1. University of Helsinki, Finland
Kimmo Raatikainen
Chiara Braghin Stefano Campadello
Heikki Helin Oskari Koskimies
Pauli Misikangas Mikko Mäkelä
Sampo Pyysalo Sasu Tarkoma
University of Helsinki, Finland

2. Overview of Presentation
Monads project
Goals
Architecture
Predicting Quality of Service
Other Research Issues
Agent Communication Layers
Wireless Java RMI
Partitioning Applications with Agents

3. Monads Research Project
Areas of research
usefulness of agents in mobile computing?
(Dis)Connection Management
Bandwidth Optimisation
Easy to use API
Supporting Communication with legacy software
agent communication in wireless environments
adaptability to available resources
short-term predictions of available resources

4. The Nomadic environment
A mobile computer connected to a network with a wireless connection
Characteristics of wireless networks
low throughput, highly variable delays, sudden disconnections, ...
Nomadic users need special support
Intelligent and adaptable applications
Optimized communication

5. Monads Adaptation Model
Adaptability
Adaptability
User
Interface
Agent
Service
Agent
Service
Terminal
Equipment
Co-operation
Data
Comm.
Agent
Adaptability
Communications
Infrastructure

6. Monads layered Architecture

7. Monads System Services

8. Predicting QOS Minimal Adaptation Uses of Prediction
Detect changes in the Quality-of-Service
Adapt to the current QoS
Adaptation may come too late
Uses of Prediction
Scheduling decisions, Data Prefetching, Connection Management
Examples
What is the expected data transfer within next ‘t’ seconds
What is the expected time to transfer the ‘x’ KB of data

9. Learning to Predict QOS
Predictions can be achieved by learning how certain quantities affect the QoS
location of the terminal
time of day
day of week
recent QoS values
Division into sub-problems:
predicting terminal movement
predicting QoS at given location and time

10. System Architecture

11. QOS Prediction - System Components
Location Service
Reads location information from a GPS device
Builds a Waypoint Map
Represents the current location as a point on a straight between two waypoints
QOS Management Service
Provides information about the current QoS
Perception Service
Centralized collection of observable values

12. System components (contd..)
Route Modeler Agent
Actively learns the regular routes of a user
Provides predictions about user movement
given a sequence of waypoints, which will be the following waypoints?
QOS Modeler Agent
Actively learns the characteristics of the QoS on the routes traveled
Provides predictions about the QoS at given location and time

13. System components (contd..)
QOS Prediction Agent
An intelligent agent that provides QoS predictions
combines predictions made by the modeler agents
Selects between alternative ways to predict
Informs other agents when the QoS is about to change significantly

14. Communication Layers Interaction Protocol Communication Language
FIPA-query, FIPA-request
Message Coupling
Communication Language
KQML, FIPA-ACL
Binary Encoding of Message/Content
Message Transport
HTTP,RMI,IIOP
Transport Protocol
SMS,MDCP,TCP

15. Related Research Results
Optimized RMI
Adaptation through Application Partitioning
terminal characteristics
wireless link quality