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[SelfOrg] 2-1.1
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
http://www7.informatik.uni-erlangen.de/~dressler/
[SelfOrg] 2-1.2
Overview
Self-OrganizationIntroduction; system management and control; principles and characteristics; natural self-organization; methods and techniques
Networking Aspects: Ad Hoc and Sensor NetworksAd 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 NetworksSensor and actor networks; coordination and synchronization; in-network operation and control; task and resource allocation
Bio-inspired NetworkingSwarm intelligence; artificial immune system; cellular signaling pathways
[SelfOrg] 2-1.3
Mobile Ad Hoc and Sensor Networks
Mobile Ad Hoc Networks (MANET) Wireless Sensor Networks (WSN)
[SelfOrg] 2-1.4
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
ServerRouter
Furth
er
network
s
Gateways
[SelfOrg] 2-1.5
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
[SelfOrg] 2-1.6
Possible Applications for Infrastructure-free Networks
Factory floor automation
Disaster recovery Car-to-car communication
ad ho
c
ad ho
c
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, … …
[SelfOrg] 2-1.7
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
[SelfOrg] 2-1.8
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
[SelfOrg] 2-1.9
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
?
[SelfOrg] 2-1.10
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
[SelfOrg] 2-1.11
Ad Hoc Networks vs. Infrastructure-based Networks
Infrastructure-based network
Ad hoc network
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
[SelfOrg] 2-1.12
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
[SelfOrg] 2-1.13
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, suitablefor 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)
[SelfOrg] 2-1.14
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?
[SelfOrg] 2-1.15
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
[SelfOrg] 2-1.16
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)
[SelfOrg] 2-1.17
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
basestation
sensornode
[SelfOrg] 2-1.18
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, …
Micro controller
Memory
Storage
Radio transceiver
Battery
Sensor 1
Sensor n…
[SelfOrg] 2-1.19
Composition of Sensor Nodes – Software
Event-driven operating principle E.g., TinyOS
System component
Event(Sensor)
Event(Timer)
Event(Transceiver)
…
System function
…System function
Event handler
New event(Data packet)
New event(Timer)
…
…
[SelfOrg] 2-1.20
Communication in WSN
MAC Energy-efficiency
Network Address-based routing Data-centric routing
Transport Data aggregation
Application Push vs. pull
Application layer
Transport layer
Network layer
MAC layer
Physical layer
Pow
er managem
ent plane
Mobility m
anagement plane
Task m
anagement plane
[SelfOrg] 2-1.21
Communication in WSN
Push vs. pull
basestation
source 1
basestation
source
basestation
source
Request (“pull”)
Transmission (“pull”)
Periodic transmission (“push”)
source 2
source 2
source 2
[SelfOrg] 2-1.22
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
[SelfOrg] 2-1.23
Deployment Options for WSN
Evaluation criteria? Coverage! Radio coverage, i.e. communication related Sensor coverage, i.e. application related
[SelfOrg] 2-1.24
MANET vs. WSN
Many commonalities 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)
[SelfOrg] 2-1.25
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
[SelfOrg] 2-1.26
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)
[SelfOrg] 2-1.27
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
[SelfOrg] 2-1.28
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
[SelfOrg] 2-1.29
Research Objectives
Quality of service 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?”
[SelfOrg] 2-1.30
Self-Organization in Sensor Networks
[SelfOrg] 2-1.31
Principles and properties
Networking functions for global connectivity and efficient resource usage
Local state
Neighbor information
Probabilistic methods
Global state (globally optimized system behavior)
Self-organizing networks Conventional networks
Implicit coordination
Explicit coordination
[SelfOrg] 2-1.32
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
[SelfOrg] 2-1.33
Horizontal dimension
Location 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
locationinformation
neighborhoodinformation
probabilisticalgorithms
- topology contro
l
- clusterin
g- ta
ble-driven ro
uting
- medium access contro
l
- data ce
ntric ro
uting
- task
allocatio
n
localstate
- gossiping
- collis
ion avoidance
[SelfOrg] 2-1.34
Vertical dimension
MAC layer Medium access, local
communication
Network layer Topology control, routing tables,
data-centric communication
Application layer Coordination and control,
application dependent requirements (coverage, lifetime)
Application layer
Transport layer
Network layer
MAC layer
Physical layer
Control plane(e.g. mobilitymanagement) C
ross-layer optimization
(e.g. energy control)
[SelfOrg] 2-1.35
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
[SelfOrg] 2-1.36
Further Studies
Medium access control (MAC) 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)
[SelfOrg] 2-1.37
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
[SelfOrg] 2-1.38
References
I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "Wireless sensor networks: a survey," Computer Networks, vol. 38, pp. 393-422, 2002.
D. Culler, D. Estrin, and M. B. Srivastava, "Overview of Sensor Networks," Computer, vol. 37 (8), pp. 41-49, 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. 78-85, 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. 89-123, January 2005.