An Application-Specific Protocol Architecture for Wireless Microsensor Networks By: W. Heinzelman, A. Chandrakasan

1
An Application-Specific Protocol Architecture for
Wireless Microsensor NetworksBy W. Heinzelman,
A. Chandrakasan H. Balakrishnan

• A review prepared for CEG 790
• By Patrick Flaherty

2
Presentation Outline

• What is a Wireless Sensor Network?
• Why are Protocols for Self-Organizing an issue?
• The proposed Low-energy adaptive clustering
  hierarchy (LEACH) protocol
• Concept
• Algorithms
• Analysis and simulation of LEACH
• Conclusions

3
What Is A Wireless Sensor Network?

• Sensor devices (source)

• Wireless communication

Network Layer Tasks (partial)
Application Source code
Transport Packets, congestion control
Network Routing
Data-Link MAC, error correction
Physical Wireless

• Network structure

4
Wireless Sensor Networks

• 10s to 1,000s of wireless sensors placed into
  an environment
• May be put into structures where truckloads of
  cabling would be required to connect to the data
  collection point (e.g., Golden Gate Bridge)
• May be placed in a natural environment to monitor
  wildlife (e.g., study relationship between
  weather conditions and animal behavior)
• May be used in hostile environments to detect
  movement of opponents

5
Wireless Sensors

• Devices that

6
Energy Consumption is a Function of Device
Activity

• Telos is a recently released microsensor platform
  design

Source Telos Fourth Generation WSN
PlatformPresented at TinyOS Technology
Exchange, Feb. 11, 2005
7
Wireless Transmission Issues

• Line-of-sight (LOS) transmission attenuation
• Power falls off as d 2

• Multiple paths lead to reflection and scattering
• Power falls off as d 4 beyond a certain distance

• Receiver may fail to discriminate valid signals
  due to
• Interference from other Tx
• Noise (internal to the Rx)

8
Characteristics That Affect Wireless Sensor
Network Design
Characteristic Implication
Severe power constraint Network protocols must take power into consideration
Number of nodes could be in the thousands, scattered in any order Network topology and routing not pre-engineered protocols must handle establishing the network
Radio consumes large amounts of power when on Keep radio off whenever feasible
Transmit power loss rises as d2 in close, as d4 further out Minimize number (and duty cycle) of distant nodes transmitting to base station
9
Authors Design Assumptions

• All nodes can transmit with enough power to reach
  the base station if needed
• Individual nodes can adjust the amount of
  transmit power
• Each node has sufficient computational power to
  support different MAC protocols, perform signal
  processing, etc.
• Nodes always have data to send
• Nodes that are sufficiently close have correlated
  data

10
Consider 3 Different Network Protocols To Clarify
Concepts

• Simple network -- every node talks directly to
  the base station
• Minimum Transfer Energy (MTE) nodes minimize
  transmit distance energy loss
• Static Cluster group nodes spatially, aggregate
  data, and assign one node to handle
  communications with the base station

11
Network Scenario -- Simple

• All nodes communicate directly with the base
  station always on

• Problems
• Who talks next?
• Out of power fast!
• Especially distant nodes

Recall Signal strength is inversely
proportional to the square of the distance
(best case)
Base Station
12
Network Scenario MTE

• Each node discovers the best hop-by-hop path to
  the base station during an initialization phase

Problem close-in nodes overused

• Data transmitted every tdelay seconds
• Collision avoidance via CSMA protocol
• As nodes run out of energy, routes are recomputed
  to maintain connection to base station
• Problems

Base Station
Problem multiple hops --gt latency
13
Network Scenario -- Static Clustering

• Organize nodes into clusters

Base Station
14
Summary of Previous Protocols
Issue Simple MTE Static Cluster
Rate of energy Consumption Very Rapid Rapid Slower (but cluster head failure is an issue)
Control of Access Not addressed CSMA TDMA
Impact from Loss of 1 Node One node lost One node lost (after rerouting) Entire cluster lost (if a cluster head)
Latency One hop Multiple hops Two hops
Less Energy Consumption
15
Low-Energy Adaptive Clustering Hierarchy (LEACH)
Protocol

• Structure of rounds occurring over time
• Nodes organize themselves into local clusters
• One node acts as the cluster head
• Member nodes transmit data to the cluster head
  during the timeslot allocated by a TDMA algorithm
• Cluster head aggregates the data from the member
  nodes (e.g., computes mean value)
• Cluster head transmits aggregated data to base
  station
• Repeat until time to begin a new round

16
Cluster Behavior During a Round
Round

• Organize new cluster

• Each member node (in turn) transmits their data
  to the cluster head during the assigned timeslot

• Cluster head processes the data

• Cluster head transmits to base station

Base Station
17
Clusters Reform Periodically

• Each round consists of a setup period and some
  number of frames

Round 1

• Each round establishes a new structure of clusters

• Each cluster has a new cluster head

Round 2

• Repeat rounds until the network fails (due to
  energy depletion)

18
Now For Some Details

• Cluster head selection algorithms
• Cluster formation algorithm
• Steady-state phase
• Alternate scheme LAECH-C

19
Cluster Head Selection Algorithms

• Need distributed Algorithms
• Desired results
• Specified number of cluster heads formed for each
  round
• Cluster head duties rotated among nodes so as to
  evenly draw power from the nodes over time (no
  overly-utilized nodes)
• Case 1
• Nodes begin with equal energy
• All nodes transmit data during each frame
• Case 2
• Nodes begin with unequal energy, and/or
• Nodes transmit upon event

20
Cluster Head Selection Case 1

• Each node elects itself to be a cluster head with
  probability Pi(t) such that for N total network
  nodes

Where k cluster heads

• To ensure that each node becomes a cluster head
  only once in each of N/k rounds, assign Ci(t) 0
  if the node has already been a cluster head in
  the current round and Ci(t) 1 otherwise.

• Each individual node chooses to become a cluster
  head in round r with probability

21
Cluster Head Selection Case 1 (continued)

• Value of N - k(r mod N/k) represents the number
  of unpicked nodes
• Use of r mod N/k ensures restarting after all
  nodes have been picked

Example
End of Round (r) Un-picked Nodes Pi(t) of remaining nodes
0 9 .22
1 7 .29
2 5 .40
3 3 .67
4 1 1.00
5 8 .25
N 9 k 2
22
Cluster Head Selection Case 2

• Nodes with more energy should have a higher
  probability of being chosen than nodes with less
  energy

• Thus, the probability that a given node will be
  chosen is determined by that nodes share of the
  total remaining energy

• Where Ei(t) is the energy of the ith node and

23
Cluster Head Selection Case 2 (continued)

• Notice that this algorithm requires each node to
  know (or have an estimate for) the value of
  Etotal(t)
• To know the exact value would take time and
  consume energy
• As an estimate we could compute the average
  energy of each node in a given cluster and
  multiply by N
• Nodes report current energy to cluster head
• Cluster head computes estimated Etotal(t) and
  returns the value to all nodes in the cluster

24
Distributed Cluster Formation

• Cluster heads broadcasts advertisement message
  (ADV) using CSMA MAC protocol
• Non-cluster head nodes measure received strength
  of ADV and select strongest sender as their
  cluster head
• Nodes notify cluster head of their selection with
  a Join-REQ message
• Cluster head creates TDMA schedule for nodes in
  its cluster

25
Steady State Phase

• Recall Rounds are divided into frames
• Each node sends data once per frame
• TDMA requires accurate synchronization
• Possible method ? base station sends
  synchronization signals
• Energy saved at non-cluster head nodes since
• Power is reduced to only that required to reach
  local cluster head
• Radio turned off except for short period provided
  by TDMA
• Cluster head steady state tasks
• Listen to non-cluster head nodes
• Aggregate the data
• Transmit the data to the base station

26
Steady State Phase (continued)

• Transmissions must succeed even though other
  nodes and cluster heads are broadcasting
• LEACH uses Direct-Sequence Spread Spectrum (DSSS)
• Each cluster uses a unique spreading code
• Chosen from a pre-defined list
• With enough spreading, potentially interfering
  signals can be filtered out during de-correlation
• Easier to implement than dynamically assigned
  frequency bands
• Difficulty is need for tight timing
  synchronization
• How does DSSS work? (Not addressed in this paper)

27
DSSS Key Ideas

• A wireless transmission technology that enables
  multiple users to share the same bandwidth

• Spreading Data signal is multiplied by a unique,
  high rate code which spreads the bandwidth
  before sending (1 data bit now represented by
  many bits)

• The resulting Spread Spectrum is less
  susceptible to interference

• Receiver must have the same code to recover the
  original data

28
LEACH-C -- A Variation of LEACH

• Idea using a central control algorithm may
  produce better clusterings
• Each node sends location information and energy
  level to the base station
• Base station
• Eliminates low energy nodes from consideration
• Finds k optimal clusters (since this is NP-hard,
  uses the Simulated annealing algorithm )
• Goal is to minimize the total sum of squared
  distances between non-cluster heads and the
  nearest cluster head

29
Performance Analysis

• Simulate the performance of four protocols
  (Static Clustering, MTE, LEACH, LEACH-C)
• How?
• Set up the simulation
• Find the optimal number of clusters
• Compare the protocols energy consumption
  performance
• Conclusions

30
Simulation of Protocol Performance

• Analytical model of even moderately-sized
  realistic networks is difficult
• Authors used the network simulator ns
• Comparison of performance over four metrics
• System lifetime
• Energy dissipation
• Amount of data transferred
• Latency

31
Experiment - Setup
Base Station

• 100 nodes randomly distributed over a 100 X 100
  grid (0, 0) to (100, 100)
• Base station placed outside the grid (50, 175)
• Channel bandwidth 1 Mb/s
• Packets have 25 byte header and 500 byte data
  size
• Power loss determined by distance d

• If d lt do, loss µ d 2

Free space model

• If d gt do, loss µ d 4

Multi-path model
32
Experiment - Setup (continued)

• Radio energy dissipation model
• lEelec energy consumed by the electronics to
  process l bits
• l efs energy consumed by the amplifier to
  transmit l bits over distance d where d lt do
• l emp energy consumed by the amplifier to
  transmit l bits over distance d where d gt do

• Then total energy consumed by the transmitter

• Total energy consumed by the receiver

33
Experiment - Setup (continued)

• Energy parameters used
• Eelec 50 nJ/bit
• efs 10 pJ/bit/m2
• emp 0.0013pJ/bit/m4
• Energy for Data Aggregation EDA 5
  nJ/bit/signal
• Question How many clusters should be used?

34
How Will The Number Of Clusters Affect Results?

• Case 1 Baseline (BL)
• S non-cluster head energy ENCHBL
• S Cluster head energy ECHBL

Case 1

• Case 2 Fewer Clusters (FC)
• ENCHFC gt ENCHBL
• ECHFC lt ECHBL
• Does Case 2 use less energy than case 1?

• Case 3 More Clusters (MC)
• ENCHMC lt ENCHBL
• ECHMC gt ECHBL
• Does Case 3 use less energy than case 1?

Is there an optimal number of clusters?
35
Optimal Number Of Clusters

• With a given spatial distribution of nodes and
  known energy consumption parameters, we can
  compute an optimal number of cluster heads (k)

• Step 1 Develop expressions for node energy use
• Cluster heads (always on)
• (assumes dtoBS gt do)
• Non-cluster heads
• (assumes dtoCH lt do)

• Step 2 Develop an expression for the expected
  squared distance from the nodes in a cluster to
  the cluster head

36
Optimum Number Of Clusters (continued)

• Step 2 (continued) Assumptions
• In an M x M grid, each cluster occupies an area
  of M2/k
• Clusters have a node distribution of p(x, y)
• The cluster head is at the center of mass of the
  cluster

• Then the expected d2 from the nodes to the
  cluster head is

(in Cartesian coordinates)
(in polar coordinates)

• Further assume the area is a circle ? radius R
  (M/(pk)1/2)
• And p(r, q) constant for r and q, then

37
Optimum Number Of Clusters (continued)

• Step 2 (continued) Assumptions
• Node density is uniform across all clusters ? p
  (1/( M2/k))
• Then simplifies to

• Step 3
• Combine energy and distance expression for
  non-cluster heads

• Then for the entire cluster
• (During a single frame)

38
Optimum Number Of Clusters (continued)

• Step 3 (continued)
• Total energy for a frame

• Step 4 Set derivative of Etotal with respect to
  k to zero

Simulation results agree with analytical
prediction

• Results for this case (100 nodes, etc.)
  Analytical method predicts 1 lt kopt lt 6

39
Comparison of Algorithms

• Each node was given 2 Joules of energy (def J
  Ws)
• This is equivalent to a 5 volt device _at_ 20 mA for
  20 s
• Parameters tracked during simulations
• Rate at which data packets were transferred to
  the BS
• Energy required to get the data to the BS
• What is not in the simulation
• No static energy loss (e.g., RTC energy use)
• Energy for CSMA is ignored (? CSMA energy use in
  MTE is understated)
• Energy expended during cluster organization (not
  mentioned in the paper)

40
Simulation Results Data Received
40 more data for the same energy as LEACH

• LEACH-C and LEACH deliver far more data than MTE
  and Static Clustering (SC) and they are far more
  energy efficient (as measured by signals per
  Joule)
• SC fails when all cluster heads die, even with
  most energy still unused
• MTE slow to deliver data due to multi-hops
• LEACH-C is the best performer due to optimal
  cluster design

41
Simulation Results Nodes Alive
LEACH-C delivers more data due to higher data
rate/J

• LEACH-C and LEACH maintain full network
  availability far longer than MTE and SC
• MTE lasts the longest, but at the price of very
  limited effective data delivery due to
• Lack of data aggregation
• Energy wasted in CSMA collisions
• LEACH-C is again the best performer

42
Conclusions

• Wireless Sensor Networks which meet the original
  assumptions will benefit from
• Rotating the cluster head position among all
  nodes
• Adapting cluster organization to new cluster
  heads
• Aggregating data
• Disadvantages
• LEACH LEACH-C are very dependent on nodes
  having correlated data
• Both require tight time synchronization
• LEACH-C requires location information

43
Future Work

• If nodes send data on condition
• They can be on standby for longer periods than
  TDMA permits
• Efficient bandwidth use will require a different
  communication protocol
• If nodes are beyond max possible communication
  range
• Multi-hop protocols may be required
• Super cluster heads may prove a better solution
• If the original cluster is kept and the nodes
  within the existing clusters just rotate the
  cluster head job
• No setup overhead is used after round one
• Downside ? nodes may expend more energy
  communicating since current cluster head may be
  far away