A Mini-survey of Dealing with Faults in Wireless Sensor Networks

Qi Han

Motivation

Current WSNs exhibit high loss rates In indoor environments,

• half of the links: 10% packet loss• A third links: 30% packet loss

At MAC layer, link-layer re-transmissions are unable to mask this loss

Assuming packet loss rateis p, then the probability that a message is successfully receivedAcross n hops is (1-p)n

Understanding packet delivery performance In dense wireless sensor networks J. Zhao and R. Govindan, SenSys 2003 (Best Paper Award)

Taming the underlying challenges of reliable multihop routing in sensor networksA. Woo, T. Tong and D. Culler, SenSys 2003

Strategies to deal with faults

MAC layer Apply ARQ

Network layer: Select high quality paths for data transmission Multi-path routing

• Braided Diffusion• GRAB (Gradient Broadcast)

Transport layer Downstream data delivery

• PSFQ, GARUDA Upstream data delivery

• TAG, ESRT

Braided Diffusion

How to perform energy-efficient and robust dissemination of data from sources to sinkstradeoff between resilience and energy

consumed Based on directed diffusion:

Construct dissemination path from multiple sources to multiple sinks on-demand

D. Ganesan, R. Govindan, S. Shenker, D. EstrinMobiHoc 2001 and MC2R 2002

Directed Diffusion

a) Source periodically broadcasts events at a low rateb) Sink sends a reinforcement message to one of its neighborsc) The message is propagated to the source, hop by hopd) When a node on the reinforced path fails, the sink re-initiates

reinforcement

Drawback: A periodic low-rate flooding scheme notifies the sink and other nodes of available alternate paths --- Consumes energy

Disjoint Multipath

Localized algorithm:-using local information- use two kinds of reinforcements

Braided Multipath

- Alternate paths in a braid are partially disjoint from the primary path

Failure Models (used for evaluation) Isolated failures:

capture independent node failures Patterned failures:

capture geographically correlated failures

Gradient Broadcast

The sink builds a cost field Cost at a node: minimum energy

overhead to forward a packet from this node to the sink along the path

The cost field gives the global direction towards the sink implicitly

• At each hop, only nodes that have costs smaller than the sender can forward the packet

F. Ye, G. Zhong, S. Lu, L. X. ZhangACM WINET 2005

Credit-based Forwarding Mesh

Limit the ‘width’ of the forwarding mesh More than enough paths of

decreasing cost exist A source assigns a credit to

the packets it sends out• Credit: An extra budget that

can be used to send a packet to the sink along a path

• The amount of credit controls the redundancy of the mesh

Reliable Downstream Sensor Data Delivery Data flows from sink to sources for the purpose of

control or management PSFQ

Assumptions: message loss occurs due to the poor quality of wireless links

Hop-by-hop recovery: node In-sequence forwarding

GARUDA: reliable delivery • To all sensors, • To a sub-region, • To minimal sensors to cover the sensing field• To a certain percentage of the sensors

Reliable Upstream Sensor Data Delivery Data flows from sources to sink TAG (Tiny Aggregation):

A node switches its parent in two cases:• Each node monitors the quality of the link to each

of its neighbors by tracking the proportion of packets received from each neighbor

• When a node observes that it has not heard from its parent for some fixed period of time, it assumes that its parent has failed

ESRT: Event-to-Sink Reliable Transport in WSN

Event!

A sensor node

A sensor node that can sense the event

Sink wants reliable event detection with minimum energy expenditure

[Y. Sankarasubramaniam, O. B. Zkan, I. F. Akyildiz, ACM MobiHoc 2003]

[Slides modified based on the class presentation of A. Abouzeid from RPI]

Problem Definition

Motivating application: Reliable detection/estimation of event features based on the

collective reports from a number of sensors, not on individual sensor reports

The sink must decide on the event feature every time units Definition

The reliability of even feature is measured by the number of received data packets

• Observed event reliability ri • Desired event reliability R

Problem statement: (congestion solution) Model any increase in source information as a increase in

the sensor reporting rate f To configure the reporting rate f of source nodes so as to

achieve the required event detection reliability R at the sink with minimum resource utilization

Evaluation Environments-- to study the relationship between f and r

ns-2 simulator 200 sensor nodes 100m x 100m area 40m transmission range 30 byte packets 65 packets buffer size 10 sec decision interval (τ)

Effect of varying sensor reporting rate f on the event reliability r

network gets congested sooner with increasing number of source nodes

r linearly increases with f until f=fmax, then drops After fmax, it is wavy

with increasing n, the drop in r is more significant

This confirms the need for a reliable transport solution with a congestion control mechanism

CongestedNot Congested

Lower reliability than required

Higher reliability than required

OOR

Five characteristic regions

Goal: To stay in

OOR where energy

expenditure is optimal

R

r

Main Idea of ESRT

Sink Based on current state Si, calculates a updated

reporting frequency fi+1, broadcasts it to sensor ndoes

• Si {(NC,LR),(C,LR)}: aggressively update f to reliably track event ASAP (Primary objective: reliably detect event)

• Si{(NC,HR),(C,HR)}: decrease f conservatively (Secondary objective: conserve energy)

Sensors Listen to the sink broadcast at the end of each

decision interval and update f Deploy a local congestion detection support

mechanism

ESRT Actions

Network State

Action

(NC,LR) Multiplicatively increase f,

Achieve required reliability ASAP

OOR f remains unchanged

(NC,HR) Decrease f conservatively

Cautiously reduce energy consumption while not compromising reliability

(C,HR) Decrease f carefully but aggressively to (NC,HR) to relieve congestion

Then, follow (NC,HR) behavior

(C,LR) Decrease f exponentially to relieve congestion ASAP

i

ii

ff

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1(21

i

ii

ff

i

ii

ff

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)/(1

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Stability of ESRT

ESRT converges to OOR from any of four initial states {(NC,LR), (NC,HR), (C,HR), (C,LR)}

From (NC,HR), ESRT stays in the state until converges to OOR Convergence time depends on ε – smaller ε

causes longer convergence time

Congestion Detection Congestion status is required at the

sink to determine the network state Based on expectation of buffer

overflow at sensor nodesDuring a single interval, f and n do not

change much If pending congestion (bk+b>B) is

detected CN bit is set in event reports

From (NC,LR)

Reaches OOR in two intervals

From (NC,HR)

ESRT stays in (NC,HR) until

reaching OOR in five intervals

(C,HR) to (NC,HR) then OOR

(C,LR) to (NC,LR) then OOR

Power savings from (NC,HR)

Reporting rate gets reduced conservatively

while maintaining reliability

What I like about the paper

Collective reliability• Individual sensor ID is not necessary• Each source attaches event ID

Biased implementation• Almost entirely in sink

What I dislike about this paper Sink must broadcast the updated reporting

frequency at high energy so that all sources can hear it Ongoing event transmission would be

disrupted Regulating all sensors to have the same

reporting rate may not work well with heterogeneous sensors

Assuming that sensors report periodically may not be true for all applications

Congestion in WSN not just caused by frequent sensor reporting

My class project- reliable upstream data delivery

Acquisitional query How to interpret the answer A

Is A based on a very incomplete subset What about the remaining sensors

Query may specify its reliability requirements(how good it wants A to be) Percentage of sensors (e.g. A is based on

reports from 80% of the sensors) Recall (answer-set/exact-set)

Quality Metrics

Sensors of interest N

Answer Nyes

Missing at most N-Nyes-Nno

NnoAnswer Nyes

Answer Nyes

recall r=Nyes/(N-Nno)

Problem Description

Given: 1 sink (where continuous queries are injected) and n sensors with constant failures in the sensor network

Objective: minimize energy consumption

s.t. r>=R, where r=Nyes/(N-Nno)

Issues to Address

How to distribute rq from the sink to intermediate nodes ?

Given the assigned rq’, what should each

intermediate node do after finishing the transmission of the reports from all children? Go to sleep immediately Re-transmit immediately Stay awake in case re-transmission is

requeted

Our Approaches

To come

Evaluation Methodology

ns-2 simulator Comparison against

Plain collection (CSMA/CA)Link layer acknowledgement

(CSMA/CA + ack/re-transmission)Multi-path routing