CS1520 Java Threads

CS2510 Fault Tolerance and Privacy in Wireless Sensor Networks

partially based on presentation by Sameh GobrielAgendaIntroduction to Wireless Sensor Networks (WSNs)

Challenges and constraints in WSNs

In-network Aggregation

RideSharing fault tolerance protocol

Secure RideSharing, privacy-preserving and fault tolerance protocol

Conventional Wireless Networks Typical conventional wireless networks are Infrastructure-based (access point). Single hop communicationUses a contention-based MAC access protocol

Adhoc and Sensor Wireless NetworksNo Backbone infrastructure.

Multihop wireless communication.

Nodes are mobile and network topology is dynamic.

SPARC/Solaris Systems

Applications are countless

...Parking lot monitoringAdhoc and Sensor Wireless Networks

Professional Care giving for seniors

Habitat and environmental monitoringHealth Monitoring Body Embedded Network Participatory sensing Military ChallengesNodes are low power, low cost devices.

Very limited supply energy.

Required Lifetime of months or even years.

It may be hard (or undesirable) to retrieve the nodes to change or recharge the batteries.

Considerable challenge on the Energy Consumption.

Challenges contraint the protocols that can be deployed 6ConstraintsThese challenges induce constraints on the protocols developed to achieve:CommunicationData FusionFault ToleranceSecurity

Energy Consumption05101520Power (mW)SensingCPUTXRXIDLESLEEP

In-network Aggregation In-network aggregation Energy Efficient data fusion in WSNs

Each sensor monitors the area around itSensor is supposed to send its data to the end user.

In-network Aggregation End user is not interested in individual sensor readings

Global system information.

Tree-Construction and Data Reporting

Tree-Construction and Data ReportingSending raw data is expensive

Data aggregation (in-network processing) can save a lot of overhead

What are potential problems that you can think of with in-network aggregation?Frequent ErrorsWhen an error occurs A subtree of values is lostIncorrect result reported to the user

Wireless links are unreliable

Nodes energy depleted

Hazardous environment

Objective: Fault-tolerant aggregation and routing scheme for WSNFault Tolerant aggregation: Retransmission

When an error occurs, retransmit the lost valueDelayed Query response:Each level has to wait for possible retransmissions before its ownPacket Overhead:Packet overhead because some handshake is requiredFault Tolerant aggregation: Multipath RoutingA node attached itself to all parents it can hear from.When a link fails, the node value is not lost.

What could be the problem with this scheme ? Duplicate Sensitive Aggregation

Duplicate insensitive aggregation:Max(5, 7, 10, 4, 10) Duplicate sensitive aggregation:Sum, Avg, Count, RideSharing: Fault-tolerant duplicate sensitive aggregation and routing scheme for WSNRideSharing: General IdeaNode selects a primary parents and backup parents

If error free:Child broadcasts value to all parentsOnly primary aggregates it

RideSharing: General IdeaWhen a link error occurs between child and primaryBackup parent detects it (small bit vector 2 bit per child)

Backup parent aggregates the missed child value in its message (if it has not sent its own yet)

In case of error value of a node rideshares with the backup parents value

RS Detection: Bit Vector

RS Correctness

Parents have to be in communication rangePrimary has to send before backupBackup overhears primary error-freeRideSharing Overhead

Child broadcast to all parents (no overhead).Primary (or backup) aggregates the value and broadcast one message to parents (no overhead).No overhead for error correction but only for error detection:Parents listen to childrenDetection of primary link failure [small bit vector]

Cascaded RideSharing

Error free case, primary aggregates child value

In case of one link error, child value rideshares withfirst backup parent

In case of two link errors2nd backup handles itWhat about Privacy ?! Applications Collaborative sensing over shared infrastructure

text

Monitoring

SensorsAttack Model

stealthily infiltrate the network to eavesdropHonest-but-CuriousQuiet infiltrators correctly aggregate, but eavesdrop

New Privacy-Preserving Fault Tolerant Protocol for in-network aggregation in WSNAdditively homomorphic stream ciphersCascaded RidesharingPrivacy PreservationRobustnessSecure RideSharing ProtocolEach sensor ni encrypts its value vi as ci = vi + gi(ki) mod M, and sets its corresponding bit in the P-Vector.2. The resulting ci values are aggregated using the Cascaded RideSharing protocol, which results in the sink receiving the value C = i ci mod M.3. The sink computes the aggregate key value K = i gi(ki) mod M for each i P- Vector. The sink extracts the final aggregate value V = i vi = C K mod M.ProtocolniP2P3P1

ERROR

OK Got it

ci = vi + gi(ki) mod MP-Vector[i] = 1L-Vectorn1n2nn

nir-bit = 0

e-bit =1ReceiverSecure RideSharing Protocol P-Vectorn1n2nn

ni1 .. 1njniP2P3P1

ci ; P-Vector[i] = 1nj

cj ; P-Vector[j] = 1Now I can recover the plain aggregate value given the P-vectorReceiverEvaluation Comparison of four protocols using the CSIM simulatorSpanning-tree: no fault tolerance, but efficient for power!Cascaded RideSharingOur confidentiality-preserving fault-tolerant aggregation protocolOur protocol with state compression Comparison metrics:Average relative RMS error in aggregated resultsAverage energy consumed per node per epochAverage message size transmitted per node per epoch

Parameter Value RangesTotal number of nodes 300, 400, 500, . . . ,1000Link error rate 0.05, 0.10, . . . , 0.35Number of primary + backup parents max(3)Participation level (% of nodes reporting values) 1.5%, 2.5%, 5%, . . . , 25%SIMULATION PARAMETERS28More Simulation ParametersParameter Possible valuesSquare area320320 ft2 gridRadio range of each node30 ftSimulations10 simulation runs each 30 epochsSensor NodesMica2Data Transmission power consumption65 mWListening and reception power consumption21 mWNetwork Bandwidth38.4 KbpsCrypto usedRC4 stream cipherOptimization (Compression)RLE standard compressionSIMULATION PARAMETERS -- cont291- Effect of Link Error Rate

48.2% improvement in RMS

Constant overhead

Constant overhead302- Effect of Participation Level

Only 7.1% increase

Only 3.6% increase313- Effect of Network Density

90.2% improvement using optimization32Thank you

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