Transcript PPTX - Self-Organization in Sensor and Actor Networks

Self-Organization in Autonomous
Sensor/Actuator Networks
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Dr.-Ing. Falko Dressler
Computer Networks and Communication Systems
Department of Computer Sciences
University of Erlangen-Nürnberg
http://www7.informatik.uni-erlangen.de/~dressler/
[email protected]
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2-1.1
Overview
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Self-Organization
Introduction; system management and control; principles and
characteristics; natural self-organization; methods and techniques
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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
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Coordination and Control: Sensor and Actor Networks
Sensor and actor networks; coordination and synchronization; innetwork operation and control; task and resource allocation
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Bio-inspired Networking
Swarm intelligence; artificial immune system; cellular signaling
pathways
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2-1.2
Mobile Ad Hoc and Sensor Networks
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Mobile Ad Hoc Networks (MANET)
Wireless Sensor Networks (WSN)
2-1.3
Infrastructure-based Wireless Networks
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Typical wireless network are based on infrastructure
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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
Gateways
Server
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IP backbone
Router
2-1.4
Infrastructure-based Wireless Networks – Limitations?
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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
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2-1.5
Possible Applications for Infrastructure-free Networks
Factory floor
automation
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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, …
…
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2-1.6
Further Applications
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Collaborative and Distributed Computing
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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
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Emergency operations
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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
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2-1.7
Solution: (Wireless) Ad Hoc Networks
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Try to construct a network without infrastructure, using networking
abilities of the participants
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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
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2-1.8
Limited range: Multi-hopping
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For many scenarios, communication with peers outside immediate
communication range is required
Direct communication limited because of distance, obstacles, …
 Solution: multi-hop network
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?
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2-1.9
Wireless Mesh Networks
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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
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Quick reconfiguration when the existing path fails due to node failures
Most economical data transfer capability coupled with the freedom of mobility
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2-1.10
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 predeployed infrastructure
Self-organized topology
maintained by the nodes
Network functions
Provided by the
infrastructure
Distributed to all
participating nodes
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2-1.11
Mobility: Suitable, Adaptive Protocols
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In many (not all!) ad hoc network applications, participants move
around
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In cellular network: simply hand over to another base station
In mobile ad hoc networks
(MANET):
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Mobility changes
neighborhood relationship
 Must be compensated for
 E.g., routes in the network
have to be changed
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Complicated by scale
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Large number of such nodes
difficult to support
2-1.12
MANET (Mobile Ad Hoc Network)
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Active IETF working group
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Standardization of IP routing protocol functionality suitable for wireless
routing application within both, static and dynamic topologies
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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
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Support for hybrid mesh infrastructures (e.g., a mixture of fixed and
mobile routers)
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2-1.13
Battery-operated Devices: Energy-efficient Operation
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Often (not always!), participants in an ad hoc network draw energy from
batteries
Desirable: long run time for
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Individual devices
Network as a whole
Energy-efficient networking protocols
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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?
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2-1.14
Problems/Challenges for (Mobile) Ad Hoc Networks
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Without a central infrastructure, things become much more difficult
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Lack of central entity for organization available
 Limited range of wireless communication
 Mobility of participants
 Battery-operated entities
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Without a central entity (like a base station), participants must
organize themselves into a network  Self-organization
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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
2-1.15
Wireless Sensor Networks
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Participants in the previous examples were devices close to a human
user, interacting with humans
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Alternative concept:
Instead of focusing interaction on humans, focus on interacting with
environment
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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
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Wireless sensor networks (WSN)
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2-1.16
Wireless Sensor Networks
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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
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base
station
sensor
node
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2-1.17
Composition of Sensor Nodes – Hardware
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Processor (and memory)
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Radio transceiver
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E.g., Chipcon CC1000 (315/433/868/915 MHz), CC2400 (2.4 GHz)
Battery
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E.g., Atmel ATmega128 microcontroller, 16 MHz, 128 kByte flash
Possibly in combination with energy harvesting
Sensors
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Light, temperature, motion, …
Sensor 1
…
Micro
controller
Radio
transceiver
Sensor n
Memory
Storage
Battery
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2-1.18
Composition of Sensor Nodes – Software
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Event-driven operating principle
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E.g., TinyOS
System component
Event
(Sensor)
…
System
function
…
System
function
Event
(Transceiver)
…
…
Event
(Timer)
New event
(Timer)
New event
(Data packet)
Event handler
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2-1.19
Communication in WSN
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MAC
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Address-based routing
 Data-centric routing
Application layer
Transport layer
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Transport
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Data aggregation
Application
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Network layer
MAC layer
Push vs. pull
Mobility management plane
Network
Power management plane
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Energy-efficiency
Task management plane
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Physical layer
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2-1.20
Communication in WSN
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Push vs. pull
base
station
source
Request (“pull”)
base
station
source 1
source 2
source 2
Periodic transmission (“push”)
base
station
source
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source 2
Transmission (“pull”)
2-1.21
Deployment Options for WSN
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How are sensor nodes deployed in their environment?
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Dropped from aircraft  Random deployment
 Usually uniform random distribution for nodes over finite area is
assumed
 Is that a likely proposition?
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Well planned, fixed  Regular deployment
 E.g., in preventive maintenance or similar
 Not necessarily geometric structure, but that is often a convenient
assumption
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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
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2-1.22
Deployment Options for WSN
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Evaluation criteria? Coverage!
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Radio coverage, i.e. communication related
 Sensor coverage, i.e. application related
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2-1.23
MANET vs. WSN
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Many commonalities
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Self-organization, energy efficiency, (often) wireless multi-hop
Many differences
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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)
2-1.24
WSN Application Examples
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Emergency operations
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Drop sensor nodes from an aircraft over a wildfire
 Each node measures temperature
 Derive a “temperature map”
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Habitat monitoring
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Use sensor nodes to observe wildlife
 E.g., Great Duck Island, ZebraNet
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Precision agriculture
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Bring out fertilizer/pesticides/irrigation only where needed
Logistics
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Equip goods (parcels, containers) with a sensor node
 Track their whereabouts – total asset management
 Note: passive readout might suffice – compare RFIDs
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2-1.25
WSN Application Scenarios
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Home automation and health care
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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)
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2-1.26
Operation and Maintenance
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Type of service of WSN
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Not simply moving bits like another network
 Rather: provide answers (not just numbers)
 Issues like geographic scoping are natural requirements, absent from
other networks
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Feasible and/or practical to maintain sensor nodes?
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E.g., to replace batteries?
 Or: unattended operation?
 Impossible but not relevant? Mission lifetime might be very small
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Energy supply?
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Limited from point of deployment?
 Some form of recharging, energy scavenging from environment?
 E.g., solar cells
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2-1.27
Research Objectives
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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
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Maintainability and fault tolerance
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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, …)
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In-network processing
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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
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2-1.28
Research Objectives
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Quality of service
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Traditional QoS metrics do not apply
 Still, service of WSN must be “good”: Right answers at the right time
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Software management
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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?”
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2-1.29
Self-Organization in Sensor Networks
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2-1.30
Principles and properties
Self-organizing networks
Conventional networks
Local state
Networking functions for
global connectivity and
efficient resource usage
Neighbor
information
Global state
(globally optimized
system behavior)
Probabilistic
methods
Implicit
coordination
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Explicit
coordination
2-1.31
Self-Organization in WSN
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Objectives
Scalability – Management overhead for coordination, support for “unlimited?”
number of nodes
 Lifetime – Application dependent description of the service quality including delays
and availability
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Categorization in two dimensions
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Horizontal, i.e. according to the necessary state information
 Vertical , i.e. according to the network layer
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2-1.32
Horizontal dimension
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Location information
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Absolute or relative position, affiliation to a group of nodes
 Usually requires multi-hop communication
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Neighborhood information
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Local state
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Direct neighborhood, based on local broadcasts
Local system state, environmental factors
Probabilistic algorithms
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No state information required, stochastic processes
location
information
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neighborhood
information
local
state
probabilistic
algorithms
2-1.33
Vertical dimension
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MAC layer
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Application layer
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Network layer
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Topology control, routing tables,
data-centric communication
Transport layer
Network layer
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Application layer
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Coordination and control,
application dependent
requirements (coverage, lifetime)
MAC layer
Cross-layer optimization
(e.g. energy control)
Medium access, local
communication
Control plane
(e.g. mobility
management)
Physical layer
2-1.34
Mapping of Primary Self-Organization Techniques
Location
information
Feedback loops
Neighborhood
information
Local state
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
Probabilistic
techniques
Randomness is often exploited to prevent unwanted
synchronization effects, e.g. for retrial attempts
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Probabilistic
methods
Local interaction
among direct
neighbors within
their wireless
communication
range
Interactions with
the environment
or indirect
interactions with
other nodes
using
environmental
changes
(stigmergy)
Stochastic
methods
2-1.35
Further Studies
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Medium access control (MAC)
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Ad hoc routing
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Classification
Principles of routing protocols
Optimized route stability
Address allocation techniques
Data-centric networking
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Problems and solutions
Case studies (S-MAC, PCM)
Flooding, gossiping, and optimizations
Agent-based techniques
Directed diffusion
Clustering
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Principles and techniques
Case studies (LEACH, HEED)
2-1.36
Summary (what do I need to know)
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Principles of ad hoc and sensor networks
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Commonalities
 Differences
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Capabilities and working behavior of WSN
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Node hardware and software
 Communication principles
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Self-organization in WSN
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Two-dimensions
 Mapping to “classical” self-organization techniques
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2-1.37
References
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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.
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2-1.38