research directions in sensor networks · research directions in sensor networks kendall e. nygard...

Research Directions inSensor Networks

Kendall E. NygardNorth Dakota State UniversityNorth Dakota State University

IARIA InfoSys Conference Sint Maarten

March 27, 2012

Project sponsor acknowledgements: U.S. Department of Energy, ArmyResearch Office, Office of Naval Research, Air Force Office of ScientificResearch, NASA, National Science Foundation

Outline and Problem Categories

• Sensors and Sensor Networks

• Coverage and Sensor Distribution

• Hierarchies and Clustering

• Mobile Sensors• Mobile Sensors

• Sensor Failures and Self-Healing

• Sensor Scheduling

• Routing

• Security and Encryption

CrossbowMica mote

Sensors, Sensor Nodes, Mobile Sensors

CrossbowStargate

NASA – Mobile Platform

SmartPhone

TransceiverSensor 1

Sensor Node Architecture

Micro-ControllerAnalog/Digital

Converter

External Memory

Sensor 1

Sensor 2

PowerSource

Sensor Node Characteristics

• Small

• Battery power or harvested power

• Limited power → Limited lifetime

• Limited RF communication radius

• Environmental conditions can be harsh• Environmental conditions can be harsh

• Low reliability → node failures

• Static in many applications, but can be mobile

• Network topology is can be dynamic as nodes fail orothers join

• Homogeneous or heterogeneous networks

• Unattended operation

AC

BD

Geographical Coverage andDistribution

Double Coverage

Single Coverage

Coverage Holes

Triple Coverage

Research Problems in Coverage and theDistribution of Sensors

Problem Solution Approach

Numbers of sensors toachieve a minimumcoverage level

statistical analysis

coverage level

Self-location Protocols and calculationsusing signal strength,reference nodes,andtriangulation

Research Problem: Coverage HoleDiscovery and Boundary Calculations

Research Problems using Mobile Sensors

Problem Goal of AlgorithmicApproaches to DirectMovements

Cover holes in sensingcoverage.

Cover Holes

Improve networkconnectivity and topology

Reduce connectivity gapsand increase redundantconnectivity and topology and increase redundantcommunication paths

Dynamically respond to newsensing tasks

Establish or increasecoverage where needed

Compensate for nodefailures

Cover gaps caused by thefailures

Reconfigure when newnodes are added

Optimize the new topology

Routing Voids Caused by Sensor Failures

Mobile Sensors Move to Improve Coverage

Research Problem: How to Direct MobileSensors to Move and cover the holes?

Distance

Small Medium

50 m 100m

Large

Small LargeMedium

Fuzzy Logic Functions to DriveMobile Sensor Movement

RelativeHole Size

Small LargeMedium

0.33 0.67

Small LargeMedium

3 6

Number of New links

Distance Size Number of NewConnections

Decision

L - - N

M M/S S N

M M/S L Y-

M L L Y

De-Fuzzification Movement Rules

S L S Y+

S M S Y

S S S N

S L M Y+

S M M Y+

S S M Y

S L/M L Y

S S L Y-

High and Low Level Sensors

• High-level sensors (like Stargate) havebetter capabilities than Low-level sensors(like Mica) in terms of communications,computation, memory/storage, energycomputation, memory/storage, energysupply, and reliability.

• Call them H-sensors and L-sensorsrespectively

Research Problems regarding Architectureswith Low and High Level Sensors (Hierarchies)

Problem Goal of Algorithmic Approaches toUtilize the H-Sensors

Design 2-level topology tosupport energy-efficiency andhigh data rates to a basestation

Cluster the L-sensors around each H-sensor which serve as relay heads, andestablish intra and inter cluster routing

Manage H-sensors to support Establish secure routing protocols at the 2Manage H-sensors to supportprivacy, authenticity, andintegrity

Establish secure routing protocols at the 2levels

Coordinate sensing tasksover time and track mobileobjects.

Build secure and efficient timesynchronization schemes

Build intelligence into thesensor network

Build Neyman-Pearson and/or BayesainModels

Build self-healing into thesensor network

Reconfigure routing tables when sensorsfail

Hierarchies and Clustering

H-Sensor

L-Sensor

Voronoi Polygon

Base Station

Intra and Inter Cluster Routing

• Shortest path trees intra andInter cluster

• L-sensors can have smalltransmission radius

• Backbone H-sensors havelonger transmission rangeand higher bandwidth

• H-sensors can carry outdata fusion and otherintelligent operations

Tabu Search to Improve Clusters

Step 1: Create Voroni clusters as an initial solution solution i. Set i* = iand k=0.

Step 2: Set k=k+1 and generate candidate neighborhood clusters bycarrying out non-Tabu boundary node exchanges between clusters.

Step 3: Generate candidate neighborhood clusters by carrying out non-Tabu cyclic transfers among clusters.Tabu cyclic transfers among clusters.

Step 4: Choose the best cluster set i from Steps 2 and 3 in terms of arouting metric (distance or hop count)

Step 5: Compare metrics. If f(i) < f(i*) then set i* = i.

Step 6: Update the Tabu list.

Step 7: If a stopping condition is met then stop. Else go to Step 2.

L-Sensordata at time t

Data Fusion at an H-Sensor Relay Node

H-Sensor DataFusion Rules

Data Sent toBase Station

SomethingObservable

at Time t

L-Sensordata at time t

L-Sensordata at time t

Neymann-Pearson,Bayesian

Research Problems in SchedulingDifferentiated Sensors

Problem Goal of Algorithmic Approaches

Extend useful sensor lifetime Build on/off times for all sensors whilemaintaining a threshold percentage ofcoverage

Self-heal sensor schedulewhen sensors fail

Rebuild on/off times for all sensors whilemaintaining a threshold percentage ofcoveragecoverage

Scheduling Problem Approach

• Superimpose a grid

• Calculate grid cellscovered by eachsensor

AC

B

1 2

Dsensor

• Discretize timeperiods

• Configuresupply/demandnetwork

Generalized Network Flow Model ForSensor Scheduling

3

3

3

g2 ,T1

S1 ,TN

S1 ,T1

S1 ,T2

gK ,T1

g1 ,T1

s1 ,T2

s1 ,T1

s1 ,TN

S11

(0 ,6)

(2, M)

(3, M)(0 ,1)

(0 ,1)

(0 ,1)

(1, M)

(0 ,1)

(0 ,1)

(0 ,1)(0 ,∞)

(0 ,∞)

24

3

SM,T2

SM ,TN

SM, T1 sM ,T1

sM ,TN

g2,TN

gK ,TN

g1 ,TN

SM

2

2

2

1 (0 ,5)

(1, M)

(0 ,1)

(0 ,1)

(1, M)

(0 ,1)

(2, M)

(4, M)

(0 ,1)

(0 ,1)

(0 ,1)

(0 ,1)sM ,T2

(0 ,∞)

(0 ,∞)

(0 ,∞)

(0 ,∞)

Generalized Network Flow Model

Security and Key Management inHeterogeneous Sensor Networks

Problem Goal of Algorithmic Approaches

Reduce communicationoverhead, computationoverhead, and storagerequirements for securityprotocols, while supportingscalability.

Build a management framework usingRabin’s cryptosystem for encryption keysthe supports confidentiality, authenticity,and availability and allows H-sensors toestablish key space information to L-sensorsscalability. sensors

Miscellaneous Projects

Instrumentation/Sensors in theSmart Grid

2828/06/2012

Cooperating Unmanned Air Vehicles

TETWALKERSCooperative Control• Mission goals negotiated• Waypoints determined• Rough path planning• Rough obstacle avoidance

Autonomous Control• Path planning• Obstacle avoidance• Step and gait choices• Step and gait choices• Collision avoidance

Wrap-up: Interesting ResearchProblems Abound in….

• Coverage and Sensor Distribution

• Hierarchies and Clustering

• Mobile Sensors

• Sensor Failures and Self-Healing• Sensor Failures and Self-Healing

• Sensor Scheduling

• Routing

• Security and Encryption