Information Service Architecture
Weilin Zhong
Nov. 14, 2001
CS851 Sensor Network
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Outline
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
Distributed Information Services and
Architecture
Random, Ephemeral Transaction Identifiers
(RETRI)
Nov. 14, 2001
CS851 Sensor Network
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Outline -- ISA

Information Service Architecture
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Sensor Network Applications
Information Services in Sensor Network
Information Service Architecture (ISA)
Critiques
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Outline --RETRI
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Random, Ephemeral TRansaction Identifiers
(RETRI)
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Global vs. Local ID
RETRI & Advantages
Address-Free Fragmentation (AFF)
Theoretical Model
Critiques
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Distributed Information Services and
Architecture for Sensor Network
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Applications of Sensor Network
Traffic Control
Sensor Network
Inventory
Terrain Exploration
Smart Environment
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Challenges
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Massive Number of Nodes
Spontaneously Deployment
Dynamic adaptable and Self-organizing
Integrated & Cooperative Service
Limited Resources and Capabilities
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What does the paper suggest?
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
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Lookup Service
Composition Service
Adaptation Service
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Distributed Services

Lookup Server
Room 236
2
ID Service
Location
1
Temperature R236
2
Light
Noise
R236
…
…
…
Nov. 14, 2001
1
Register
R236
3
3
Accept/Reject
Lookup
Server
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Distributed Service Discovery
Service
Provider X
Higher-level
Cluster
Higher-level
Cluster
Lookup
Service
Client
Sensor
Cluster
Checks own registry
first before forwarding
discovery request
Server C
Lookup
Server B
Lookup
Server A
Update new Service
location information
in local cache
Nov. 14, 2001
Update new service
location information in
local cache
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Discovery for Mobility Nodes
Service
Higher-level
Cluster
Provider X
Higher-level
Cluster
Sensor
Cluster
Lookup
Service
Client
Server C
Notify Change in
Lookup
Service X new Location
Server B
Lookup
Server A
Update new Service
location information
in local cache
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Compositional Server
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Node Addition and Removal
Network Abstractions
Cluster Formation & Hierarchical composition of clusters
Formation
3rd-level
Cluster C
:Cluster Header
2nd-level
Cluster B
Composition Server C
Formation Compositional
Composition Server B
Sensor
Cluster
A
Nov. 14, 2001
Service
Compositional Abstraction C
Formation Compositional
Composition
Server A
CS851 Sensor Network
Service
Abstraction B
Service
Abstraction A
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Compositional Service

Temperature Control System
Service Abstraction
Formation Compositional Building
Average
Composition Server of Bldg
Temperature
Building
Formation Compositional Floor Average
Floor 1
Composition
Server of Floor Temperature
Formation Compositional Room Average
Room
Composition
Room 101
Room 102
Server of Room Temperature
Room 103
:Cluster Header
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Adaptation Server
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Monitor During Normal Execution
Schedule reconfiguration operations when needed
Analytical Tools
Analytical Tools
Dependency
Dependency
Compositional
Lookup
Adaptation
Compositional
Lookup
Adaptation
Server
Server
Server
Server
Server
Server
CS851 Sensor Network
Accept /Reject
relocate
Register
Formation
Composite
Accept /Reject
De-register
Formation
Composite
Nov. 14, 2001
Monitor/Reconfigure
Monitor/Reconfigure
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Adaptation Service
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Temperature Control
Average Temp with
90% Confidence Level Accept/Reject
Compositional
Server
100 samples/sec
Integrated
Monitoring
Adaptation
Server
Sampling 33 times/sec
ID Service
Location
1
Temperature
R101
2
Temperature
R101
3
Temperature
R101
Nov. 14, 2001
Lookup
Server
CS851 Sensor Network
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Adaptation Service

Temperature Control (Add a node)
Average Temp with
90% Confidence Level Accept/Reject
Compositional
Server
100 samples/sec
Integrated
Monitoring
Adaptation
Server
ID Service
Location
1
Temperature
R101
2
Temperature
R101
3
Temperature
R101
4
Temperature
R101
Nov. 14, 2001
Sampling 25 times/sec
Register
Accept
Lookup
Server
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Information Service Architecture
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Application Systems

Collaborative Signal Processing
Integrated
Integrated
:Cluster Header
Reading
Reading
Signal Processing
Agent
3rd-level
Cluster C
Intermediate
2nd-level
Cluster B
Integrated
Data fusion
Reading
Mobile Agents
Sensor
Cluster
A
Sub Area
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Temperature Control System
Temperature ?= 26
Lookup Server
Wherever there is
person
UserID
Name
Location
Database
1
Dave
R101
Server
2
Jack
R102
Monitoring/Control
Register
Accept
Lookup Server
Register
Room 101
Nov. 14, 2001
Room 102
Room 103
CS851 Sensor Network
Accept
ID
S
L
1
T
101
2
T
101
3
T
101
4
T
102
5
T
102
6
T
102
7
T
103
8
T
103
9
T
103
19
Temperature Control System
Temperature ?= 26
Lookup Server
Wherever there is
person
UserID
Name
Location
Database
1
Dave
R101
Server
2
Jack
R102
Register
Accept
Sub-query
Sub-query
Monitoring/Control
there (temperature,
is a person? R102,26)
(temperature,Where
R101,26)
R101, R102
Mediator
Mediator
Object Server
ID
S
L
1
T
101
2
T
101
3
T
101
4
T
102
5
T
102
TL
102
7
T
103
8
T
103
Lookup Server
Room 101
Collaborative
Processing Agent 1
Room 102
Collaborative
Processing Agent 2
Room 103
Sensor
Lookup
Available Sensors
OID
S6
1
Ave T
2
Ave
T
9
R101
R102 103
T
& their locations
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Correct Assumption?
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Sensor = Service Provider?
Problems
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Identifiable Sensor ( unique ID, Location)
Register/De-register each sensor
Highly dense sensor network – smart paint
Highly dynamic sensor network – traffic control
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Correct Assumption?
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Servers are properly deployed in advance?
Problems
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Static Architecture
Hostile Environment – battlefield
Moving Sensor Network – smart dust
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Critiques
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Critiques for Distributed Information Services
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Globally unique identifiers
GPS locations are used
Register/De-register every sensor at every movement
Static and Pre-deployed Architecture
Bad scalability
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Random, Ephemeral Transaction
Identifiers -- RETRI
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Outline --RETRI

Random, Ephemeral TRansaction Identifiers
(RETRI)





Global ID vs. Local ID
RETRI & Advantages
Address-Free Fragmentation (AFF)
Theoretical Model
Critiques
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Why not Global Unique ID?
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Global Unique ID can be very expensive in
Sensor Network
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Small Data Rate/Size vs. Large Global Unique ID size
Highly dynamic vs. Static Assigned Global Unique ID
Local Unique ID is desirable
Traditional Local ID
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Central Address Authorities (DHCP)
Listening and Scoping (Multicast address
allocation)
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Basic Idea of this paper
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5
4
1
Transaction-based ID
Reduce the transmission of
header bit
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3
2
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Great scalability
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5
4
1
3
2
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Header bits increased with
transaction density instead of
number of nodes
Temporal and locally unique ID
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Nov. 14, 2001
Header bits transmitted
H = 3 bit * 10 packet * 10 trans
In Static allocated global ID
H = 16bit * 10 packet * 10 trans
Avoid expensive global Ids
ID is reusable
Collision is not a concern
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Address-Free Fragmentation
Data Packet
Data Packet
AFF Sender
ID
ID
AFF Receiver
ID
ID
ID
ID
transaction
Collision
ID
ID
ID
AFF Sender
Data Packet
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Theoretical Model
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Efficiency Metric
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Static Allocation
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E= Useful Bits Received/ Total Bits Transmitted
Estatic = D / ( D + H)
Address-Free Architecture
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Eafa = D X P (Success) / (D + H)
P(Success) = ( 1 – 1/2H)2(T-1)
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D: bits of Data
H: bits of header ( identifier)
T: transaction density T, the average number of concurrent transactions
visible at any single point in the network.
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Efficiency Curve
Optimal Balance
 Superior with transaction
Locality

Transaction
Density
Optimal
Balance
Bits --- E
16
9 – 60%
256
13 – 52%
64k
21 – 40%
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Efficiency Curve – Larger Data Size
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Increasing Optimal Header
Length
Static Allocation wins
Reasons:
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Larger data size amortizes
the cost of static allocation
Large data size increase the
cost of collisions
The cost of collision is higher
than the benefits gained
from sending less identifier
bits.
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When AFF is superior?
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AFF wins
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Large number of nodes
Small transaction density
Small data rate/size
Lower-power radio and
simple MAC protocols
=> Sensor Network
Nov. 14, 2001
Static Allocation Wins
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Small number of nodes
High transaction density
Large data rate/size
High-power radio and
complex MAC protocols
=> Ethernet
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Critiques of AFF

Problems with AFF
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Hop-to-hop transmission
Store and forward model
1
3
Transaction
5
Transaction
Transaction
Transaction
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Questions?
Thank You!
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