Sensor Networks
Lecture 8
LEACH Clustering
• LEACH: (Low Energy Adaptive Clustering Hierarchy)
rotates cluster heads to balance energy consumption
• Each cluster head performs its duty for a period of
time
• Each sensor makes an independent decision on
whether to become a cluster head and if yes
broadcasts advertisement packets
LEACH Clustering (cont.)
• Each sensor that is not a cluster head listens to
advertisements and selects the closest cluster head
• Once a cluster head knows the membership, a
schedule is created for the transmission from sensors
in the cluster to the cluster head to avoid collision
(e.g., based on TDMA)
• The cluster head can send a single packet to the
base station (directly) over long distance to save
energy consumption
• No assurance of optimal cluster distributions
HEED Clustering
• HEED (Hybrid Energy-Efficient Distributed clustering) uses the residual energy
info for cluster head election to prolong sensor network lifetime
• Probability of a sensor becoming a cluster head is:
• Clusters are elected in iterations:
– A sensor announces its intention to become a cluster head, along with a cost
measure indicating communication cost if it were elected a cluster head
– A non-CH sensor picks a candidate with the lowest cost
– A non-CH sensor not covered doubles its CHprob in iterations until CHprob is 1, in
which case the sensor elects itself to the cluster head
PEGASIS: Power-Efficient Gathering in Sensor Information Systems
• A chain of sensors is formed for data transmission (could be
formulated by the base station)
• Finding the optimal chain is NP-complete
• Sensor readings are aggregated hop by hop until a single
packet is delivered to the base station: effective when
aggregation is possible
• Advantages: No long-distance data transmission; no overhead
of maintaining cluster heads
• Disadvantages:
– Significant overhead: Can use tree instead
– Disproportionate energy depletion (for sensors near the base station):
Can rotate parent nodes in the tree
Aggregation/Duplicate Suppression
• Aggregation of information in a tree structure
– In-network information processing such as max,
min, avg
• Duplication Suppression:
– On forwarding messages, sensor nodes whose
values match those of other sensor nodes can
simply annotate the message
– Or just remain silent, on overhearing identical (or
“similar enough”) values
Querying a Sensor Network
• Can have sensor nodes periodically transmit sensor readings
• More likely: Ask the sensor network a question and receive an
answer
• Issues:
– Getting the request out to the nodes
– Getting responses back from sensor nodes who have answers
• Routing:
– Directed Diffusion Routing
– Geographic Forwarding (such as Geocasting)
Query-Oriented Routing
• For query-oriented routing: Queries are
disseminated from the base station to the
sensor nodes in a feature zone
• Sensor readings are sent by sensors to the
base station in a reverse flooding order
• Sensor nodes that receive multiple copies of
the same message suppress forwarding
Query: Asking a Question
Response to Base Station:
Initial
Directed Diffusion Routing
• Direction: From source (sensors) to sink (base station)
• Positive/negative feedback is used to encourage/discourage
sensor nodes for forwarding messages toward the base station
– Feedback can be based on delay in receiving data
– Positive is sent to the first and negative is sent to others
• A node will forward with low frequency unless it receives
positive feedback
• This feedback propagates throughout the sensor network to
suppress multiple transmissions
• Eventually message forwarding converges to the use of a
single path with data aggregation for energy saving from the
source to the base station
Responses, After Some Guidance
• Use directed diffusion based on positive/negative feedback to
guide response message forwarding
Directed Diffusion Routing Cont.
• Pros
– On demand route setup
– Each node does aggregation and caching, thus
good energy efficiency and low delay
• Cons
– Query-driven, not a good choice for continuous
data delivery
– Extra overhead for data matching and queries
Geographic Routing [Ref. 11]
• For dense sensor networks such that a sensor is
available in the direction of routing
• Location of destination is sufficient to determine the
routing orientation
• Research issue:
– selecting paths with a long lifetime for delivering messages
between sensors, or from sensors to a base station without
excessively consuming energy
– Determining paths that avoid “holes” – determining the
boundary or perimeter of a hole through local information
exchanges periodically to trade energy consumption (for
hole detection) vs. routing efficiency
Geographic Forwarding
References
• Chapters 8-11, F. Adelstein, S.K.S. Gupta, G.G. Richard III and L.
Schwiebert, Fundamentals of Mobile and Pervasive Computing,
McGraw Hill, 2005.
• Other References:
• 10. X. Yu, “Distributed cache updating for the dynamic source
routing protocol,” IEEE Transactions on Mobile Computing, Vol. 5,
No. 6, pp. 2006, pp. 609-626.
• 11. S. Wu and K.S. Candan, “Power-Aware Single and Multipath
Geographic Routing in Sensor Networks,” Ad Hoc Networks, Vol. 5,
2007, pp. 974–997.
Fault Tolerance and Reliability
• Sensor nodes are more susceptible to failure
because of direct exposure to the environment and
energy depletion
• Failure and fault recovery are basic assumptions:
incorporate redundancy to cope with failure
• Performing consensus in a cluster for high reliability
of measurement
– Clustering based on sensing responsibility
– Static vs. dynamic grouping
• Dynamic grouping does not need to maintain state information and
is more accurate (near the event) but incurs overhead in forming the
group and reaching consensus
Searching for Agreement: Static
Grouping
Searching for Agreement: Dynamic
Grouping
MAC Layer Protocols
• IEEE 802.11 scheduling protocols are not suitable for wireless
sensor networks because:
– With RTS/CTS (Request to Send / Clear to Send) , collision can still occur
because of hidden/expose terminal problems
– Listening to traffic to avoid collision requires the nodes to stay on
• TDMA is more suitable (requiring clock synchronization)
– A number of reservation mini-slots can be used to reserve each of the
transmission slots
– Sensors can indicate whether or not they wish to transmit a message
during the scheduling time segment
– Nodes that are not planning to send or receive a packet need to stay
on only during the reservation time slot to see if other sensors are
sending a packet to them
– Collisions are avoided, except for small reservation packets
Tradeoff between Energy Efficiency
and Reliability/Performance
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An important design issue
Improved reliability vs. energy consumption
Aggregating sensor readings vs. loss of information
Energy-efficient protocols often involve increased
delay, loss of accuracy, reduced reliability and/or
other performance penalty
– Direct sensor-BS transmission vs. sensor-CH-BS
– Sensor readings with redundancy
• Achieving application requirements while prolonging
lifetime is a major challenge
Fault Tolerant Data Propagation
• Reference: [12] listed at the end
• Use path redundancy to cope with sensor “reading”
faults
– One path (no redundancy)
– Multiple paths to return sensor readings and a majority
voting of the first three readings returned is performed to
cope with faults
– For example, use Time To Live (TTL) to indicate how many
hops a sensor reading message is to be propagated,
thereby creating multiple paths to propagate the sensor
reading message from source to sink
Fault Tolerant Data Propagation
• Source: node A
• Sink: node I
• When TTL = 3
hops, there are
7 paths from A to
When TTL=4 hops,
there are 21 paths
Fault Tolerant Data Propagation
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An example
Source: node E
Sink: node I
p: link fault probability (causing
reading error)
q: node fault probability (causing
reading error)
TTL=1: Reliability is 1-p
TTL=2: what is the reliability?
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•
Three possible paths: E->I, E->H->I,
E->F->I, with fault probability of p A A
System fails when two out of three
paths fail, so reliability is
1-pA2-2pA(1-A)-(1-p)A2 where A=1-
(1-q)(1-p)2 =2p+q-2pq-p2+p2q
The more the path redundancy, the
higher the reliability at the expense
of more energy consumption
Energy Efficiency
• Metric: Mean Time to Failure (MTTF)
– Time till the first node dies (not useful)
– Time half of the sensor nodes die (too arbitrary)
– Time when the sensor network can no longer perform its
intended function (yeah!)
• Difficult to define precisely
• Designing protocols so that
– All the sensors die at roughly the same time
– Sensors die in random locations instead of in specific
locations
Balancing Energy Consumption
• Clustering – is it always good?
– Triangular routing: sensors -> cluster head -> base
station
– Overhead in selecting and rotating among sensors
to be cluster heads
– Good only if message aggregation is feasible;
otherwise directly sending sensing readings to the
base station may end up saving energy more
Energy-Efficient Clustering
• Reference: [13] listed at the end
• Two key parameters:
– p: probability of a sensor becoming a cluster head
– k: number of hops covered by a cluster
• Find optimal (p, k) that would minimize the
energy consumed
Energy-Efficient Clustering:
Formulation
• Sensors are distributed following a homogeneous
spatial Poisson process with intensity → in a square
area of size 4a2
• Per-hop distance is r
• Energy model: each sensor uses 1 unit of energy to
transmit or receive 1 unit of data
• The information processing center is in the middle of
the area
• Idea: Define a function for the energy used and find
(p, k) that would minimize the energy used
On Optimal Path and Source
Redundancy in Sensor Networks
• Reference: [14] listed at the end
• Analyze the effect of redundancy on MTTF and
determine the optimal path and source redundancy
level to maximize MTTF while satisfying reliability
(Rreq) and timeliness (Treq) QoS requirements in
WSNs.
• Develop a hop-by-hop data delivery mechanism
utilizing source and path redundancy with the goal to
satisfy QoS requirements while maximizing the
lifetime of the sensor system
• Query: must return a sensor reading to the PC within
the real-time deadline.
Cluster based WSN architecture
Hop-by-Hop Data Delivery
Protocol
Hop-by-hop Data Delivery
Protocol
• Based on localized geographic routing
• Path redundancy: Form m paths from a source CH
to the PC:
– m SNs in hop one relay the data through broadcasting
– only one SN relays the data in each of the subsequent
hops in each path
• Source redundancy: Each of the ms SNs to
communicate with the source CH through a distinct
path:
• only one SN relays the data through broadcast in
each of the subsequent hops in each path
Probability Model
• System MTTF - Total number of queries the
system can answer before it fails due to energy
depletion, sensor faults, or channel error
• Rq - Reliability of a query as a result of applying
the hop-by-hop data delivery mechanism with m
paths for path level redundancy and ms sensors for
source level redundancy