1. Content-Based Music Information Retrieval in Wireless Ad-hoc Networks
Ioannis Karydis
Alexandros Nanopoulos
Apostolos Papadopoulos
Dimitrios Katsaros
Yannis Manolopoulos
Aristotle University of Thessaloniki, Greece

2. A walk in the park… song excerpt propagate reply song excerpt reply
ISMIR 2005
17-Sep-18

3. An emerging paradigm in music distribution
The new trend is here: wireless devices that can do much (lots of MHz!)
The music industry found a blooming application: music has turned into commodity over WWW
How can we extend this success to the new trend of wireless networks?
Is this another way to help piracy?
No! Licensed distribution of digital music offers:
minimisation of distribution costs
custom orders (track selection)
instant delivery (temporal + spatial)
ISMIR 2005
17-Sep-18

4. What we need to make this true…
CBMIR for wireless P2P networks:
Consider the frequent alteration of the network topology
Optimise the traffic for the constrained bandwidths of wireless networks (find effective representations of music data)
Design the routing of music data over the wireless ad-hoc network
ISMIR 2005
17-Sep-18

5. Why not existing (wired) solutions?
In wireless ad-hoc networks two nodes can communicate only if in close proximity (in-range).
Network peers
participate randomly
participate for short term
change frequently their location.
These factors cause existing approaches, e.g., indexing, to become inapplicable.
ISMIR 2005
17-Sep-18

6. Layout Background Problem definition Proposed method
Experimental results
Summary
ISMIR 2005
17-Sep-18

7. Mobile ad-hoc networks
Wireless mobile ad-hoc network (MANET)
Collection of wireless mobile hosts
Temporary network
NO centralised administration
NO standard support services
The ad-hoc nature requires path discovery
Need for routing policies in MANETs
ISMIR 2005
17-Sep-18

8. Routing in MANETs Rely on some form of broadcasting, e.g.:
source-initiated on-demand routing protocols
hybrid routing protocols
Flooding is the simplest broadcasting approach
each node in the network forwards a packet exactly once
generates too many redundant transmissions => broadcast storm problem
To address flooding
probabilistic approaches
deterministic approaches
ISMIR 2005
17-Sep-18

9. Layout Background Problem definition Proposed method
Experimental results
Summary
ISMIR 2005
17-Sep-18

10. Problem definition
Given a mobile client that wants to find music documents that are similar to a query, search all approachable peers in an MANET and return possible answers to the querier.
ISMIR 2005
17-Sep-18

11. Layout Background Problem definition Proposed method
Experimental results
Summary
ISMIR 2005
17-Sep-18

12. Template for CBMIR in MANETs
User poses a query
Query transformed to a representation form R
R is broadcasted to all peers in range
Qualifying sequences (true- and false- positives) comprise an answer-set
Answer-sets are broadcast back to the querier
Resolution of false-positives at:
peers that provide answers
intermediate peers
the querier
Return of actual matches to the user/application
FWD traffic
BWD traffic
ISMIR 2005
17-Sep-18

13. Options to represent the query
The whole query sequence itself (time domain)
Large size
The first few coefficients of a frequency-domain transformation:
DFT, DCT, …
We choose DWT (Haar) transformation
Small size
A sample of the query sequence and the first few DWT coefficients
Medium size
ISMIR 2005
17-Sep-18

14. Options for false-alarm resolution
At the qualifying peers
Possible when using the whole query sequence
No false-alarms
At the querier
When choosing representation only with DWT coefficients
False-alarms (many!)
At the querier, but intermediate peers help
Significantly reduced number of false-alarms
Intermediate peers prune many of them
ISMIR 2005
17-Sep-18

15. Resulting approaches Query representation Resolution FWD Traffic
BWD Traffic CQ
minimal (only coeffs)
at querier
Good (coeffs are small)
Bad (false positives) QL
Maximal (full query)
at peers
Bad (query is large)
Good
(no false positives) ST
Medium (coeffs + sample)
at peers and at querier (+ pruning in the root)
Good (small sample)
Good (pruning policy)
ISMIR 2005
17-Sep-18

16. ST example 1 2 3 4 20% 10% 5% 5 1 2 3 4 20% 10% 5% 5 ISMIR 2005
17-Sep-18

17. Layout Background Problem definition Proposed method
Experimental results
Summary
ISMIR 2005
17-Sep-18

18. Experiments Simulation test-bed 100 network nodes
300 songs (various music genres, e.g. pop, greek, rock, classical) average length 5 min
Each song was randomly repeated 4 times
Mobility simulator (GSTD)
Area 4 km
Peer radius 500m
Peer velocity 5km/h
Metrics
average traffic
time 1st and last result were discovered 2
ISMIR 2005
17-Sep-18

19. Time of 1st & last results vs. Max-hop
Increase in available Max-Hop => more peers examined => longer times
ISMIR 2005
17-Sep-18

20. Traffic vs. Max-hop BWD phase is more demanding for all algorithms
ISMIR 2005
17-Sep-18

21. Time of 1st & last results vs. query size
increase in query size => increased processing required for the determination of matching excerpts
ISMIR 2005
17-Sep-18

22. increase in query size => propagation of larger representations
Traffic vs. query size
increase in query size => propagation of larger representations
ISMIR 2005
17-Sep-18

23. Traffic vs. NF parameter
High NF, limits the effectiveness of the policy for the BWD phase, since most peers are selected at random by this policy
ISMIR 2005
17-Sep-18

24. Traffic vs. initial sample factor
Forward traffic increases with increasing sample size
ISMIR 2005
17-Sep-18

25. Layout Background Problem definition Proposed method
Experimental results
Summary
ISMIR 2005
17-Sep-18

26. significant reduction in response times and traffic
Summary
Introduced CBMIR application in wireless ad-hoc networks
Recognised new challenges posed by wireless ad-hoc networks.
Proposed a novel algorithm, with twofold optimisation:
use of query representation with reducing length,
selective policy for routing answers, which performs additional pruning of traffic.
Result:
significant reduction in response times and traffic
The examined context does not depend on specific features and distance measure
ISMIR 2005
17-Sep-18

27. Content-Based Music Information Retrieval in Wireless Ad-hoc Networks
Thank you!
ISMIR 2005
17-Sep-18