Post on 16-Dec-2015
IN-NETWORK VS CENTRALIZED PROCESSINGFORLIGHT DETECTION SYSTEMUSINGWIRELESS 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 phaseDiscovery of topologyAssigning time interval
Aggregation phaseSenseAggregateForward
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
(b) Non-sensing intermediate node(a) Sensing leaf 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
NodeBefore After
Parent Level Parent Level20 11 3 1 230 2 2 3 232 31 3 33 4
Causes change in depth of the tree
That’s why topology reformation is required
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
ExperimentsandResults
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
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 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 Ad- Hoc 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
(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