1. Self-Organization in Autonomous Sensor/Actuator Networks [SelfOrg]
Dr.-Ing. Falko Dressler
Computer Networks and Communication Systems
Department of Computer Sciences
University of Erlangen-Nürnberg

2. Overview
Self-Organization Introduction; system management and control; principles and characteristics; natural self-organization; methods and techniques
Networking Aspects: Ad Hoc and Sensor Networks Ad hoc and sensor networks; self-organization in sensor networks; evaluation criteria; medium access control; ad hoc routing; data-centric networking; clustering
Coordination and Control: Sensor and Actor Networks Sensor and actor networks; coordination and synchronization; in-network operation and control; task and resource allocation
Bio-inspired Networking
Swarm intelligence; artificial immune system; cellular signaling pathways

3. Mobile Ad Hoc and Sensor Networks
Mobile Ad Hoc Networks (MANET)
Wireless Sensor Networks (WSN)

4. Infrastructure-based Wireless Networks
Typical wireless network are based on infrastructure
E.g., GSM, UMTS, WLAN, …
Base stations connected to a wired backbone network
Mobile entities communicate wirelessly to these base stations
Traffic between different mobile entities is relayed by base stations and wired backbone
Mobility is supported by switching from one base station to another
Backbone infrastructure required for administrative tasks
IP backbone
Further networks
Gateways
Server
Router

5. Infrastructure-based Wireless Networks – Limitations?
What if …
No infrastructure is available? – E.g., in disaster areas
It is too expensive/inconvenient to set up? – E.g., in remote, large construction sites
There is no time to set it up? – E.g., in military operations

6. Possible Applications for Infrastructure-free Networks
Factory floor automation
Disaster recovery
Car-to-car communication
Finding out empty parking lots in a city, without asking a server
Search-and-rescue in an avalanche
Personal area networking (watch, glasses, PDA, medical appliance, …)
Military networking: Tanks, soldiers, … …

7. Further Applications Collaborative and Distributed Computing
Temporary communication infrastructure
Quick communication with minimal configuration among a group of people
Examples
A group of researchers who want to share their research findings during a conference
A lecturer distributing notes to a class on the fly
Emergency operations
Rescue, crowd control, and commando operations
Constraints
Self-configuration with minimal overhead
Independency of fixed or central infrastructure
Freedom and flexibility of mobility
Unavailability of conventional communication infrastructure

8. Solution: (Wireless) Ad Hoc Networks
Try to construct a network without infrastructure, using networking abilities of the participants
This is an ad hoc network – a network constructed “on demand”, “for a special purpose”
Simplest example: Laptops in a conference room – a single-hop ad hoc network

9. Limited range: Multi-hopping
For many scenarios, communication with peers outside immediate communication range is required
Direct communication limited because of distance, obstacles, …
Solution: multi-hop network ?

10. Wireless Mesh Networks
Alternate communication infrastructure for mobile or fixed nodes/users
Independence of spectrum reuse constraints and the requirements of network planning of cellular networks
Mesh topology provides many alternate data paths
Quick reconfiguration when the existing path fails due to node failures
Most economical data transfer capability coupled with the freedom of mobility

11. Ad Hoc Networks vs. Infrastructure-based Networks
Prerequisites
Pre-deployed infrastructure, e.g. routers, switches, base stations, servers
None
Node properties
End system only
Duality of end system and network functions
Connections
Wired or wireless
Usually wireless
Topology
Outlined by the pre-deployed infrastructure
Self-organized topology maintained by the nodes
Network functions
Provided by the infrastructure
Distributed to all participating nodes

12. Mobility: Suitable, Adaptive Protocols
In many (not all!) ad hoc network applications, participants move around
In cellular network: simply hand over to another base station
In mobile ad hoc networks (MANET):
Mobility changes neighborhood relationship
Must be compensated for
E.g., routes in the network have to be changed
Complicated by scale
Large number of such nodes difficult to support

13. MANET (Mobile Ad Hoc Network)
Active IETF working group
Standardization of IP routing protocol functionality suitable for wireless routing application within both, static and dynamic topologies
Approaches are intended to be relatively lightweight in nature, suitable for multiple hardware and wireless environments, where MANETs are deployed at the edges of an IP infrastructure
Support for hybrid mesh infrastructures (e.g., a mixture of fixed and mobile routers)

14. Battery-operated Devices: Energy-efficient Operation
Often (not always!), participants in an ad hoc network draw energy from batteries
Desirable: long run time for
Individual devices
Network as a whole
Energy-efficient networking protocols
E.g., use multi-hop routes with low energy consumption (energy/bit)
E.g., take available battery capacity of devices into account
How to resolve conflicts between different optimizations?

15. Problems/Challenges for (Mobile) Ad Hoc Networks
Without a central infrastructure, things become much more difficult
Lack of central entity for organization available
Limited range of wireless communication
Mobility of participants
Battery-operated entities
Without a central entity (like a base station), participants must organize themselves into a network  Self-organization
Pertains to (among others)
Medium access control – no base station can assign transmission resources, must be decided in a distributed fashion
Finding a route from one participant to another

16. Wireless Sensor Networks
Participants in the previous examples were devices close to a human user, interacting with humans
Alternative concept:
Instead of focusing interaction on humans, focus on interacting with environment
Network is embedded in environment
Nodes in the network are equipped with sensing and actuation to measure/influence environment
Nodes process information and communicate it wirelessly
Wireless sensor networks (WSN)

17. Wireless Sensor Networks
Multiple roles can be distinguished
Sensors – measure physical phenomena, sources of measurement data
Base stations – analyze and post-process data, sinks for measurement data
Actuators – perform actuation in response to received data
Processing elements – pre-processing of transmitted data
base station
sensor
node

18. Composition of Sensor Nodes – Hardware
Processor (and memory)
E.g., Atmel ATmega128 microcontroller, 16 MHz, 128 kByte flash
Radio transceiver
E.g., Chipcon CC1000 (315/433/868/915 MHz), CC2400 (2.4 GHz)
Battery
Possibly in combination with energy harvesting
Sensors
Light, temperature, motion, …
Sensor 1
Micro controller
Radio transceiver …
Sensor n
Memory
Storage
Battery

19. Composition of Sensor Nodes – Software
Event-driven operating principle
E.g., TinyOS
System component
Event
(Sensor)
System function
New event
(Timer) …
Event
(Timer) … … …
System function
New event
(Data packet)
Event
(Transceiver)
Event handler

20. Communication in WSN MAC Network Transport Application
Energy-efficiency
Network
Address-based routing
Data-centric routing
Transport
Data aggregation
Application
Push vs. pull
Application layer
Task management plane
Transport layer
Mobility management plane
Power management plane
Network layer
MAC layer
Physical layer

21. Communication in WSN Push vs. pull base station source 2 source
Request (“pull”)
source 1
source 2
Periodic transmission (“push”)
base station
source
source 2
Transmission (“pull”)

22. Deployment Options for WSN
How are sensor nodes deployed in their environment?
Dropped from aircraft  Random deployment
Usually uniform random distribution for nodes over finite area is assumed
Is that a likely proposition?
Well planned, fixed  Regular deployment
E.g., in preventive maintenance or similar
Not necessarily geometric structure, but that is often a convenient assumption
Mobile sensor nodes
Can move to compensate for deployment shortcomings
Can be passively moved around by some external force (wind, water)
Can actively seek out “interesting” areas

23. Deployment Options for WSN
Evaluation criteria? Coverage!
Radio coverage, i.e. communication related
Sensor coverage, i.e. application related

24. MANET vs. WSN Many commonalities Many differences
Self-organization, energy efficiency, (often) wireless multi-hop
Many differences
Applications, equipment: MANETs more powerful (read: expensive) equipment assumed, often “human in the loop”-type applications, higher data rates, more resources
Application-specific: WSNs depend much stronger on application specifics; MANETs comparably uniform
Environment interaction: core of WSN, absent in MANET
Scale: WSN might be much larger (although contestable)
Energy: WSN tighter requirements, maintenance issues
Dependability/QoS: in WSN, individual node may be dispensable (network matters), QoS different because of different applications
Data centric vs. id-centric networking
Mobility: different mobility patterns like (in WSN, sinks might be mobile while nodes are usually static)

25. WSN Application Examples
Emergency operations
Drop sensor nodes from an aircraft over a wildfire
Each node measures temperature
Derive a “temperature map”
Habitat monitoring
Use sensor nodes to observe wildlife
E.g., Great Duck Island, ZebraNet
Precision agriculture
Bring out fertilizer/pesticides/irrigation only where needed
Logistics
Equip goods (parcels, containers) with a sensor node
Track their whereabouts – total asset management
Note: passive readout might suffice – compare RFIDs

26. WSN Application Scenarios
Home automation and health care
Smart environment (smart sensor nodes and actuators in appliances learn to provide needed service)
Post-operative or intensive care (telemonitoring of physiologic data)
Long-term surveillance of chronically ill patients or the elderly (tracking and monitoring)

27. Operation and Maintenance
Type of service of WSN
Not simply moving bits like another network
Rather: provide answers (not just numbers)
Issues like geographic scoping are natural requirements, absent from other networks
Feasible and/or practical to maintain sensor nodes?
E.g., to replace batteries?
Or: unattended operation?
Impossible but not relevant? Mission lifetime might be very small
Energy supply?
Limited from point of deployment?
Some form of recharging, energy scavenging from environment?
E.g., solar cells

28. Research Objectives Network lifetime
The network should fulfill its task as long as possible – definition depends on application
Lifetime of individual nodes relatively unimportant
But often treated equivalently
Maintainability and fault tolerance
WSN has to adapt to changes, self-monitoring, adapt operation
Incorporate possible additional resources, e.g., newly deployed nodes
Be robust against node failures (running out of energy, physical destruction, …)
In-network processing
Again, the network should fulfill a given task on behalf of an external user
Move necessary computations into the network  reduction of communication costs, speedup of operations
Definition of network lifetime as a homework?

29. Research Objectives Quality of service Software management
Traditional QoS metrics do not apply
Still, service of WSN must be “good”: Right answers at the right time
Software management
Programming and re-programming of sensor nodes according to the current application demands
Debugging of distributed heterogeneous sensor nodes?
From ZebraNet: “how to reboot a zebra?”
Definition of network lifetime as a homework?

30. Self-Organization in Sensor Networks

31. Principles and properties
Self-organizing networks
Conventional networks
Local state
Networking functions for global connectivity and efficient resource usage
Global state (globally optimized system behavior)
Neighbor information
Probabilistic methods
Implicit coordination
Explicit coordination

32. Self-Organization in WSN
Objectives
Scalability – Management overhead for coordination, support for “unlimited?” number of nodes
Lifetime – Application dependent description of the service quality including delays and availability
Categorization in two dimensions
Horizontal, i.e. according to the necessary state information
Vertical , i.e. according to the network layer

33. Horizontal dimension Location information Neighborhood information
Absolute or relative position, affiliation to a group of nodes
Usually requires multi-hop communication
Neighborhood information
Direct neighborhood, based on local broadcasts
Local state
Local system state, environmental factors
Probabilistic algorithms
No state information required, stochastic processes
- table-driven routing - medium access control
- data centric routing - task allocation
collision avoidance
gossiping
- topology control - clustering
location information
neighborhood information
local state
probabilistic algorithms

34. Vertical dimension MAC layer Network layer Application layer
Medium access, local communication
Network layer
Topology control, routing tables, data-centric communication
Application layer
Coordination and control, application dependent requirements (coverage, lifetime)
Control plane
(e.g. mobility management)
Application layer
Transport layer
Cross-layer optimization (e.g. energy control)
Network layer
MAC layer
Physical layer

35. Mapping of Primary Self-Organization Techniques
Location information
Neighborhood information
Local state
Probabilistic methods
Feedback loops
Feedback is provided by observing and evaluating system parameters; this can be done either by local means (sensor readings) or with external help of neighboring systems
Interactions
Information exchange among remote nodes using routing techniques
Local interaction among direct neighbors within their wireless communication range
Interactions with the environment or indirect interactions with other nodes using environmental changes (stigmergy)
Probabilistic techniques
Randomness is often exploited to prevent unwanted synchronization effects, e.g. for retrial attempts
Stochastic methods

36. Further Studies Medium access control (MAC) Ad hoc routing
Problems and solutions
Case studies (S-MAC, PCM)
Ad hoc routing
Classification
Principles of routing protocols
Optimized route stability
Address allocation techniques
Data-centric networking
Flooding, gossiping, and optimizations
Agent-based techniques
Directed diffusion
Clustering
Principles and techniques
Case studies (LEACH, HEED)

37. Summary (what do I need to know)
Principles of ad hoc and sensor networks
Commonalities
Differences
Capabilities and working behavior of WSN
Node hardware and software
Communication principles
Self-organization in WSN
Two-dimensions
Mapping to “classical” self-organization techniques

38. References
I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: a survey," Computer Networks, vol. 38, pp , 2002.
D. Culler, D. Estrin, and M. B. Srivastava, "Overview of Sensor Networks," Computer, vol. 37 (8), pp , August 2004.
I. Dietrich and F. Dressler, "On the Lifetime of Wireless Sensor Networks," University of Erlangen, Dept. of Computer Science 7, Technical Report 04/06, December 2006.
F. Dressler, "Self-Organization in Ad Hoc Networks: Overview and Classification," University of Erlangen, Dept. of Computer Science 7, Technical Report 02/06, March 2006.
H. Karl and A. Willig, Protocols and Architectures for Wireless Sensor Networks, Wiley, 2005.
C. Prehofer and C. Bettstetter, "Self-Organization in Communication Networks: Principles and Design Paradigms," IEEE Communications Magazine, vol. 43 (7), pp , July 2005.
C. S. Raghavendra, K. M. Sivalingam, and T. Znati, Wireless Sensor Networks. Boston, Kluwer Academic Publishers, 2004.
H. Zhang and J. C. Hou, "Maintaining Sensing Coverage and Connectivity in Large Sensor Networks," Wireless Ad Hoc and Sensor Networks: An International Journal, vol. 1 (1-2), pp , January 2005.