Download Presentation - Computer Science

IN-NETWORK VS CENTRALIZED PROCESSING
FOR
LIGHT DETECTION SYSTEM
USING
WIRELESS SENSOR NETWORKS
Presentation by,
Desai, Bhairav
Solanki, Arpan
Outline


Introduction
Algorithm and Methodology
 Formation
of routing topology
 In-network aggregation
 Centralized aggregation



Experiments and Results
Conclusion
References
Introduction
Databases Vs Sensor Networks
Range Queries – much better idea for sensor
networks
 Additional operators have to be added for
Query Language e.g. epoch and duration
 Continuous long running Queries

Data Centric Networking
Combination of Querying, storage and routing
techniques
 Works efficiently if we use the combination as
application specific rather than generalized
like traditional IP based techniques.

Challenges
Volatile System
 Append Only Streams
 High Energy cost of communication
 Variable data arrival rate at different nodes
 Limited Storage on nodes

Centralized Processing
In Network Processing
Objective

Implementing In-network aggregation in real
environment for a Data-centric application

Comparing In-network and Centralized
aggregation approach
Algorithm
and
Methodology
Topology Formation
Collection Tree Protocol
 Base Station – Root of the Collection Tree
 EXTnode = EXTparent + EXTlink to parent
where EXT root = 0
 Detecting Routing Loops

In-network Aggregation

Data aggregation at in-network nodes

Steps required to overcome change in topology
Network Behavior
Two phases

Node discovery phase
 Discovery
of topology
 Assigning time interval

Aggregation phase
 Sense
 Aggregate
 Forward
Assigning time interval
Calculate time interval
Where
Tnode – Time duration of a node
D – Total depth of the tree
Lnode – Level of the node in the routing tree
T – Total epoch duration
Processing Plans
(a) Sensing leaf node
(b) Non-sensing intermediate node
(c) Sensing intermediate node
Node Operation (Sensing leaf nodes)
Node Operation (Sensing intermediate nodes)
Node Operation (Non-sensing intermediate nodes)
Nodes divided in groups
Change in topology
Consequences
Node
20
30
32
Before
Parent
11
2
31
After
Level
3
2
3
Parent
1
3
33
Causes change in depth of the tree
That’s why topology reformation is required
Level
2
2
4
Centralized Aggregation

No discovery of topology

No assignment of time interval

No steps to overcome change in topology

Aggregation of data at the base-station
Node Operation (Sensing leaf nodes)
Node Operation (Sensing intermediate
nodes)
Node Operation (Non-sensing intermediate nodes)
Job of the base station

Collect data from all the nodes

Perform aggregation
Experiments
and
Results
In-network aggregation
In-network aggregation
In-network aggregation
In-network aggregation
In-network aggregation
In-network aggregation
Centralized aggregation
Comparing both approaches
Comparing Bytes Transmitted
Conclusion

Lesser number of Hop counts

Low amount of bytes transmitted

Lower energy consumption
References
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C. Intanagonwiwat, R. Govindan, and D. Estrin, Directed Diffusion: A Scalable and Robust Communication
Paradigm for Sensor Networks, In Proceedings of the Sixth Annual International Conference on Mobile
Computing and Networks (MobiCO, August 2000)
David Gay, Phil Levis, Rob Von Behren, Matt Welsh, Eric Brewer, and David Culler, “The nesC
language: A holistic approach to networked embedded systems,” in SIGPLAN Conference on
Programming Language Design and Implementation (PLDI’03), June 2003.
J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D. Estrin, and D. Ganesan, “Building
Efficient Wireless Sensor Networks with Low-Level Naming,” Proceedings of the ACM
Symposium on Operating Systems Principles (SOSP), October 2001.
Wendi Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan, Energy-Efficient
Communication Protocols for Wireless Microsensor Networks, Proc. Hawaaian Int'l Conf. on
Systems Science, January 2000.
Z. Cheng and W. Heinzelman, “Flooding Strategy for Target Discovery in Wireless Networks,”
Proceedings of the Sixth ACM International Workshop on Modeling, Analysis and Simulation of
Wireless and Mobile Systems (MSWiM), September 2003.
D. Braginsky and D. Estrin, “Rumor Routing Algorithm for Sensor Networks,” Proceedings of
ACM WSNA, September 2002.
References
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J. Bonfils and P. Bonnet, Adaptive and Decentralized Operator Placement for In-Network Query
Processing, Telecommunication Systems - Special Issue on Wireless Sensor Networks, January
2004
S. Madden, M.J. Franklin, J.M. Hellerstein, and W. Hong, TAG: a Tiny AGgregation Service for
Ad-Hoc Sensor Networks, 5th Symposium on Operating System Design and Implementation
(OSDI 2002), December 2002
Y. Yao and J. Gehrke, The cougar Approach to In-Network Query Processing in Sensor
Networks, SIGMOD, March 2002
S. Madden, R. Szewczyk, M.J. Franklin, and D. Culler, Supporting Aggregate Queries Over AdHoc Wireless Sensor Networks, Mobile Computing Systems and Applications, June 2002
S. Ganeriwal, R. Kumar, and M. B. Srivastava, Timing-Sync Protocol for Sensor Networks,
Proceedings of ACM SenSys’03, November 2003
TinyOS Mailing list, http://www.tinyos.net/
TinyOS Naming Conventions, http://www.tinyos.net/tinyos-1.x/doc/tutorial/naming.html
(TinyOS Introduction 2003)
Getting Started with TinyOS and nesC, http://www.tinyos.net/tinyos-1.x/doc/tutorial/lesson1.html
(Dissemination Protocol 2004)
Dissemination, http://www.tinyos.net/tinyos-2.x/doc/html/tep118.html
References
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(Collection Protocol 2004)
Collection, http://www.tinyos.net/tinyos-2.x/doc/html/tep119.html
(The Collection Tree Protocol 2004)
CTP-Collection Tree Protocol, http://www.tinyos.net/tinyos-2.x/doc/html/tep123.html
“Networking Wireless Sensors” by Bhaskar Krishnamachari. Cambridge University Press, 2005
“Wireless Sensor Networks – An Information Processing Approach” by Feng Zhao, Leonidas
Guibas. Morgan Kaufmann Publishers, 2004