This document describes KasadakaNet, a machine-to-machine communication system for sharing data in rural areas using a "pass-by" approach. It uses a combination of sneakernet transport of devices called Kasadakas along with local WiFi networks created by a device called the Wifi-donkey. The system was evaluated through experiments measuring factors like success rates and request times under different conditions like travel speed and query sizes. The results showed the system can enable knowledge sharing in rural scenarios with low-cost hardware and open source components, providing a viable approach for machine-to-machine capabilities in information and communication technologies for development.

1. Machine-to-machine
communication in rural conditions:
Realizing KasadakaNet
By Fahad Ali
Supervised by Victor de Boer

2. Contents
● Related works
● Problem description
● Research question
● Our solution: KasadakaNet
● Evaluation
● Discussion and conclusion

3. The Kasadaka
Related works
● Enables information services for
the rural poor
● Rapid prototyping platform: allows
easy creation of applications for new
use cases

4. M2M Communication
Related works
● Transferring data between machines over some type of network
● Over the internet, local Wifi/Bluetooth networks, cellular networks, etc.
● M2M communication in rural conditions?

5. Problem description
● Lack of data sharing between devices
● Pass-by approach:
sneakernet + local wifi networks
● Case: Kasadaka platform

6. Research question
● RQ: "How can machine-to-machine communication and semantic data
sharing be achieved using a pass-by communication method in such a way
that it matches requirements from ICT4D use cases?"

7. System overview
KasadakaNet
● Sneakernet + local Wifi solution
● Technical challenges:
○ Semantic data
○ Less human input
● Two components:
○ A set of Kasadakas
○ The Wifi-donkey

8. The Wifi-donkey
KasadakaNet
● Built using Open Source Software (PirateBox, ClioPatria, linux packages,
custom scripts)
● Two main tasks:
○ Host Wifi network and manage connected clients (hostapd, dnsmasq, works out of the
box)
○ When a Kasadaka connects: send SPARQL query to Kasadaka, store RDF result (custom
scripts, configuring linux)

9. Experimental setup: measuring range
Evaluation

10. Experimental setup: Pass-by experiment
Evaluation
● Measured variables
○ Success rate
○ Result file size
○ Request time
● Independent variables
○ Travel speed
○ Query size (# of triples)

11. Experimental setup: Scaling experiment
Evaluation
● Load dataset of 475000 triples
● Side-by-side data transfer
● Measured variables:
○ Request time
○ Result file size
● Independent variable:
○ Query size in # of triples (7 categories: 30, 300, 1k, 5k, 10k, 50k, 100k)

12. Results: Pass-by experiment
Evaluation

13. Results: Scaling experiment
Evaluation

14. Discussion and conclusion
● Results show that the system works in the setting it was tested in.
● Success rate depends mostly on time spent within range.
● What about rural conditions and real scenarios?
● And non-Kasadaka ICT4D implementations?
● A Sneakernet + local wifi solution is a viable approach in extending
knowledge sharing systems with M2M capabilities:
○ low cost hardware
○ open source

15. Questions?