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Energy Efficient Routing Algorithms
for Application to Agro-Food
Wireless Sensor Networks
Francesco 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]
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Contents
1. WSN features
2. Routing protocols
3. Proposed approach
4. Performance analysis
5. Conclusions
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Research involvements
“GoodFood” 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.
“NEWCOM” 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.
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1. WSN features
Definition
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.
N
N
IPvx
Task Mng
Satellite
N
N
Gateway
N
N
2G/3G/
4G
N
N
N
Gateway
N
N
N
N
N
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1. WSN features
WSN Applications
• Military, Environmental, Health, Home, Space Exploration, Chemical
Processing, Disaster Relief
Sensor types
• Seismic, Low sampling rate magnetic, Thermal, Visual, Infrared, Acoustic,
Radar
Sensor tasks
• 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
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1. WSN features
WSN implementation (HW & SW)
Functional blocks
Network Nodes
Location Finding
Sensor ADC
Mobilizer
Processor Memory
Transceiver
Gateway
Power Unit
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1. WSN features
Multi-Hop WSN
Theorem (Stojmenovic, Xu Lin)
Let be the source and the gateway at distance d and the
needed transmitted power satisfies:
ud   ad   c
This is minimized if:
1


c
d
1 


a
1

2

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
 a  1 
d
 c 
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1. WSN features
Multi-Hop WSN
Communication paradigm
Source
relay
relay
Gateway
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1. WSN features
Multi-Hop WSN
Flexibility:
 Adaptability
 Re-configurability
 Robustness
 Scalability

Power saving
Untethered
3
1
Dummy node
2
6
No nw planning
•
•
•

0
Energy-awareness
•
•

WSN
GATEWAY
4
Sensor Node
5
Random deployment
Self-organization
Re-configuration
Cooperative approach
•
•
Distributed procedures
Data processing
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2. Routing protocols
Protocol 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
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2. Routing protocols
Network layer
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
Application
Transport
Network
LLC
MAC
Physical
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2. Routing protocols
Network layer
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)
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2. Routing protocols
Network layer
Flooding
Each node forwards the packets to all the neighbor
nodes within its transmission range
PROs
CONs
 Simple implementation
 No table updating
 No neighbor nodes
discovering
 Scalability
 Implosion and goodput
decreasing
 Duplicate packets
 No available resource
knowledge
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2. Routing protocols
Network layer
Gossiping
Each node sends a packet only to one neighbor node
chosen according to a suited criterion (random or metric
based)
PROs
CONs
 Scalability
 Long convergence transient
time
 Adaptability
 Possible presence of loops
 Modularity
 Graceful performance
degradation
 Packet loss if TTL expires
 Signaling overhead
 No implosion
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3.
Proposed approach
Network layer

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.
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3.
Proposed approach
Network layer

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;
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3.
Proposed approach
Protocol behavior
Dynamic Gossiping
Packet
Optimum
next hop selection
HELLOforwarding
broadcasting
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4.
Performance analysis
Application 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
2
1
1
3
2
3
1
2
3
3
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4.
Performance analysis
Simulation 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]
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4.
Performance analysis
Power consumption
6X6
9X4
12000
12000
8000
4000
8000
Flooding
Random G
Proposed G
UE
UE
Flooding
Random G
Proposed G
4000
0
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
time [slot]
5
6
7
8
9
10
time [slot]

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.
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4.
Performance analysis
Delivering efficiency
6X6
9X4
1
Flooding
Random G
Proposed G
0,5
Delivery efficiency
Delivery efficiency
1
0
Flooding
Random G
Proposed G
0,5
0
0
1
2
3
4
5
6
7
8
9
10 11
time [slot]
0
1
2
3
4
5
6
7
8
9
10 11
time [slot]

increasing end-to-end packet delivering of dynamic vs static gossiping;

worse delivering efficiency (throughput).
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4.
Performance analysis
Network connectivity
Static gossiping
Dynamic gossiping
Topology
Node 1
Node 2
Node 3
Topology
Node 1
Node 2
Node 3
6×6
105
35
105
6×6
82
76
85
9×4
42
21
182
9×4
86
70
89

50% reduction of power consumption for the most solicited nodes (1,2,3);

lesser spatial variance of energy wasting;

lesser dependency with the topology.
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5.
Conlusions

Pervasive use of AmI concepts in agriculture, relying on highlyintegrated 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.
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Energy Efficient Routing Algorithms
for Application to Agro-Food
Wireless Sensor Networks
Francesco 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]
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2. Routing protocols
Network layer
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-tomany 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
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