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

1. 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 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

2. Contents • WSN features • Routing protocols • Proposed approach • Performance analysis • Conclusions

3. 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.

4. Definition Task Mng Gateway Gateway 2G/3G/4G N N N N N N N Satellite N N N N N IPvx N N • 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.

5. WSN Applications • WSN features • 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

6. WSN implementation (HW & SW) Location Finding Mobilizer Transceiver Sensor ADC Processor Memory Power Unit • WSN features Functional blocks Network Nodes Gateway

7. WSN features Multi-Hop WSN • Theorem (Stojmenovic, Xu Lin) • Let be the source and the gateway at distance d andthe needed transmitted power satisfies: • This is minimized if: • Otherwise, the overall requested energy can be minimized by choosing equally spaced n-1relay nodes such that n is the integer closer to:

8. Source relay relay Gateway • WSN features Multi-Hop WSN Communication paradigm

9. WSN GATEWAY 3 0 1 Dummy node 2 4 6 Sensor Node 5 • WSN features Multi-Hop WSN 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

10. Protocol design • Routing protocols • 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

11. Network layer Application Transport Network LLC MAC Physical • Routing protocols • 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

12. Network layer • Routing protocols • 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)

13. PROs • Simple implementation • No table updating • No neighbor nodes discovering • Scalability • CONs • Implosion and goodput decreasing • Duplicate packets • No available resource knowledge • Routing protocols Network layer • Flooding • Each node forwards the packets to all the neighbor nodes within its transmission range

14. PROs • Scalability • Adaptability • Modularity • Graceful performance degradation • No implosion • CONs • Long convergence transient time • Possible presence of loops • Packet loss if TTL expires • Signaling overhead • 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)

15. Network layer • Proposed approach • 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.

16. Network layer • Proposed approach • an HELLO reception makes the routing table to be updated and, hence, to select the best next hop by means of the following procedure: • entries with minimum NUMHOPS to the sink are chosen; • among the remaining nodes those with higher AVAILABLE ENERGY are the candidates; • finally, the node minimizing the Euclidean distance to the gateway is selected;

17. HELLO broadcasting • Optimum next hop selection • Packet forwarding • Proposed approach Protocol behavior • Dynamic Gossiping

18. Application scenario 1 2 • 1 • 2 3 • 3 1 2 • 2 • 1 3 • 3 • Performance analysis 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

19. Simulation results • Performance analysis • 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]

20. Power consumption • Performance analysis • 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.

21. Delivering efficiency • Performance analysis • increasing end-to-end packet delivering of dynamic vs static gossiping; • worse delivering efficiency (throughput).

22. Network connectivity • Performance analysis Static gossiping Dynamic gossiping • 50% reduction of power consumption for the most solicited nodes (1,2,3); • lesser spatial variance of energy wasting; • lesser dependency with the topology.

23. 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.

24. 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 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

25. Network layer • Routing protocols • 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