Wireless Sensor Networks 24th Lecture 06.02.2007
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Transcript of Wireless Sensor Networks 24th Lecture 06.02.2007
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University of FreiburgComputer Networks and Telematics
Prof. Christian Schindelhauer
Wireless SensorNetworks
24th Lecture06.02.2007
Christian Schindelhauer
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 2
Overview
Unicast routing in MANETs Energy efficiency & unicast routingGeographical routing
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 3
Energy-efficient unicast: Goals
Particularly interesting performance metric: Energy efficiency
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Goals– Minimize energy/bit
• Example: A-B-E-H– Maximize network
lifetime• Time until first node
failure, loss of coverage, partitioning
Seems trivial – use proper link/path metrics (not hop count) and standard routing
Example: Send data from node A to node H
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 4
Basic options for path metrics
Maximum total available battery capacity
– Path metric: Sum of battery levels
– Example: A-C-F-HMinimum battery cost
routing– Path metric: Sum of
reciprocal battery levels– Example: A-D-H
Conditional max-min battery capacity routing
– Only take battery level into account when below a given level
Minimize variance in power levels
Minimum total transmission power
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 5
A non-trivial path metric
Previous path metrics do not perform particularly well
One non-trivial link weight:
– wij weight for link node i to node j
– eij required energy, some constant, i fraction of battery of node i already used up
Path metric: Sum of link weights– Use path with smallest metric
Properties: Many messages can be send, high network lifetime
– With admission control, even a competitive ratio logarithmic in network size can be shown
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 6
Multipath unicast routing
Instead of only a single path, it can be useful to compute multiple paths between a given source/destination pair
Source Sink
Disjoint paths
Primary path
Secondary path
Source Sink
Disjoint paths
Primary path
Secondary path
Source Sink
Braided paths
Primary pathSource Sink
Braided paths
Primary path
– Multiple paths can be disjoint or braided
– Used simultaneously, alternatively, randomly, …
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 7
Overview
Unicast routing in MANETs Energy efficiency & unicast routingGeographical routing
– Position-based routing– Geocasting
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 8
Geographic routing
Routing tables contain information to which next hop a packet should be forwarded
– Explicitly constructedAlternative: Implicitly infer this information from physical
placement of nodes– Position of current node, current neighbors, destination known –
send to a neighbor in the right direction as next hop– Geographic routing
Options– Send to any node in a given area – geocasting – Use position information to aid in routing – position-based
routing• Might need a location service to map node ID to node
position
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 9
Basics of position-based routing
“Most forward within range r” strategy– Send to that neighbor that realizes the most forward progress
towards destination– NOT: farthest away
from sender!
Nearest node with (any) forward progress– Idea: Minimize transmission power
Directional routing– Choose next hop that is angularly closest to destination– Choose next hop that is closest to the connecting line to
destination– Problem: Might result in loops!
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 10
Problem: Dead ends
Simple strategies might send a packet into a dead end
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 11
Right hand rule to leave dead ends –
GPSR Basic idea to get out of a dead end: Put right hand to the
wall, follow the wall– Does not work if on some inner wall – will walk in circles– Need some additional rules to detect such circles
Geometric Perimeter State Routing (GPSR)– Earlier versions: Compass Routing II, face-2 routing– Use greedy, “most forward” routing as long as possible– If no progress possible: Switch to “face” routing
• Face: largest possible region of the plane that is not cut by any edge of the graph; can be exterior or interior
• Send packet around the face using right-hand rule• Use position where face was entered and destination position
to determine when face can be left again, switch back to greedy routing
– Requires: planar graph! (topology control can ensure that)
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 12
GPSR – Example
Route packet from node A to node Z
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LEnter face
routing
Leave face routing
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 13
Another Approach
is presented in my Inaugural Lecture on
Online Routing in Ad-Hoc-NetzwerkenChristian Schindelhauer
Donnerstag, 15. Februar 2007, 16 h ct
Hörsaal 00-026, Geb. 101
Georges-Köhler-Allee
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 14
Geographic routing without positions –
GEM Apparent contradiction: geographic, but no position?Construct virtual coordinates
– that preserve enough neighborhood information to be useful in geographic routing but do not require actual position determination
Use polar coordinates from a center point
Assign “virtual angle range” to neighbors of a node, bigger radius
Angles are recursively redistributed to children nodes
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 15
Geographic Random Forwarding (GeRaF)
How to combine position knowledge with nodes turning on/off?
– Goal: Transmit message over multiple hops to destination node; deal with topology constantly changing because of on/off node
Idea: Receiver-initiated forwarding– Forwarding node S simply broadcasts a packet, without specifying
next hop node– Some node T will pick it up (ideally, closest to the source) and
forward itProblem: How to deal with multiple forwarders?
– Position-informed randomization: The closer to the destination a forwarding node is, the shorter does it hesitate to forward packet
– Use several rings to make problem easier, group nodes according to distance (collisions can still occur)
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 16
GeRaF – Example
1 D-1
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 17
Overview
Unicast routing in MANETs Energy efficiency & unicast routingMulti-/broadcast routingGeographical routing
– Position-based routing– Geocasting
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 18
Location-based Multicast (LBM)
Geocasting by geographically restricted floodingDefine a “forwarding” zone – nodes in this zone will forward
the packet to make it reach the destination zone– Forwarding zone specified in packet or recomputed along the way– Static zone – smallest rectangle containing original source and
destination zone– Adaptive zone – smallest rectangle containing forwarding node
and destination zone• Possible dead ends again
– Adaptive distances – packet is forwarded by node u if node u is closer to destination zone’s center than predecessor node v (packet has made progress)
Packet is always forwarded by nodes within the destination zone itself
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 19
Determining next hops based on Voronoi
diagramsGoal: Use that neighbor to forward packet that is closest to
destination among all the neighborsUse Voronoi diagram computed for the set of neighbors of
the node currently holding the packet
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 20
Trajectory-based forwarding (TBF)
Think in terms of an “agent”: Should travel around the network, e.g., collecting measurements
– Random forwarding may take a long timeIdea: Provide the agent with a certain trajectory along which
to travel – Described,
e.g., by a simple curve
– Forwardto node closestto this trajectory
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 21
Mobile nodes, mobile sinks
Mobile nodes cause some additional problems
– E.g., multicast tree to distribute readings has to be adapted
Source
Source
Source
Sink movesdownward
Sinkmovesupward
SourceSource
SourceSource
SourceSource
Sink movesdownward
Sinkmovesupward
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 22
Conclusion
Routing exploit various sources of information to find destination of a packet
– Explicitly constructed routing tables– Implicit topology/neighborhood information via positions
Routing can make some difference for network lifetime – However, in some scenarios (streaming data to a single sink),
there is only so much that can be done– Energy efficiency does not equal lifetime, holds for routing as well
Non-standard routing tasks (multicasting, geocasting) require adapted protocols
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 23
Data-centric and content-based
networking
Apart from routing protocols that use a direct identifier of nodes (either unique id or position of a node), networking can talk place based directly on content
Content can be collected from network, processed in the network, and stored in the network
This chapter looks at such content-based networking and data aggregation mechanisms
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 24
Data-centric and content-based
networking
Interaction patterns and programming modelData-centric routingData aggregationData storage
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 25
Desirable interaction paradigm properties
Standard networking interaction paradigms:Client/server, peer-to-peer
– Explicit or implicit partners, explicit cause for communication
Desirable properties for WSN (and other applications)– Decoupling in space – neither sender nor receiver need to know
their partner– Decoupling in time – “answer” not necessarily directly triggered
by “question”, asynchronous communication
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 26
Interaction paradigm: Publish/subscribe
Achieved by publish/subscribe paradigm– Idea: Entities can publish data under certain names– Entities can subscribe to updates of such named data
Conceptually: Implemented by a software bus– Software bus stores subscriptions, published data; names used as
filters; subscribers notified when values of named data changes
Software bus
Publisher 1 Publisher 2
Subscriber 1 Subscriber 2 Subscriber 3
Variations– Topic-based P/S –
inflexible – Content-based P/S
– use general predicates over named data
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 27
Publish/subscribe implementation
optionsCentral server – mostly not applicable Topic-based P/S: group communication protocolsContent-based networking does not directly map to multicast
groups– Needs content-based routing/forwarding for efficient networking
t < 10
t > 20
t < 10
t < 10 ort > 20
t > 20
t > 30
t > 20
t < 10 ort > 20
t = 35!
t = 35!
t = 35!
t = 35!
t = 35!
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 28
Data-centric and content-based
networking
Interaction patterns and programming modelData-centric routingData aggregationData storage
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 29
One-shot interactions with big data sets
Scenario– Large amount of data are to be communicated – e.g., video
picture – Can be succinctly summarized/described
Idea: Only exchange characterization with neighbor, ask whether it is interested in data
– Only transmit data when explicitly requested – Nodes should know about interests of further away nodes
! Sensor Protocol for Information via Negotiation (SPIN)
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 30
SPIN example
ADVADV REQ
DATA
(1) (2) (3)
(4) (5) (6)ADV
ADV
AD
V
REQ
RE
Q
DATA
DA
TA
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 31
Repeated interactions
More interesting: Subscribe once, events happen multiple times
– Exploring the network topology might actually pay off– But: unknown which node can provide data, multiple nodes might
ask for data ! How to map this onto a “routing” problem?
Idea: Put enough information into the network so that publications and subscriptions can be mapped onto each other
– But try to avoid using unique identifiers: might not be available, might require too big a state size in intermediate nodes
! Directed diffusion as one option for implementation– Try to rely only on local interactions for implementation
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 32
Data-centric and content-based
networking
Interaction patterns and programming modelData-centric routingData aggregationData storage
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 33
Data aggregation
Any packet not transmitted does not need energyTo still transmit data, packets need to combine their data
into fewer packets ! aggregation is neededDepending on network, aggregation can be useful or
pointless
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 34
Metrics for data aggregation
Accuracy: Difference between value(s) the sink obtains from aggregated packets and from the actual value (obtained in case no aggregation/no faults occur)
Completeness: Percentage of all readings included in computing the final aggregate at the sink
Latency
Message overhead
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University of FreiburgInstitute of Computer Science
Computer Networks and TelematicsProf. Christian Schindelhauer
Wireless Sensor Networks 06.02.2007 Lecture No. 24 - 35
Partial state records
Partial state records to represent intermediate results– E.g., to compute average, sum and number of previously
aggregated values is required – expressed as <sum,count> – Update rule:– Final result is simply s/c
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36
University of FreiburgComputer Networks and Telematics
Prof. Christian Schindelhauer
Thank youand thanks to Holger Karl for the slides
Wireless Sensor NetworksChristian Schindelhauer
24th Lecture06.02.2007