an and d Im Impl plementa ementation tion (01 0120 20442 - - PowerPoint PPT Presentation

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an and d Im Impl plementa ementation tion (01 0120 20442 - - PowerPoint PPT Presentation

Net etwork work Ke Kerne nel l Ar Archi chitect tectures ures an and d Im Impl plementa ementation tion (01 0120 20442 4423) ) Net etwork work Ar Archi chite tecture cture Chaiporn Jaikaeo chaiporn.j@ku.ac.th Department


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Net etwork work Ke Kerne nel l Ar Archi chitect tectures ures an and d Im Impl plementa ementation tion (01 0120 20442 4423) ) Net etwork work Ar Archi chite tecture cture

Chaiporn Jaikaeo chaiporn.j@ku.ac.th Department of Computer Engineering Kasetsart University

Materials taken from lecture slides by Karl and Willig

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Out Outline line

Ne Netwo twork rk sc scena nari rios

  • s

Optimization goals

Design principles

Gateway concepts

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Ty Typi pical cal Vi Views ws of f WS WSN

Self-organizing mobile ad hoc networks (MANETs)

Peer-to-peer networks

Multi/mobile agent systems and swarm intellegence

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Sens nsor

  • r Ne

Netw twork rk Sce cena narios rios

Sour urces ces: Any entity that provides data/measurements

Sin inks: Nodes where information is required

Source Sink Internet Sink Source Sink Source

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Sin ingle gle-Hop Hop vs. . Mul ulti ti-hop hop

Multi-hop networks

  • Send packets to an intermediate node
  • Intermediate node forwards packet to its destination
  • Store

re-and and-fo forward rward multi-hop network

Store & forward multi-hopping NOT the only possible solution

  • E.g., collaborative

networking, network coding

Source Sink Obstacle

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Mu Multi lti-hopping hopping Al Alwa ways ys Ef Effi fici cient? nt?

Obvious idea: Multi-hopping is more energy- efficient than direct communication

  • Suppose we put a relay at distance d/2
  • Energy for distance d is reduced from cd to

2c(d/2)

  • c - some constant
  •  - path loss coefficient ( 2)

Usually wrong, or over-simplified

  • Need to take constant offsets for powering

transmitter, receiver into account

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Mu Multiple ltiple Sin inks, ks, Mu Mult ltiple iple sou

  • urces

rces

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Out Outline line

Network scenarios

Optimization timization go goals ls

Design principles

Gateway concepts

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Go Goal: al: Qua Quali lity ty of f Serv rvic ice

QoS in WSN is more complicated (compared to MANET)

  • Event detection/reporting probability
  • Event classification error, detection delay
  • Probability of missing a periodic report
  • Approximation accuracy (e.g, when WSN constructs a

temperature map)

  • Tracking accuracy (e.g., difference between true and

conjectured position of the pink elephant)

Related goal: robustness

  • Network should withstand failure of some nodes
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Go Goal: al: En Energ rgy y effi ffici ciency ncy

Many definitions

  • Energy per correctly received bit
  • Energy per reported (unique) event
  • Delay/energy tradeoffs
  • Network lifetime
  • Time to first node failure
  • Network half-life (how long until 50% of the nodes

died?)

  • Time to partition
  • Time to loss of coverage
  • Time to failure of first event notification
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Sha harpe rpening ning th the Dr Drop

Sacrifice long lifetimes in return for an improvement in short lifetimes

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Out Outline line

Network scenarios

Optimization goals

Desi sign gn prin inciples iples

Gateway concepts

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Di Distr tributed ibuted Or Organ ganization ization

WSN participants should cooperate in

  • rganizing the network
  • Centralized approach usually not feasible

Potential shortcomings

  • Not clear whether distributed or centralized
  • rganization achieves better energy efficiency

Option: “limited centralized” solution

  • Elect nodes for local coordination/control
  • Perhaps rotate this function over time
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In In-Ne Network twork Pro roce cessing ssing

WSNs are expected to provide information

  • Gives additional options
  • E.g., manipu

pulate late or proc

  • cess the data in the

network

Main example: aggregation

  • Apply aggregation functions to a collection tree

in a network

  • Typical functions: minimum, maximum,

average, sum, …

  • Not amenable functions: median
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Ag Aggr gregation gation Ex Exam ample ple

1 1 3 1 1 6 1 1 1 1 1 1

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Sig ignal nal Pro rocess cessing ing

Another form of in-network processing

E.g.,

  • Edge detection
  • Tracking/angle detection of signal source

Exploit temporal poral and sp spatial tial correlation elation

  • Observed signals might vary only slowly in time
  • Signals of neighboring nodes are often quite

similar

Compressive sensing

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Ada Adapt ptiv ive e Fi Fide delity lity

Adapt data processing effort based on required accuracy/fidelity

E.g., event detection

  • When event occurs, increase rate of message

exchanges

E.g., temperature

  • When temperature is in acceptable range, only

send temperature values at low resolution

  • When temperature becomes high, increase

resolution and thus message length

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Da Data ta Cent ntric ric Ne Netw twork rking ing

Interactions in typical networks are addressed to the id ident ntit ities ies of nodes

  • Known as node-centric or address-centric

networking paradigm

In WSN, specific source of events might not be important

  • Several nodes can observe the same area

Focus on data/results instead

 Data-centri centric c networ

  • rking

ng

  • Principal design change
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Im Impl plementa ementation tion Opt Optio ions ns

Publish/subscribe (NDN – Named Data Networking)

  • Nodes can publ

blish data, can subs bscr cribe be to any particular kind of data

  • Once data of a certain type has been

published, it is delivered to all subscribers

Databases

  • SQL-based request
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Out Outline line

Network scenarios

Optimization goals

Design principles

Gat ateway eway con

  • ncep

epts ts

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Ga Gate teways ways in in WS WSN/ N/MANET MANET

Allow remote access to/from the WSN

Bridge the gap between different interaction semantics

  • E.g., data vs. address-centric networking

Need support for different radios/protocols

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Gateway nodes Internet Gateway

WS WSN N tu tunne nneling ling

Use the Internet to “tunnel” WSN packets between two remote WSNs

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6Lo LoWPAN WPAN

IPv6 over Lo Low-power Wireless Personal Area Networks

Nodes communicate using IPv6 packets

An IPv6 packet is carried in the payload of IEEE 802.15.4 data frames

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Ex Example ample 6Lo LoWPAN WPAN Sys yste tems ms

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Sum ummary mary

Network architectures for WSNs look quite different from typical networks in many aspects

Data-centric paradigm opens new possibilities for protocol design