Transcript Slide 1

Wireless Sensor Networks
Aν. Καθηγητής Συμεών Παπαβασιλείου
Εθνικό Μετσόβιο Πολυτεχνείο
Τμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών
Υπολογιστών
[email protected]
Τηλ: 210 772-2550
Data gathering in WSN
Issues to consider
• Delay:
Some application require data gathering within specific timeframe
• Energy:
The total energy consumption needs to be minimized in order to
increase the network lifetime
Network Lifetime: Time until
 First node dies
 Network looses its connectivity
 Network coverage falls under predefined threshold
• Accuracy:
Different applications require different level of accuracy
• Network Coverage:
All points within the network that the sensors are deployed need
to be covered by at least one sensor node
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Data aggregation
Sink
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Data gathering approaches
• The data gathering approaches are classified based
on their characteristics. Rely upon:
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Network structure
Routing dependence
Nature of sent data
Frequency of data transmissions
Network connectivity
• Simplest way to sent data: Direct communication
to the sink
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Hierarchical – no hierarchical approaches
• Given the network structure the data gathering strategies
are divided:
 Hierarchical
 No Hierarchical
• Hierarchical are further divided to:
 Cluster-based
 Chain-based
 Tree-based
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Cluster based I
• Sensor nodes are divided into
groups –clusters- based on their
relative position
• A node takes the leader role in
each group – cluster head
• At each gathering round nodes
send their data to cluster head
• The cluster head sends the
gathered data to the sink
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Cluster based II
• The cluster head consumes greater energy
• Therefore, nodes take turns in becoming cluster heads
are often
• Delay is incurred because of the data gathering in the
clusters
• Low complexity in cluster creation
• Significant energy benefits
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Cluster based III
• Representative protocols:
 Low-Energy Adaptive Clustering Hierarchy (LEACH) (Heinzelman,
Chandrakasan and Balakrishnan, 2000)
 LEACH-C, centralized version of LEACH (Heinzelman 2000)
 E-LEACH, enhanced version of LEACH (Pham, Kim and Moh, 2004)
 Δημιουργία ομάδων αισθητήρων σε συνδυασμό με ενδιάμεσα
σημεία αναμετάδοσης (Choi, Shah and Das, 2004)
 Clustering-Based Maximum Lifetime Data Aggregation, CMLDA
(Dasgupta, Kalpakis and Namjoshi 2003)
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Chain Based I
• Sensor nodes form a chain
•In each gathering round every
node sends its data to its
neighbor in the chain closer to
the sink
• Data in each node are
aggregated
• The final node sends the
aggregated data to the sink
• Chain is often reconfigured
• Energy savings but also
increased delay
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Chain Based II
• Representative protocols:
 Simplest protocol is the linear
 Power-Efficient Gathering in Sensor Information Systems,
PEGASIS (Lindsey, Raghavendra and Sivalingam, 2002)
 Code Division Multiple Access, CDMA (Lindsey, Raghavendra
and Sivalingam 2002)
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Tree Based I
• A data gathering tree is form that
spans over the whole network
• Usually, the sink initiates the
process
• Every node is connected to the
tree either as inner node or as
leaf
• Every parent node wait the data
from its children nodes and send
an aggregated packet to the
higher level (i.e. its parent)
•Energy savings but also
increased delay
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Tree Based II
• Representative protocols:
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Efficient Data GathEring protocol, EDGE (Thepvilojanapong,
Tobe and Sezaki 2005)
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Power Efficient Data gathering and Aggregation Protocol,
PEDAP (Tan and Körpeo 2003)
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Non hierarchical approaches
• Flooding: Every sensor node sends its packets to
all of its neighbors
• Great energy cost
• Excessive packet creation
• Gossiping: Every sensor node sends its packets to
a group of its neighbors
• Solves the flooding drawbacks
• Directed diffusion (Intanagonwiwat, Govindan and
Estrin (2000)
• Sink asks for data
• Data packets are created
• More efficient paths are reinforced
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Routing independent propabilistic methods I
• Many strategies are routing dependent
• However, some approaches are routing independent
and can be combined with energy efficient routing
for greater energy earnings
• The decision for data aggregation is distributed and
probabilistic
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Routing independent propabilistic methods I
• Representative protocols:
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Quality Constrained Data Aggregation and
Processing, Q-DAP, (Zhu, Papavassiliou & Yang,
2006)
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 Every node with probability γ waits defined time
and aggregates all the packets gathered in the
given time duration.
• Adaptive Application-Independent Data
Aggregation, AIDA, (He, Blum, Stankovic &
Abdelzaher, 2004)
 The aggregation is realized in a separate layer –
between the data link layer and the network layer
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Approaches based on the nature of the data I
Distributed compression strategies
• Use of source compression with combination of
the correlation of data between neighboring
nodes
• Less bits are transmitted
less energy is
consumed
• Loss in data accuracy
• Cost of compression and decompression should
be small
• The approaches are divided:
 multi-input coding strategies
 single-input coding strategies
 self coding
 foreign coding
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Approaches based on the nature of the data II
• Representative protocols:
 Minimum-Energy Gathering Algorithm, MEGA, foreign coding
(Rickenbach & Wattenhofer, 2004)
 Low-Energy Gathering Algorithm,LEGA, approximation
algorithm for self-coding (Rickenbach & Wattenhofer, 2004)
 Removal of correlation with the use of distributed compression
algorithm (Chou, Petrovic & Ramchandran 2003)
 Energy-Efficient Distributed Source Coding, EEADSC (Tang,
Raghavendra & Prasanna 2003)
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Approaches based on the nature of the data III
Transmission of meta-data
• Whenever a node has data to send, transmits first a
packet that describes its data
• Neighboring nodes wanting to receive the data, send a
packet to declare their interest
• Data packet transmission follows
• Use of the described approach by the SPIN protocols
(Heinzelman, Kulik, & Balakrishnan 1999)
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Query based approaches I
• Data are sent to the sink:
 Periodically
 Whenever a value exceeds a threshold
 As a response to user request
• Users pose requests to the sink
• The sink inserts the question to the network and the
sensor nodes send the requested data
• The requests may regard a specific group of sensor
nodes
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Example: What is the temperature in the west side of the room?
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Query based approaches II
• Representative protocols:
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The Cougar approach, (Yao & Gehrke, 2002)
 At each node there is a query proxy layer that interacts
with the network and application layer
 Synchronization is needed among the nodes
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Tiny AGregation, TAG, (Madden, Franklin, Hellerstein &
Hong, 2002)
 The request is propagated to all the network nodes
(distribution phase)
 The nodes that have data answering the question send it
through a data collection tree rooted at the sink. In every
intermediate node data aggregation is performed (data
gathering phase)
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Query based approaches III
• Representative protocols:
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Temporal coherency-aware in-Network Aggregation, TiNA,
(Sharaf, Beaver, Labrinidis & Chrysanthis, 2004)
 Enhancement of the above mentioned approaches with the
tradeoff of loss in accuracy
 Use of tct value which represents the acceptable loss in
accuracy – defined by the user
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Adaptive Periodic Threshold-sensitive Energy Efficient
sensor network protocol, APTEEN, (Manjeshwar, Zeng &
Agrawal, 2002)
 Network is partioned into groups
 Use of modified TDMA model
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Selection of subset of sensors I
• In every gathering round a representative set of
sensor nodes is selected that sends sensed data to
the sink
• The chosen subset must cover the entire network
• Nodes that are not chosen are put either to sleep or
idle mode
• Similar to the approaches used in the MAC layer
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Selection of subset of sensors II
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Energy Savings with Topology Control
(TC)
Two major ways to do TC:
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Controlling the power at the node to create energy effective
topologies
Taking advantage of the network density for turning off the
radio interface
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“Node sleep” saves a lot
Only a (connected) fraction of the nodes stays up for
performing network functions
Another idea:
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backbone formation can also be used for the sake of
topology control (only backbone nodes are awake, or better,
nodes have different duty cycles depending on whether they
belong to the backbone or are ordinary nodes)
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Selection of subset of sensors IV
• Representative protocols:
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Selection of a connected correlated-dominating set, (Gupta,
Navda, Das & Chowdhary, 2005)
Use of data reporters for transmission of data (Choi & Das,
2005)
Capability for data gathering with different level of accuracy
(Chen, Guan & Pooch, 2004)
The above approaches have great energy savings with the
tradeoff of loss in covering the whole network
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Data gathering in mobile WSNs I
• All the above presented approaches work for static
deployed WSNs
• Not efficient use in mobile environments
• Different parameters need to be taken into
consideration, ex. The motion pattern of the nodes
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Data gathering in mobile WSNs II
• Representative protocols:
 Liu and Lee, 2004. Creation of clusters based on the LEACH
protocol
 For the cluster head selection each node sends a packet containing
information about the location, speed and direction
 Each node based on its data decides in which cluster will become
member of
 Chae, Han, Lim, Seo and Wo, 2000. Creation of sensor groups
with 2 kinds of nodes: sensors & transmitters
 Nodes operate in defined intervals and then are put to idle mode
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Data gathering approaches comparison I
Hierarchical
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Great energy savings
Delay in data gathering
Initialization and maintance cost
Data accuracy depends on the aggregation function used
Non - Hierarchical
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Sensor nodes consume great amount of energy
Simple in operation and maintance
Increase in network load because of vast amount of data
Small delay & good throughput at first but as the load
increased increase in delay and decrease in throughput
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Data gathering approaches comparison II
Routing independent – probabilistic approaches
• Increase in network lifetime
• Delay and throughput depend on the aggregation decision taken in
a distributed manner at every node
Approaches based on the nature of data
•Energy savings
•Cost in compressing and decompressing the data
•Delay and throughput depend on the type of coding
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Data gathering approaches comparison III
Querry based approaches
• Not all nodes send data to the sink
less energy consumed in each data gathering round
• Data accuracy depend on the type of aggregation function
• Many nodes do not send data similar to previous sent
• Delay because of data aggregation
Selection of subset of sensor
• Since some nodes are put in sleep mode in predefined rounds
• Network lifetime increases
• Reduced network coverage
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Comparison Table
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Security
Security I
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What is different ?
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Security has never been more important!
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Unfriendly, unattended environments
Severe resource constraints render most of the
cryptographic mechanisms impossible
PKI is infeasible for sensor networks and have
to rely on symmetric key cryptography
Applications in battlefield management,
emergency response systems and so on
Key management is the most critical issue
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Focus of majority of the research
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Security II
SPINS
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Complete suite of security protocols for sensor
networks
SNEP (Secure Network Encryption Protocol)
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Data Confidentiality
Data Integrity
Data Freshness
μTESLA
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Lightweight version of TESLA for authenticated
broadcast
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Security III
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Authenticated Routing
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Base station can be authenticated using
μTESLA
For each time interval, the first packet heard is
chosen as parent, which is authenticated later
Prevents spurious routing
Node-to-Node Key Agreement
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A sends B a request with a nonce
B asks the sink for a session key using SNEP
Sink distributes shared session keys securely
to A and B using SNEP with strong freshness
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References
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W. Ye, J. Heidemann, D. Estrin, “Medium Access Control With Coordinated
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2003
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References
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Heinzelmann, W. (2000). Application-Specific protocol architectures for
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References
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Madden, S.R., Franklin, M. J., Hellerstein, J. M., and Hong, W. (2002).
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Maryland, Baltimore County, USA