This document discusses using network coding protocols for smart grid communications. It proposes using random linear network coding (RLNC) and tunable sparse coding protocols. These protocols are compared to the currently used master-slave scheme through simulations in NS-2. The results show that the network coding protocols can collect data packets from more households in less time compared to the master-slave scheme. Specifically, collection time is improved by 3-10 times when using the network coding protocols with and without feedback.

1. Network Coding
Protocols for Smart Grid
Communications
TEAM- MASTERMINDS

2. STRUCTURE
BACKGROUND
PROPOSED NETWORK CODING
PROTOCOLS
COMPARISON RESULTS
CONCLUSION
2

3. B A C K G R O U N D
• SMART GRIDS
• SMART METERS
• CURRENTLY USED - MASTER SLAVE SCHEME
3

4. A smart grid is an electricity network based
on digital technology that is used to supply
electricity to consumers via two-way digital
communication. 4

5. There are three main benefits to smart
meters:
SMART METER
More accurate
No one has to come to your home to
read your meter
Better oversight and management of
our energy use
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7. CURRENTLY USED
SCHEME
The master (in
this case, the
substation)
requests data
from each
slave (the
secondary
substation) in
a Round Robin
fashion.
Master sends
a data-request
packet to the
intended
slave,
followed by a
transmission
of data from
slave
If the data is
received
correctly, the
master
proceeds to
the next slave.
Otherwise,
the master
repeats the
process
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8. GIST
• NETWORK CODING
• RLNC
• TUNABLE SPARSE
CODING
ONE PHASE ( NC)
TWO PHASE ( NC- fb)
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9. WHY USE NETWORK CODING??
Network coding saves
• one transmission (thus saving energy)
• one time slot (thus reducing the delay)
Structure of the coded packet for the general case.
ATypical wireless coding example 9

11. Tunable Sparse Coding
There are three key ideas in tunable sparse network coding:
1
• Sparse coding is more beneficial at the
beginning of a transmission session
2
• Dense coding is required towards the end of
the sessions for fast completion
3
• Sparse coding translates in reduced
complexity
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13. C O M P A R I S O N R E S U L T S
13

14. COMPARISON SETTINGS
• NS-2 network simulator
• Wireless Setting
• Collects one packet of 100 bytes
from each sender every 15 min.
FIRST EXPERIMENT
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15. 15
• BS and the secondary
substations are positioned within
a rectangle of 3300 m
per 2500m. Around each substation,
we add 32 households

16. (a) Average percentage of collected packets (c)Average collection time
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17. • Topology shown in fig (a) fitting in a
rectangle of 1000 m per 1400 m.
• 32 households are distributed uniformly at
random within an annulus around each
secondary substation, but with a minimum
radius of 10 m and a maximum radius of
100 m. The remaining
conditions are similar to the 1st experiment.
SECOND EXPERIMENT
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18. (b)Average percentage of collected packets. (c) Average collection time.
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19. With network coding, the data packets
are collected much sooner than the
defined deadline.
Compared with the MS reference protocol, the
protocols discussed here exhibited a threefold
(without explicit feedback) to tenfold (with explicit
feedback) improvement in the collection time.
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