Zone Sharing: A Hot-Spots Decomposition Scheme for Data-Centric Storage in Sensor Networks

Zone Sharing: A Hot-Spots Decomposition Scheme

for Data-Centric Storage in Sensor Networks

Mohamed Aly Nicholas Morsillo

Panos K. ChrysanthisKirk Pruhs

Advanced Data Management Technologies LabDept. of Computer Science

University of Pittsburgh

DMSN’05

DMSN’05 2 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs

Roadmap

Background Problem Statement: Storage Hot-spots Algorithms: Zone Sharing Experimental Results Conclusions


Sensor Networks Data Characteristics

Monitoring Applications: One or more phenomenon

Sensor readings: events An event contains one or more attributes for each

phenomenon under concern Querying load variations

Continuous queries: e.g. habitat monitoring applications Ad-hoc queries: e.g. disaster management applications


Sensor Networks Data Storage Options

Base station storage Events are sent to base stations where queries are issued

and evaluated Best suited for continuous queries

In-Network storage Events are stored in the sensor nodes Best suited for ad-hoc queries


Data-Centric Storage

Quality of Data (QoD) of ad-hoc queries Define an event owner based on the event value Examples:

Distributed Hash Tables (DHT) [Shenker et. al., HotNets’03]

Geographic Hash Tables (GHT) [Ratnasamy et. al., WSNA’02]

Distributed Index for Multi-dimensional data (DIM)[Li et. al., SenSys’03]

Greedy Perimeter Stateless Routing algorithm (GPSR)[Karp & Kung, Mobicom’00]

Among the above schemes, DIM has been shown to exhibit the best performance


Storage Hot-Spots

S1x є

[1,10]

S2x є

[10,20]

S3x є

[20,30]

S4x є

[30,40]

50%

40%

7%

3%


Zone Sharing in DIM

S2x є

[10,20]

y є [1,10]

S3x є

[10,20]

y є [10,20

]

S1x є

[1,10]y є

[1,20]

Z = 0

Z = 10

Z = 11

70%

5%

25%

S1

S2 S3 A = 0

A = 10 A = 11


Zone Sharing in DIM

S2x є

[1,10]y є

[1,10]

S3x є

[10,20]

y є [1,20]

S1x є

[1,10]y є

[10,20]

Z = 01

Z = 00

Z = 1

35%

35%

30%

(donor)

(migrator)

(receiver)

S3

S2 S1 A = 1

A = 00 A = 01


Hot-Spot Decomposition in Zone Sharing


Storage Safety Requirement (1)

Pre-migration load (donor) >> post-migration load (receiver)

ldonor / (lmigrator + lreceiver) ≥ C1

C1 should be greater than or equal to 2 to make sure that the donor is really falling in a hot-spot

Evaluated by donor and receiver


Storage Safety Requirement (2)

Post-migration load (migrator) >> pre-migration load (migrator)

T / lmigrator ≥ C2

C2 should be greater than or equal to 2 to avoid cyclic migrations

Applied solely by migrator


Energy Safety Requirement (1)

Energy consumed (donor) << total energy (donor) T / edonor ≤ E1

E1 must be less than or equal to 0.5 Applied only by donor



Energy consumed (migrator) << total energy (migrator)

(lmigrator + re * T) / emigrator ≤ E2

E2 must be less than or equal to 0.5 Applied only by migrator



Energy consumed (receiver) << total energy (receiver)

lmigrator * re / ereceiver ≤ E3

E3 must be less than or equal to 0.5 Applied only by migrator


Distributed Migration Criterion (DMC)

1. ldonor / (lmigrator + lreceiver) ≥ C1

2. T / lmigrator ≥ C2

3. T / edonor ≤ E1

4. (lmigrator + re * T) / emigrator ≤ E2

5. lmigrator * re / ereceiver ≤ E3


Single-Hop Zone Sharing (SHZS)

Goal: Overall minimal changes to the original DIM

Single Hop Zone Sharing: A zone can be traded at most once Periodic exchange of neighbors information DMC applied locally by nodes No changes needed to GPSR

Applicability: Small Hot Spots


Single-Hop Zone Sharing (SHZS)

Problems: Large hot-spots: overloaded neighbors

DMC hard to be satisfied Zone traded only once

nodes still in hot-spots after migration process Messages pass by original destination (donor) before

going to migrator energy consumption overhead

Solution: Allow a zone to be traded more than once


Multi-Hop Zone Sharing (MHZS)

A zone can be traded more than once A new data structure: Traded Zoned List

Keeps track of the traded zones to redirect messages to their new destinations

An entry is composed of 3 values: (zone address, original owner, final owner)

GPSR changed to check the list first and update the destination field in the message


Roadmap

Background Problem Statement: Storage Hot-spots Algorithms: Zone Sharing Experimental Results Conclusions


Simulation Description

Compare: DIM, SHZS, and MHZS. Simulator similar to the DIM’s [Li et. al., SenSys’03]

Two phases: insertion & query. Insertion phase

Each sensor initiates 5 events Events forwarded to owners

Query phase Queries of sizes 10% to 100% of the attributes ranges


Experimental Setup

Parameter Value

Network size 50 to 300 sensors

Initial energy 50 units

Energy unit energy needed to send one event

C1 & C2 2

E1 , E2 , and E3 0.3

Number of hot-spots 1

Hot-spot sizes (X,Y) 10% - 50% of the events (X)

falling into

10% of the attribute ranges (Y)

Sensor node storage capacity 15 units (events)


Experimental Results: Data Persistence

0

50

100

150

200

250

300

350

400

450

500

50 100 150 200 250 300

Network Size

DIM

SHZS

MHZS

Dropped Events for a network with a (50%, 10%) Hot-Spot


Experimental Results: QoD

0

50

100

150

200

250

300

350

400

450

500

550

50 100 150 200 250 300

Network Size

DIM

SHZS

MHZS

Result Size of a 50% Query for a network with a (50%, 10%) Hot-Spot


Experimental Results: Load Balancing

0

5

10

15

20

25

50 100 150 200 250 300

Network Size

DIM

SHZS

MHZS

Note: An overloaded node is a node reaching its max. capacity

Overloaded Nodes for a network with a (40%, 10%) Hot-Spot


Experimental Results: Energy Consumption

35

36

37

38

39

40

41

42

43

44

50 100 150 200 250 300

Network Size

DIM

SHZS

MHZS

Average Node Energy for a network with a (50%, 10%) Hot-Spot


Conclusions

Contribution: A storage hot-spots decomposition scheme for DCS sensor nets Two versions: SHZS & MHZS

Experimental validation of its practicality Current ZS extensions:

Hot-spots incremental avoidance scheme (submitted for publication)

Possibility of ZS generalizations: Non-uniform loads for individual sensors Upper bound for ZS max. trading hops (nMHZS)


Thank You

Questions ?

Advanced Data Management Technologies Labhttp://db.cs.pitt.edu

Zone Sharing: A Hot-Spots Decomposition Scheme for Data-Centric Storage in Sensor Networks

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