COST 289 7 th MCM - München March, 7-8 2005 1/24 Energy Efficient Routing Algorithms for Application to Agro-Food Wireless Sensor Networks Francesco Chiti*,

COST 289 7th MCM - München March, 7-8 2005 1/24

Energy Efficient Routing Algorithms for Application to Agro-Food Wireless Sensor

NetworksFrancesco Chiti*, Andrea De Cristofaro*, Romano Fantacci *, Daniele Tarchi*,

Giovanni Collodi§, Gianni Giorgetti*, Antonio Manes▲

*Dipartimento di Elettronica e Telecomunicazioni, ▲Dipartimento di Energetica, §Consorzio MIDRA

Università di Firenze -Via di S. Marta, 3 - 50139 Firenze, Italy

[email protected], [email protected], [email protected], [email protected], [email protected], [email protected]


ContentsContents

1. WSN features

2. Routing protocols

3. Proposed approach

4. Performance analysis

5. Conclusions


Research involvementsResearch involvements

““GoodFoodGoodFood” EU Integrated Project” EU Integrated Project

• Development of novel solutions for the safety and quality assurance, along the food chain within the agro-food industry.

• Work Package 7 aims at investigating integrated solutions according to the AmI concepts, allowing full interconnection and communication of multi-sensing systems.

““NEWCOMNEWCOM” EU NoE” EU NoE

Project A is addressed to “Ad Hoc and Sensor networks” with regards to:

Cross-layer design of sensor networks;

Simulation models and architectures for cross-layered sensor networks.


DefinitionDefinition1. WSN features

Wireless Sensor Network (WSN) is composed of a large number of sensor nodes (N) that are densely deployed either inside the investigated phenomenon or very close to it.

NNNN

NN

NN

NN

NN

NN

NNNN

NN

NN

NN

NN

NN

GatewayGateway

GatewayGateway

Task MngTask Mng

IPvIPvxx

SatelliteSatellite

2G/2G/3G/4G3G/4G


WSN ApplicationsWSN Applications

• Military, Environmental, Health, Home, Space Exploration, Chemical Processing, Disaster Relief

Sensor typesSensor types

Sensor tasksSensor tasks

• Seismic, Low sampling rate magnetic, Thermal, Visual, Infrared, Acoustic, Radar

• Temperature, Humidity, Lightning Condition, Pressure, Soil Makeup, Noise Levels

• Vehicular, Movement, Presence or Absence of certain types of objects, Mechanical stress levels on attached Objects, current characteristics (Speed, Direction, Size) of an object

1. WSN features


WSN implementation (HW & SW)WSN implementation (HW & SW)

Network Nodes

Gateway

Functional blocks

Location Finding

TransceiverSensor ADC

Power Unit

Processor Memory

Mobilizer

1. WSN features


Theorem (Stojmenovic, Xu Lin)

Let be the source and the gateway at distance d and the needed transmitted power satisfies:

This is minimized if:

Otherwise, the overall requested energy can be minimized by choosing equally spaced n-1 relay nodes such that n is the integer closer to:

1

121

a

cd

1

1

c

ad

caddu

Multi-Hop WSNMulti-Hop WSN1. WSN features


Gateway

Source

relay

relay

Multi-Hop WSNMulti-Hop WSN

Communication paradigm

1. WSN features


Multi-Hop WSNMulti-Hop WSN

Dummy node

Sensor Node

0 1

2

3

4

5

6

WSN

GATEWAY

Flexibility: Adaptability Re-configurability Robustness Scalability

Energy-awareness• Power saving• Untethered

No nw planning• Random deployment• Self-organization• Re-configuration

Cooperative approach• Distributed procedures• Data processing

1. WSN features


Protocol designProtocol design

Ad Hoc protocol are often unsuitable because:

• Number of sensor nodes can be several order of magnitude higher

• Sensor nodes are densely deployed and are prone to failures

• The topology of a sensor network changes very frequently due to node mobility and node failure

• Sensor nodes are power, computational capacities and memory limited

• May not have global ID like IP address

• Need tight integration with sensing tasks

Specific cross-layer protocols design with an across layers information passing and functionalities adaptation to channel and load variations



Network layerNetwork layer

Physical

MAC

LLC

Network

Transport

Application

This layer is in charge of discovering the best path between a couple of nodes (Sender and Destination), relaying on the following characteristics:

• Sensor networks are mostly data centric

• An ideal sensor network has attribute based addressing and location awareness

• Data aggregation may be joined with a collaborative effort

• Power efficiency is always a key factor




Metrics considered to develop energy efficient routing algorithms:

• Power Available (PA) at each node

• Energy () needed to send a packet over a link

Resorting to these, there 4 possible approaches to choose the proper path:

Maximum PA Route (PAs summation)

Minimum Energy Route ( summation)

Minimum Hop Route (number of hops)

Maximum Minimum PA Route (minimum of maximum PA)



Flooding

Each node forwards the packets to all the neighbor nodes within its transmission range


PROs

Simple implementation

No table updating

No neighbor nodes discovering

Scalability

CONs

Implosion and goodput decreasing

Duplicate packets

No available resource knowledge



CONs

Long convergence transient time

Possible presence of loops

Packet loss if TTL expires

Signaling overhead

Gossiping

Each node sends a packet only to one neighbor node chosen according to a suited criterion (random or metric based)


PROs

Scalability

Adaptability

Modularity

Graceful performance degradation

No implosion




Dynamic table driven and link state

Each idle node periodically broadcasts an HELLO message with fields:

• SOURCEID: unique hardware identifier;

• NUMHOPS: number of hops to reach the sink;

• COORDINATES: location with respect to the gateway;

• AVAILABLE ENERGY: i.e., the energy that is still available to transmit and process the packets.




an HELLO reception makes the routing table to be updated and, hence, to select the best next hop by means of the following procedure:

i. entries with minimum NUMHOPS to the sink are chosen;

ii. among the remaining nodes those with higher AVAILABLE ENERGY are the candidates;

iii. finally, the node minimizing the Euclidean distance to the gateway is selected;



Dynamic Gossiping

HELLO broadcastingOptimum next hop selectionPacket forwarding


Protocol behaviorProtocol behavior


Application scenarioApplication scenario

Field-trial of the University of Florence’s Montepaldi farm for the Wine Chain monitoring (wine production and ageing chain steps)

Sensed parameters: air, ground, plants (leaf temperature, stem growth, xylem flux and pathogenic diseases), fermentation and ageing issues


1 2

3

1 2

3

1 2

3

2

3

1


Simulation resultsSimulation results

Reference metrics:

power consumption or, equivalently node lifetime especially for the most solicited nodes (connectivity);

end-to-end throughput or delivering efficiency;

end-to-end packet delivering delay.

Compared approaches:

basic flooding routing scheme;

a static gossiping: proactive link state evaluation;

proposed dynamic gossiping.

Utilization of Network Protocol Simulator (NePSing): a C++ framework for modeling time-discrete, asynchronous systems

[“the NePSing Project,” 2004. [Online]. Available: http://nepsing.sourceforge.net]



Power consumptionPower consumption4. Performance analysis

6 X 6

0

4000

8000

12000

1 2 3 4 5 6 7 8 9 10

time [slot]

UE

Flooding

Random G

Proposed G

9 X 4

0

4000

8000

12000

1 2 3 4 5 6 7 8 9 10

time [slot]

UE

Flooding

Random G

Proposed G

remarkable gain of the dynamic gossiping vs flooding scheme;

same behavior of the static and the dynamic gossiping;

Increasing signaling overhead (slightly worse performance) especially in an asymmetric network topology, i.e., in a rectangular-wise grid if compared with a square-wise.


Delivering efficiencyDelivering efficiency4. Performance analysis

increasing end-to-end packet delivering of dynamic vs static gossiping;

worse delivering efficiency (throughput).

6 X 6

0

0,5

1

0 1 2 3 4 5 6 7 8 9 10 11

time [slot]

De

liv

ery

eff

icie

nc

y

Flooding

Random G

Proposed G

9 X 4

0

0,5

1

0 1 2 3 4 5 6 7 8 9 10 11

time [slot]

De

liv

ery

eff

icie

nc

y

Flooding

Random G

Proposed G


Network connectivityNetwork connectivity4. Performance analysis

50% reduction of power consumption for the most solicited nodes (1,2,3);

lesser spatial variance of energy wasting;

lesser dependency with the topology.

Topology Node 1 Node 2 Node 3

6 × 6 105 35 105

9 × 4 42 21 182

Static gossiping

Topology Node 1 Node 2 Node 3

6 × 6 82 76 85

9 × 4 86 70 89

Dynamic gossiping


5. Conlusions

Pervasive use of AmI concepts in agriculture, relying on highly-integrated WSNs to create a sensitive and responsive environment;

Proposal of an energy efficient dynamic routing protocol;

Performance analysis:

• signaling overhead, delay and throughput;

• Power consumption;

• Network life-time (connectivity).

Further developments:

• On-board implementation and testing;

• Cross-layer integration with energy efficient Link Layer schemes (e.g., SMAC);

• Management of differentiated services.

Francesco Chiti, Andrea De Cristofaro, Romano Fantacci, Daniele Tarchi, Giovanni Collodi, Gianni Giorgetti and Antonio Manes, “Energy Efficient Routing Algorithms for Application to Agro-Food Wireless Sensor Networks” in Proc. of IEEE ICC 2005.


Energy Efficient Routing Algorithms for Application to Agro-Food Wireless Sensor

NetworksFrancesco Chiti*, Andrea De Cristofaro*, Romano Fantacci *, Daniele Tarchi*,

Giovanni Collodi§, Gianni Giorgetti*, Antonio Manes▲

*Dipartimento di Elettronica e Telecomunicazioni, ▲Dipartimento di Energetica, §Consorzio MIDRA

Università di Firenze -Via di S. Marta, 3 - 50139 Firenze, Italy

[email protected], [email protected], [email protected], [email protected], [email protected], [email protected]



Quality of Service oriented routing protocols

• Routes based on QoS requirements without periodic table updating (no need for routing tables )

• Flexibile, robust and modular

• One-to-one, many-to-one, one-to-many, and many-to-many communications

Types of Streams

Type 1: Time critical and loss sensitive

Type 2: time critical but not loss sensitive data

Type 3: loss sensitive data that is not time critical

Type 4: neither time critical nor loss sensitive


Documents

COST 289 7 th MCM - München March, 7-8 2005 1/24 Energy Efficient Routing Algorithms for Application to Agro-Food Wireless Sensor Networks Francesco Chiti*,