Sensors• Actuators• CPUs/Memory• Radio
Research QuestionsResearch Questions
• What are the correct HW elements to make solutions at the OS/middleware/application levels easier?– Current motes are only 1 possible platform
• How about DSPs? Special security HW?
– What capacities (cpu speed, memory, bandwidth, power, etc.) and their fundamental limitations, have if any, on solutions
Sensor/Actuator CloudsSensor/Actuator Clouds
HeterogeneousHomogeneous
Resource management, team formation, networking, …
Severe constraints
power, memory, bandwidth, cpu, cost, ...
• Background: Challenge fundamental assumptions underlying distributed systems technology
– How the problems change
• Key Areas to be Addressed
– Routing
– Power Management
– Localization
– Security
– Paradigms
– Theory
– Other Issues
• Examples: key research problems/solutions
– Spatial-Temporal Routing
– Application Independent Data Aggregation
– Localization Realities
How the Problems ChangeHow the Problems Change
• Environment– connect to physical environment (large numbers, dense, real-time)
– massively parallel interfaces (sometimes)
– faulty, highly dynamic, non-deterministic
– wireless (indirect impact on remote entity)
– power management critical
• Network– structure is dynamically changing
– sporadic connectivity
– new resources entering/leaving
– large amounts of redundancy
– self-configure/re-configure
– individual nodes are unimportant - route/query to AREA
How the Problems ChangeHow the Problems Change
• OS/Middleware– manage aggregate performance
• control the system to achieve required emerging behavior
• How do we know it works?
– self-organizing (self-*)
– fuzzy membership and team formation
– manage power/mobility/real-time/security tradeoffs
– geographical/location based (spatial)
– real-time/real world (temporal)
– data centric
ExamplesExamples
• Can you give me examples of simple decentralized algorithms that exhibit aggregate behavior?
ImplicationsImplications
• Fundamental Assumptions underlying distributed systems technology has changed– wired => wireless (limited range, high error
rates)– unlimited power => minimize power– Non-real-time => real-time– fixed set of resources => resources being
added/deleted– each node important => aggregate performance
• New solutions necessary
Example: Resource Management
Example: Resource Management
• Measure communication errors – if too many
• increase communication power or if a mobile node it might move closer to the destination
Example: ConsensusExample: 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 ?
New Concept of ConsensusNew Concept of Consensus
• 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 an area or by function
Classical New Definitions
Example: Group Management (Tracking)
Example: Group Management (Tracking)
Base Station
Group Management - APIGroup Management - API
– Create_Group(name,function,criterion,atleast,accuracy) - implicit and explicit
– Destroy_Group(name)– Join()– Leave()– Move_COG()– Expand() -- to gain sensing confidence– Shrink() -- to save power– Commit(grp_ID) - to synchronize group re-
configurations
What’s HardWhat’s Hard
• Multiple targets• Crossing targets• False Alarms
– Depends on (changing) environment, sensors, confidence tradeoffs, noise, lost messages, …)
• Speed of targets• Uniqueness of targets• Classify targets• Proper abstractions• Save power/min. commun.
The EssenceThe Essence
• Power
• Other limited resources (BW, CPU, …)
• Extreme Scale
• Changing “everything” / uncertainty
• Aggregation– unimportant individual nodes– decentralized, very simple algorithms
• What I do impacts you (collisions) – mutual exclusion
Six ThemesSix Themes
• Routing
• Power
• Localization
• Security
• Paradigms
• Theory
• Are there others? Yes…..
RoutingRouting
• Solutions must be– Power aware– Robust to lost messages, dead motes, voids– Real-time– Communication range variations– Moving end points– Amount of state information – Extreme Scale– Secure
PowerPower
• Example Algorithms– AFECA – power up and power down with time
proportional to the number of neighbors– GAF – create grid and keep at least one mote alive
in each grid (rotate among them in the grid)– SBPM – no grids; non-deterministic; minimize
connectivity; decentralized; complete sensing coverage (60% savings over no power management)
– Differentiated Surveillance • 50% less energy than “best” other solution
PowerPower
• Other power savings:– Vary transmission power– Turn off devices not needed
• On – all devices on
• Off – microprocessor in low power state so that registers/memory are not lost and clock interrupt can occur
– Checking – microprocessor and radio are on
– Choose routes that minimize power– Aggregate messages to save power
LocalizationLocalization
• Space (localization) and Time (clock sync) Basis– Environmental monitoring – where and when
events occurred
• Localization is a function of– Hardware available, cost requirement, signal
propagation model, timing and energy requirements, network makeup, nature of environment, node and beacon density, time sync, communication costs, error requirements, device mobility, …
SecuritySecurity• What is the single most important issue that could
prevent WSNs from wide scale deployment? – Security– 2nd issue -> Privacy
• At application level– Authenticity and integrity
• Security of each service (examples)– Routing:
• non-secure if a single node is captured!• Eavesdrop or change message• Flood
• Insidious unintended consequences of collecting data– Monitor oceans for fish migration (data mine location of
submarine fleet)
SecuritySecurity
• Localization– Attacker can report he is close to everyone– Chirp then wait then transmit to give false
location (normally chirp and transmit simultaneously – measure signals difference)
• Network Discovery– Provide false messages to create false topology– Prevent convergence
ParadigmsParadigms
• Virtual Machines
• SQL and data services models
• EnviroTrack
• Tie to physical systems/physics
• Swarm computing
• Biological metaphors
TheoryTheory• Theory of computation for WSN
• Emerging behavior of local/decentralized algorithms
• New graph theory
• New spatial-temporal analysis
• Aggregate control theory
• Utilization Equivalent Bounds
• Modeling and Analysis
• What are the fundamental scientific questions
Other Key Issues (1)Other Key Issues (1)
• Sensing/communication range ratio
• Sensing/communication/power tradeoffs
Sensing Range
CommunicationRange
What if the opposite?
Other Key Issues (2)Other Key Issues (2)
• Reality programming– Robust to faults– Sensor realities
• Don’t believe one reading
• Hysteresis
• Sensor fusion
• Activation delays
• Avoid false alarms
• Self-Calibration
Other Key Issues (3)Other Key Issues (3)
• Limited capacities
• Rapid dynamics
• Scaling factors and implications on behaviors– Extreme scaling
• Insidious interactions– High density with many motes off to enable long
system lifetime; turn on when activity happens then too many with many collisions and poor response
Other Key Issues (4)Other Key Issues (4)
• Architecture – hierarchy of control/capability/functionality
• Size of targets/events (point/area)
Fire
X
Explosion
Middleware ServicesMiddleware Services
• Non-traditional– Configuration service– Automatic calibration– Network programming– Reset services– Management services
Middleware ServicesMiddleware Services
• Real-Time Routing– SPEED – spatial-temporal concept
• Application Independent Data Aggregation– AIDA – feedback control
• Localization– APIT – realities of wireless world
Sensor Net RoutingSensor Net Routing • End-to-end• Real-time• Collisions• Congestion
Destination
Source
Assumption: Nodes know location
SPEEDSPEED
E2E Di stance
j
FS
iD
Actual Speed
Speed todestination(Set Point )
E2E Delay is bound by E2E Distance/Speed SetPoint
USE VELOCITY
Application Independent Data Aggregation
Application Independent Data Aggregation
• Expensive to acquire the “channel”
• Small data packets
• Group data packets into 1 MAC packet
• Works in addition to other data aggregation techniques which are based on semantics
Transport Layer
A.I DataAggregation
Network Layer
MAC Layer
ApplicationLayer
Data CentricRouting
MAC Layer
ApplicationLayer
TransportLayer
Data CentricRouting
MAC Layer
ApplicationLayer
TransportLayer
A.I DataAggregation
a. AIDA b. ADDA c. Both
Major Architectural DifferenceMajor Architectural Difference
FIXED SCHEMEFIXED SCHEME
• Accumulate N packets
• N: degree of aggregation– FIXED
– On Demand
– Adaptive/FC
• T: Time out for old packets when accumulation rate is slow
MAC
AIDA
Network
InputQueue
Input Queue
AggregatePool
AggregatorDe-Aggregator
NetworkOutput Queue
CounterPurge Timer
activate
Activate
ReachAggDegreeor Time Out
Activate
PrioritizedOutput Queue
DYNAMIC/Adaptive FCDYNAMIC/Adaptive FC
• Adaptive choice of N
• Take into account the output Queue delay
• Delay is used to adjust the output queue push rate and degree of aggregation
MAC
AIDA
Network
PrioritizedOutput Queue
InputQueue
Input Queue
AggregationPool
Aggregator
De-Aggregator
NetworkOutput Queue
IsEmpty
degree
Queuing Delay
AggDegree&
RateController
Counting
LocalizationLocalization
• Determine the geographic location of each node with a high degree of accuracy (necessary for application)– Applications
• search and rescue
• disaster relief
• target tracking
– Protocols• location aware routing
• guaranteeing sensing coverage
• location directory services
• Fundamental and Enabling Service
Radio Model in Evaluation Radio Model in Evaluation
Radio ModelDOI = Degree of Irregularity
DOI = 0.05 DOI = 0.2
M
NA
Anchor Receiving nodes
X
Known: Signal strength is not goodindicator of distance over the entireregion
Hypothesis: Signal strength IS accurate enough for nodes very close to each other!
Testing HypothesisTesting Hypothesis
300
350
400
450
500
550
600
1 5 9 13 17 21 25 29 33 37
Beacon Sequence Number
sig
na
l Str
en
gth
(m
v)
1 Foot
5 Feet
10 Feet
15 Feet
SummarySummary
• (Much) Current Distributed Systems Technology– wired networks, powerful nodes, highly reliable nodes,
interaction with users, fixed numbers of resources/team members, unlimited power, ...
• Embedded (Large Scale) Distributed Systems– wireless, simple nodes, unreliable nodes, interaction with
the environment, resources being added and deleted continuously, power management needed, …