Architectures and Applications for Wireless Sensor Networks (01204525) Network Architecture Chaiporn Jaikaeo [email protected] Department of Computer

Architectures and Applications for Wireless Sensor

Networks (01204525)

Network Architecture

Chaiporn [email protected]

Department of Computer EngineeringKasetsart University

Materials taken from lecture slides by Karl and Willig

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Outline Network scenarios Optimization goals Design principles Service interface Gateway concepts

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Typical Views of WSN Self-organizing mobile ad hoc

networks (MANETs) Peer-to-peer networks Multi/mobile agent systems and

swarm intellegence

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Sensor Network Scenarios Sources: Any entity that provides

data/measurements Sinks: Nodes where information is

required

Source

SinkInternet

Sink

Source

Sink

Source

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Single-Hop vs. Multi-hop Multi-hop networks

Send packets to an intermediate node Intermediate node forwards packet to its

destination Store-and-forward 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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Multi-hopping Always Efficient? 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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Multiple Sinks, Multiple sources

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Different sources of mobility Node mobility Sink mobility Event mobility

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Sink Mobility

Request

Movementdirection

Propagationof answers

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WSN Event Mobility

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Goal: Quality of Service 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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Goal: Energy efficiency 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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Sharpening the Drop Sacrifice long lifetimes in return for

an improvement in short lifetimes

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Goal: Scalability Network should be operational regardless

of number of nodes At high efficiency

Typical node numbers difficult to guess MANETs: 10s to 100s WSNs: 10s to 1000s, maybe more

Requiring to scale to large node numbers has serious consequences for network architecture Might not result in the most efficient solutions

for small networks! Carefully consider actual application needs

before looking for scalable solutions

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Distributed Organization WSN participants should cooperate

in organizing the network Centralized approach usually not

feasible Potential shortcomings

Not clear whether distributed or centralized organization 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-Network Processing WSNs are expected to provide

information Gives additional options E.g., manipulate or process 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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Aggregation Example

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1

31

1

6

1

1

11

1

1

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Signal Processing Another form of in-network

processing E.g.,

Edge detection Tracking/angle detection of signal

source Exploit temporal and spatial

correlation Observed signals might vary only

slowly in time Signals of neighboring nodes are often

quite similar Compressive sensing

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Adaptive Fidelity 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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Data Centric Networking Interactions in typical networks are

addressed to the identities 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-centric networking Principal design change

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Implementation Options Publish/subscribe (NDN – Named

Data Networking) Nodes can publish data, can

subscribe 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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Other Design Principles Exploit location information Exploit activity patterns Exploit heterogeneity

By construction By evolution

Cross-layer optimization of protocol stacks for WSN Goes against grain of standard

networking Promises big performance gains

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Interfaces to Protocol Stacks The world’s all-purpose network interface:

sockets Good for transmitting data from one sender to one

receiver Not well matched to WSN needs (ok for ad hoc

networks)

App as another component Well-designed interface

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Gateways in WSN/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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WSN to Internet Communication E.g., deliver an alarm message to an Internet

host Issues

Need to find a gateway (integrates routing & service discovery)

Choose “best” gateway if several are available How to find Alice or Alice’s IP?

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Internet to WSN communication How to find the right WSN to answer a

need? How to translate from IP protocols to WSN

protocols, semantics?

Gatewaynodes

Remote requester

Internet Gateway

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Gatewaynodes

Internet

Gateway

WSN tunneling Use the Internet to “tunnel” WSN

packets between two remote WSNs

6LoWPAN IPv6 over 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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Example 6LoWPAN Systems

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Summary Network architectures for WSNs look quite

different from typical networks in many aspects

Data-centric paradigm opens new possibilities for protocol design

Documents

Architectures and Applications for Wireless Sensor Networks (01204525) Network Architecture Chaiporn Jaikaeo [email protected] Department of Computer