cost 289 7 th mcm - münchen march, 7-8 2005 1/24 energy efficient routing algorithms for...
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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
chiti@lenst.det.unfi.it, collodi@ing.unifi.it, fantacci@lenst.det.unfi.it, g.giorgetti@ing.unifi.it, antonio.manes@unifi.it, tarchi@lenst.det.unifi.it
COST 289 7th MCM - München March, 7-8 2005 2/24
ContentsContents
1. WSN features
2. Routing protocols
3. Proposed approach
4. Performance analysis
5. Conclusions
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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.
COST 289 7th MCM - München March, 7-8 2005 4/24
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
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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
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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
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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
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Gateway
Source
relay
relay
Multi-Hop WSNMulti-Hop WSN
Communication paradigm
1. WSN features
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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
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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
2. Routing protocols
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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
2. Routing protocols
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Network layerNetwork 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)
2. Routing protocols
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Flooding
Each node forwards the packets to all the neighbor nodes within its transmission range
Network layerNetwork layer
PROs
Simple implementation
No table updating
No neighbor nodes discovering
Scalability
CONs
Implosion and goodput decreasing
Duplicate packets
No available resource knowledge
2. Routing protocols
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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)
Network layerNetwork layer
PROs
Scalability
Adaptability
Modularity
Graceful performance degradation
No implosion
2. Routing protocols
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Network layerNetwork 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.
3. Proposed approach
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Network layerNetwork 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;
3. Proposed approach
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Dynamic Gossiping
HELLO broadcastingOptimum next hop selectionPacket forwarding
3. Proposed approach
Protocol behaviorProtocol behavior
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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
4. Performance analysis
1 2
3
1 2
3
1 2
3
2
3
1
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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]
4. Performance analysis
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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.
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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
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eff
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nc
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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
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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
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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.
COST 289 7th MCM - München March, 7-8 2005 24/24
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
chiti@lenst.det.unfi.it, collodi@ing.unifi.it, fantacci@lenst.det.unfi.it, g.giorgetti@ing.unifi.it, antonio.manes@unifi.it, tarchi@lenst.det.unifi.it
COST 289 7th MCM - München March, 7-8 2005 25/24
Network layerNetwork 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-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
2. Routing protocols
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