1 EnviroStore: A Cooperative Storage System for Disconnected Operation in Sensor Networks Liqian Luo, Chengdu Huang, Tarek Abdelzaher John Stankovic INFOCOM

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EnviroStore: A Cooperative Storage System for Disconnected Operation in Sensor Networks

Liqian Luo, Chengdu Huang, Tarek Abdelzaher

John Stankovic

INFOCOM 2007INFOCOM 2007

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Outline

Introduction Design Implementation Evaluation Conclusion

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Introduction (1/3)

Data Collection A sensor network is connected to the base

station that collects the data. near-real-time information is desirable object tracking, event notification…etc

Some applications do not require real-time information environmental monitoring temperature, light variation Disconnected Network Model

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Introduction (2/3)

Disconnected Network Model No need to maintain a base station in the field. No need to connect every node as well as the base

station. But, not preclude contact with a base station.

opportunistic data upload via data mules

Primary Concern to maximize effective storage capacity to minimize data loss flash memory overflow and power consumption

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Introduction (3/3)

EnviroStoreEnviroStore a cooperative storage system employ data redistribution scheme also consider the rate of energy consumption can delay the onset of data loss with large input

data imbalance

Communication-centric

Storage-centric

path routing, data aggregation, …etc maximize effective storage capacity

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DesignSystem Model

Sensory data must be buffered until an upload opportunity arises.

partitioned network island

Share data across partitioned networks through mobile mules.

disruption-tolerant!

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DesignIn-network Data Redistribution

Data Redistribution to balance storage utilization… Offloading data from nodes that are highly

loaded to nodes that are not.

Perfectly balanced system is not energy-efficient. excessive and unnecessary data dissemination Not to start offloading data too early! lazy-offload scheme

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Lazy-offload Scheme to postpone data balancing until the latest possible time allow certain imbalance between neighboring nodes use local information only

Node i decides to offload data when…

imbalanceiiTHi RR-Rand RR

: remaining storage size : threshold value

: average remaining storage of the neighbor

: level of local imbalance

iR

iRTHR

imbalanceR

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Node i should select the destination node from underloaded neighbors. whose remaining storage size is above should prevent data ping-pong choosing under loaded neighbor with probability

(proportional to its remaining storage) amount of data to be transferred…

iR

When

to offload data

Who

to offload data

How Much

to offload

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Node i selects node j as the redistribution destination. Not to reverse the direction of imbalance.

further avoid data ping-pong

So, the amount of data to be transferred:

jijj R - D - RR Δ

iiji R D R

iijjij -RR, -RR-R D Δmin

: node advertisement threshold

: amount of data transferred

ΔR

ijD

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Our algorithm keep track of... remaining free storage remaining node energy

Node i could invoke or accept data redistribution when…

i

i

i

i

S

R

E

Ωremaining energy of node i

initial energy of node i

remaining storage of node i

initial storage of node i

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DesignCross-partition Data Redistribution

A

B

partitioned network island

mobile data mules

mR-αRα )1(calculate

mule advertisement message mule advertisement message (high frequency)(high frequency)

node advertisement message node advertisement message (low frequency)(low frequency)

mRR

Upload or Download?

Upload or Download?

: average remaining storage

: available storage on the mulemRR

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DesignCross-partition Data Redistribution

State transition of a sensor node in cross-partition data redistribution.

Upload data to the mules.

Download data from the mules.

use back-off timersfrequency difference frequency difference between nodes and mules!between nodes and mules! proportional to current occupancy ratios

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ImplementationSystem architecture for sensor nodes

Reading and Writing log items.Send advertisement messages and maintain neighbor table. Determine whether the current node should offload data to the neighbor or the mule.Start data transfer towards a selected destination.Provide reliable unicast for nodes to transfer log items.

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ImplementationLocal Storage Structure

Circular Buffer containing continuous log items

Random Access is not required.

Not need for any complex space management

Prolong flash lifetime by balancing write access.

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ImplementationUser Interface

EnviroStore supports two types of log files.

Log-array Files simultaneously written by different nodes attributes of an environmental event that is independently

monitored by multiple nodes

Log-sequence Files one writer at a time Multiple nodes should coordinate with each other. useful for tracking moving objects

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ImplementationUser Interface

Example: Different Types of Log Files

to obtain the temporal and spatial distribution of the temperature in Room 303

to track the position of a vehicle

Hand off leadership from node to Hand off leadership from node to node!node!

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Evaluation

EnviroStore is implemented in nesC on TinyOS. Use TOSSIM to experimentally evaluate the performance.

Deployment Configuration Field: 36 nodes (6x6 Grid)

Data Mules The movement of mules follow a constraint random walk

model. Speed: 5 ft/s Turning Angle: random between and

2ft8080

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π-

6

π

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Evaluation

Pentium4 1.7 GHz machine with 1G RAM.

Storage Capacity Sensor Nodes: 16 KB Data mules: 64 KB

Parameter Settings : 0.95*S : 0.05*S : 0.01*S

THR

imbalanceR

Rto accelerate heavy-weight simulation…

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EvaluationI. Single Disconnected Sensor Network

Scenario 1: Single Disconnected Sensor Network

Deployment Configuration

Node 4Node 4

non-zero input ratenon-zero input rate

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Without EnviroStore

data loss caused by insufficient local storage

256 sec

Data storing rate at different time

Drop below the input rate!

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1900 sec

With EnviroStore

Drop below the input rate!

drop gradually…

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To investigate the effects of on the energy consumptionTHR

Number of data messages sent per second

540 sec180 sec 1200 sec

significant energy due to lazy offload!

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We explore a more general scenario. Data rates are uniformly distributed among nodes. The input rates are random samples from an exponential

distribution. Mean = 16 B/s

Example:

input rates at different nodes

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500 sec 800 sec60% improvement!

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EvaluationII. Partitioned Sensor Network with Mules

Scenario 2: Partitioned Sensor Network with Data Mules


64 B/s

32 B/s

0 B/s

0 B/s

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96 B/s

512 sec

256 sec 1900 sec

2400 sec 2800 sec

Delay data loss by a factor of more than 10.

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Distribution of total stored data after 3600 sec

Without mules Without one mule

64 B/s32 B/s0 B/s

0 B/s 64 B/s32 B/s0 B/s

0 B/s

overloaded

underloaded

more balanced storage occupancy!

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Number of data messages per second

36

1900 sec 2400 sec

drop

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Scenario 2: Add base station and extra nodes

Base StationExtra Nodes

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Data storing rate of the base station over time

0

Ensure the connectivity between sensor nodes and the base station.

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Total stored data of the base station over time

Disconnect the network partitions from the base station and add some data mules.

More mules can increase the rate of uploading data to the base station.

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Conclusion

EnviroStore cooperative storage system maximize network storage capacity in-network and cross-partition data redistribution opportunistic data offload

Plan to further extend the work. controllable data mules data replacement policies Evaluation on real hardware platforms.

Documents

1 EnviroStore: A Cooperative Storage System for Disconnected Operation in Sensor Networks Liqian Luo, Chengdu Huang, Tarek Abdelzaher John Stankovic INFOCOM