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PPT – An Application-Specific Protocol Architecture for Wireless Microsensor Networks By: W. Heinzelman, A. Chandrakasan PowerPoint presentation | free to download - id: 683e91-OWE5Y

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An Application-Specific Protocol Architecture for

Wireless Microsensor NetworksBy W. Heinzelman,

A. Chandrakasan H. Balakrishnan

- A review prepared for CEG 790
- By Patrick Flaherty

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

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

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

Wireless Sensors

- Devices that

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

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)

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

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

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

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

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

Network Scenario -- Static Clustering

- Organize nodes into clusters

Base Station

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

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

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

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)

Now For Some Details

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

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

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

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

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

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

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

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

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)

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

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

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

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

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

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

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?

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?

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

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

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)

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

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)

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

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

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

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