This paper discusses the issues of data representation for one model of context-aware services. This model is based on network proximity ideas. For network proximity, the location information (latitude, longitude) is replaced with information about proximity to network nodes. Network nodes play a role of tags and let position the users within some restricted area. In this paper, we target wireless networks nodes (Wi-Fi access points, Bluetooth nodes). Services for such models provide to mobile subscribers access to certain information, depending on availability (presence) of wireless networks. And another option is a publication by mobile users context-sensitive information associated with wireless networks. In our paper, we discuss key-value data store deployment as a basic persistence mechanism for network proximity. Also, we provide a description for system-wide cache on the base of Bloom filter.

1. On data model for context–
aware services
Dmitry Namiot
Lomonosov Moscow State University
dnamiot@gmail.com

2. Network proximity
• A special model for context-aware
services
• Context described as a set of wireless
networks (nodes)
• Wi-Fi access points, Bluetooth nodes,
Bluetooth tags
• Data could be directly associated with
network nodes.

3. Context
• Context is anything we can add to location
• Models for context-aware systems:
• Data exchange depending on the context
• Situational awareness
• Context-aware data discovery and data
search

4. Network nodes
• Wi-Fi (Bluetooth) devices are everywhere
• Wi-Fi (Bluetooth) is presented in every
mobile phone
• Easy to measure (existing standards)
• We can reuse existing infrastructure
• There is no connection with location (geo-
coordinates)

5. Metrics
• The basic element: fingerprint
• A list of “visible” nodes: ID, MAC-address,
RSSI (signal strength)
• Occurrence counting
• RSSI-based “distance”

6. iBeacons

7. Related projects

8. Related projects

9. CityProximus: prototype
• The prototype (Fraunhofer, FOCUS):

10. CityProximus:shortly
• A set of rules:
• Network fingerprint – > data chunks
(information)
• Can use existing networks as well as
especially created wireless nodes

11. CityProximus: architecture
• Data base for network proximity rules and
content
• Rules editor
• Application server (API for developers)
• Mobile application for access to content
(context-aware browser)

12. CityProximus: data model
Rules: productions
If (fingerprint condition) then { present some
content }
RETE algorithm
REST API with JSON output:
[
{ “type”:”some_type”,”data”:”some_data”},
{“type”: ...},...
]

13. CityProximus: NoSQL model
• Key-value store
• Key: MAC-address
• Value: JSON array
• Apache Accumulo
• Query by index
• Bloom filter for cache