A review prepared for CEG 790 By: Patrick Flaherty

04/19/23 1

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

A review prepared for CEG 790By: Patrick Flaherty

04/19/23Flaherty – CEG 790

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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


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What Is A Wireless Sensor Network?

Sensor devices (source)

Base Station(sink)

Wireless communication

Network structure

Network Layer

Tasks (partial)

Application Source code

Transport Packets, congestion control

Network Routing

Data-Link MAC, error correction

Physical Wireless


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Wireless Sensor Networks

10’s to 1,000’s 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


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Wireless Sensors

Devices that:

SensorsLightHeatVibration…

Measure some input variableProcessor

Process the measurement

Radio

Transmit data to higher level

Small & inexpensive (ideally)

Battery

Panasonic

CR2354 560 mAh

Powered by battery (typically)


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Energy Consumption is a Function of Device Activity

Telos is a recently released microsensor platform design

Source: “Telos Fourth Generation WSN Platform”Presented at: TinyOS Technology Exchange, Feb. 11, 2005

Radio power consumption dominates (even in receive mode)

Standby mode supports long life


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Wireless Transmission Issues

Line-of-sight (LOS) transmission attenuation

Power falls off as d 2 Tx Rx

d

Tx Rx

d

Tx Tx

Rx

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)


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Characteristics That Affect Wireless Sensor Network Design

Characteristic ImplicationSevere 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


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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


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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


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Network Scenario -- Simple

All nodes communicate directly with the base station – always on

Base Station

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)

Far away --> Hi-power --> Short life


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Network Scenario – MTE

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

Base Station

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: Problem: multiple hops --> latency

Problem: close-in nodes overused


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Network Scenario -- Static Clustering

Organize nodes into clusters

Base Station

Nodes send data to “Cluster Head”

Access via TDMA

Cluster head aggregates the data and sends results to base station

Problem: When cluster head’s energy depleted, no further data is sent from this cluster


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Summary of Previous Protocols

Issue Simple MTEStatic 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 lostOne node lost

(after rerouting)Entire cluster lost(if a cluster head)

Latency One hop Multiple hops Two hops

How to improve this idea?

Less Energy Consumption


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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


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Cluster Behavior During a Round

Organize new cluster

Round

Base Station

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

Time


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Clusters Reform Periodically

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

Round 1 Round 2 Round n……

Frame

Round 1

Round 2

Cluster Heads

Each round establishes a new structure of clusters

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

Each cluster has a new cluster head


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Now For Some Details

Cluster head selection algorithms

Cluster formation algorithm

Steady-state phase

Alternate scheme LAECH-C


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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”


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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


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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

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 = 9k = 2

Base Station

Example


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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 node’s share of the total remaining energy

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


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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


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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


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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

Round 1

Frame 1 Frame 2


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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)


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DSSS Key Ideas

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

SourceRF

Modulator

CodeGenerator

X

Code Bits (Code)

Digital Signal (Data)

Tx

Frequency Spectrum “Spread” FrequencySpectrum

f1 Mhz 11 Mhz

f

The resulting “Spread Spectrum” is less susceptible to interference

Receiver must have the same code to recover the original data

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)

Wireless Technologies

Spread SpectrumNarrow Band

FrequencyHopping

Direct Sequence


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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


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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


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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


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Experiment - Setup

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

Base Station d

d < d o

d o

If d < do, loss d 2

If d >= do, loss d 4

d

d > d o

d o

Free spacemodel

Multi-pathmodel


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Experiment - Setup (continued)

Radio energy dissipation model lEelec: energy consumed by the

electronics to process l bits l fs: energy consumed by the

amplifier to transmit l bits over distance d where d < do

l mp: energy consumed by the amplifier to transmit l bits over distance d where d >= do

Then total energy consumed by the transmitter:

Total energy consumed by the receiver:


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Experiment - Setup (continued)

Energy parameters used: Eelec = 50 nJ/bit fs = 10 pJ/bit/m2

mp = 0.0013pJ/bit/m4

Energy for Data Aggregation: EDA = 5 nJ/bit/signal

Question: How many clusters should be used?


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How Will The Number Of Clusters Affect Results?

Case 1: Baseline (BL) non-cluster head energy = ENCHBL

Cluster head energy = ECHBL

Base Station

Case 1

Base Station

Case 2

Base Station

Case 3

Case 2: Fewer Clusters (FC) ENCHFC > ENCHBL

ECHFC < ECHBL

Does Case 2 use less energy than case 1?

Case 3: More Clusters (MC) ENCHMC < ENCHBL

ECHMC > ECHBL

Does Case 3 use less energy than case 1?

Is there an optimal number of clusters?


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Step 1: Develop expressions for node energy use Cluster heads (always on): (assumes dtoBS > do)

Non-cluster heads: (assumes dtoCH < do)

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)

Listening Aggregating Transmitting

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


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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

(in Cartesian coordinates)

(in polar coordinates)

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

Further assume the area is a circle radius R = (M/(k)1/2) And p(r, ) constant for r and , then


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Step 3: Combine energy and distance expression for non-

cluster heads:


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

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


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

Simulation results agree with analytical prediction

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

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


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Comparison of Algorithms

Each node was given 2 Joules of energy (def: J = W·s)

This is equivalent to a 5 volt device @ 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)


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Simulation Results – Data Received

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

~40% more data for the

same energy as LEACH


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Simulation Results – Nodes Alive

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

LEACH-C delivers more data due to higher data

rate/J


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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


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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

A review prepared for CEG 790 By: Patrick Flaherty

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