WSN Performance

8/10/2019 WSN Performance

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temas Embebidos 2013/14

SNs - Performance 1

Wireless SensorNetworks PerformanceSistemas Embebidos

2013/14

Pedro Brando

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References

These slides are based in chapter 11 ofWireless Sensor Networks: Technology,Protocols, and Applications, KazemSohraby, Daniel Minoli, Taieb Znati, fromWiley-Interscience, ISBN 978-0-471-74300-2,

2007 [WSN-KDT]

SE 2013/14 - WSNs 2 - pbrandao (see at beginning)

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SNs - Performance 2

Background

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Basic scenario


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Image from [WSN-KDT]


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SNs - Performance 3

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Sensor Types

specialized sensing platformE.g.: Spec

generic sensing platformE.g.: SunSPOT

High bandwidth sensingUsing Bluetooth: imote2

gateway-like sensor nodeE.g.: stargate


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Topologies

StructuredE.g.: two-tier Nodes at low level onlysense, upper level senseand relayMultihop

Routing more efficientMore energy for topologyformationMore node complexity tohandle the protocol

Ad Hocflat and unstructuredtopologyAll nodes sense andrelay


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SNs - Performance 4

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Topologies

Multihop multipath, route redundancyBattery depletion

dysfunctional node

Disjoint topology (when dysfunctionalnodes reach threshold)

Mobility causes similar problems


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Traffic

From sensor nodes to a single sink Many to one (convergecast)

May be for several sinks multipaths

Nodes closer to sink will have more trafficto handle

Dysfunctional sooner

deploy more nodes around the sink, rotatenodes

Data aggregation


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SNs - Performance 5

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WSN Service type

basic service: detect certain events andreport them.

data is usually small (a few bytes or a fewbits)

transmit more than one event in a single dataunit if application reporting frequency allows it.


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Design Factors for WSNs


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Table from [WSN-KDT]


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SNs - Performance 6

MAC protocols


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MAC protocols energy waste

packet collision require retransmissionenergy waste

Wireless shared medium

Control messages for data transmission (e.g.,RTS/CTS) consume energyOverhearing and idle listening energywaste.

Overhearing: node receives packets destined forothers.Idle listening: nodes listen on the channel to get itsstatus


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SNs - Performance 7

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Some approaches

S-MAC: low-duty-cycle coordinated sleepand wakeup time periods to reducepower consumption while achieving highthroughput.

LEACH: recall that it uses TDMA in clusterand CDMA between clusters


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Measuring MAC performance

Collision probability

Control overheadDelay

Throughput.


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SNs - Performance 8

Routing protocols


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Classification


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Image from [WSN-KDT]


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SNs - Performance 9

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Data centric routing advantage

Easy deploymentData aggregation enables energy saving

Low overhead in control messages


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Measuring routing performance

Computational overhead

Communications overheadPath reliability

Path length

Convergence rateStability


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SNs - Performance 10

Transport protocols


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Main factors

Congestion controlReliability

Different from normal netsReceive info from at least one node inselected area

Receive certain ratio of successful transmissionsfrom a node

Have a hop-by-hop mechanism forcongestion control and loss recoveryFairness


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Performance models


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MetricsSystem lifetime:

duration of time until some node depletes all itsenergy;

duration of time until the QoS of applicationscannot be guaranteed

duration of time until the network has been

disjoined.Energy efficiency: number of packets thatcan be transmitted successfully using aunit of energy.


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Metrics (cont.)

Reliability: can be defined as the ratio ofsuccessfully received packets over thetotal number of packets transmitted.Coverage: ratio of the monitored space tothe entire space.Connectivity: evaluate how well thenetwork is connected and/or how manynodes have been isolated.QoS metrics: applications may have QoSrequirements such as delay, loss ratio, andbandwidth.


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Traffic model

Event-Based Delivery:Monitor continuously

Detect event and transmit (with possible value)

Continuous DeliveryContinuously or periodically

Query-Based DeliverySink issues query

Hybrid DeliveryDiverse types of data


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Energy


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Image from [WSN-KDT],from a paper from 2002

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Energy models

Model for Sensing:Energy expenditure proportional to (radius) 2 or(radius) 4 of area

Model for Computation:Low energy per clock cycle energy efficiencyEnergy efficiency: energy per instruction

ATMega 128L at 4 MHzConsumption: 16.5mW,Efficiency: 242 MIPS/W or 4 nJ/instruction

ARM Thumb at 4 MHz:Consumption: 75mWEfficiency: 480 MIPS/W or 2.1 nJ/instruction


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Energy models

Model for CommunicationOptimal distance:

= 2

( )2 , where

Ec: base energy required to run thetransmitter/receiver circuitry

e: unit energy required for the transmitter amplifier, itis different for distances bigger than the crossoverdistance

s: power factor 2 or 4 if distance is smaller or greaterthan crossover distance respectively


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Energy models

Node ModelActive (A) and Sleep (S) states

If A:R state: receive and send data

N state: send only if in backlog

Next hop node:Wait (W): either in S or N

Forwarding (F): in R

Use Markov chain model


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MAC Model

Gupta and Kumar define successfultransmission from a to b with max radiorange of r if:

,

, > where k is any other node receiving

, > where l is any other node transmitting

From this an interference model was

derived based on the CSMA/CA of 802.11DCF


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Routing model

Energy consumed for a generic path P

= , ( , )

next hop of i in path P

, ( , ) : energy from node i to node assuming data size is bits and distance

Results:


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System model


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Closed loop model

Case analysis


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Analysis

Total nodes

: bit error rate and packet error rate: = 1 1

Average retransmission for K maxretransmissions

For K = =


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Analysis (cont.)

Total energy per hop = + +

Converged data rate

Where a is aggregation efficiency


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Analysis (cont.)

System lifetime


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Max-min fairness

See book


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The endfor WSN Performance


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Summary

Performance and traffic managementSensors

MAC

Routing

Transport

Energy Models

Analysis


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Documents

WSN Performance