convergecasting in wireless sensor networks master’s thesis by valliappan annamalai committee...
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Convergecasting In Wireless Sensor Networks
Master’s ThesisbyValliappan Annamalai
Committee membersDr. Sandeep GuptaDr. Arunabha SenDr. Hasan Cam
Outline Problem Statement Preliminary information System model Proposed Algorithms Results Conclusion and Future Work
Problem Statement Network construction in a sensor
network for Convergecasting Must minimize time consumed for
data collection
Group Communication Patterns Broadcast Multicast Convergecast
0
1 2
5
3 4
6
Broadcast & Convergecast
Broadcast
Convergecast
Multicasting
0
1 2
5
3 4
6
*
**
*
* Indicates Multicast GroupMembers
Group Communication in Wired Networks Done at the network layer Each pair of nodes can have a
separate connection between them Nodes usually share a bus Sharing leads to collision Collision and retransmission leads to
power wastage.
Group Communication in Wireless Networks Common medium for communication Need a contention based reliable MAC
layer in wireless networks Contention increases power consumption For real time data collection, allocating a
separate channel for each pair of nodes Channel can be divided based on TDMA,
FDMA and CDMA
Sensor Network Set of sensors that collectively form
a network. Communication medium Frequency used part of ISM band Constraint
Power Computation Memory
Applications of Sensor Networks Military
Surveillance reconnaissance
Environment monitoring Fire and flood detection
Health monitoring Applications make use of broadcasting
and convergecasting Latency must be kept to a minimum
Related Work Pegasis: Chain construction for data
aggregation Energy consumption high Delay is high
Wave Expansion approach Less reliable
Broadcast tree construction algorithm proposed by I. Chlamtac
Contribution of this Research Work Channel allocation is NP-Complete Two network construction and
channel allocation algorithms (CTCCAA) for convergecasting.
Currently these allocate time slots and codes
Same network can also be used for broadcasting
System Model Set of nodes placed in the area of interest Nodes are static Controlling node (root node or base
station) Amount of data sensed at each node is
constant Controlling node responsible for network
construction
Convergecast Tree Construction and Channel Allocation Algorithm(CTCCAA)
Two algorithms Pipelined CTCCAA Non-pipelined CTCCAA
Centralized algorithms capable of allocating codes and slots
Node position given as input
Pipelined CTCCAA Data collection starts at the leaf
nodes. Propagates towards the root node. Generates a parent child relationship
between nodes
Constraints No two nodes that have parent(s) in
the transmission range of each other share the same channel
Slot assigned to parent is less than the one assigned to its children
Example that illustrates the working of Pipelined CTCCAA
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1 2
3 4 5
1 2
2 3 4123
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Maximum SlotSize = 3 * xWhere,x is the numberof bits sensed byeach node
Non-pipelined CTCCAA Data collection at independent and
non-interfering parts of the network Each node has buffering capability Used for non-real time data
collection Algorithm is similar to pipelined
version but the reversal of slots is not done
Constraints Slot assigned to a child need not be
less than the slot assigned to the parent
If a child has two possible parent it is assigned to the closest parent
Example: Slot assignment for non-pipelined CTCCAA
Comparison Metric
Latency Convergecasting
Graphs with random node placement was generated
Calculated time taken for convergecasting on a broadcast tree (Tb,c)
Calculated time taken for convergecasting on the network constructed by pipelined CTCCAA (Tc,c)
Comparison … Broadcasting
Calculated time taken for broadcasting on a broadcast tree (Tb,b)
Calculated time taken for broadcasting on the network constructed by pipelined CTCCAA (Tb,c)
Results for pipelined convergecasting
Ratio on time taken for pipelined convergecasting on graphs with node density 0.3 nodes / unit ^ 2
Ratio on time taken for pipelined convergecasting on graphs with node density 0.5 nodes / unit ^ 2
Results for non-pipelined Convergecasting
Ratio on time taken for non-pipelined convergecasting on graphs with node density 0.3 nodes / unit ^ 2
Ratio on time taken for non-pipelined convergecasting on graphs with node density 0.5 nodes / unit ^ 2
Results for Broadcasting
Ratio on time taken for broadcasting on graphs with node density 0.3 nodes / unit ^ 2
Ratio on time taken for broadcasting on graphs with node density 0.5 nodes / unit ^ 2
Conclusion & Future work The algorithms proposed
successfully construct networks for convergecasting that reduces latency
Got accepted for WCNC 2003 Better slot allocation algorithm that
completely eliminates idle time wastage
References “Tree-based Broadcasting in Multihop Radio Networks” by I.
Chlamtac and S. Kutten “The Wave Expansion Approach to Broadcasting in Multihop
Radio Networks” by I. Chlamtac and O.Weinstein “Directed Diffusion: A Scalable and Robust Communication
Paradigm for Sensor Networks” by C. Intanagonwiwat, R. Govindan and D. Estrin
“Frequency Assignment: Theory and Application” by W.K. Hale “Pegasis: Power-Efficient Gathering in Sensor Information
Systems” by S. Lindsey and C. S. Raghavendra