Future and Emerging Technologies (FET)

Future and Emerging Technologies (FET)

The roots of innovationThe roots of innovationThe roots of innovationThe roots of innovation

Proactive initiative on:

Global Computing (GC)

Proactive initiative on:

Global Computing (GC)

1st Year Review,

Cyprus, January 31, 2003

DBGlobe IST-2001-32645

WP1 - System Architecture

DBGlobe Midterm Review, WP 1 2

DBGlobeWP1 - System Architecture

Dieter Pfoser

CTI, Greece

DBGlobe Midterm Review, WP 1 3

Objectives WP 1 - System Architecture To derive appropriate architectures for ad-hoc

databases of mobile entities. Such architectures should be metadata driven. In particular,

– to define what is the appropriate metadata information to describe mobile entities; such metadata must include information at various levels of detail,

– to derive an appropriate metadata definition and manipulation language,

– to design distribution and replication protocols,– to make the architectures dynamically configurable and

extensible, and– to achieve fault-tolerance and availability.

DBGlobe Midterm Review, WP 1 4

Outline

Introduction Architecture

– Infrastructure– Middleware

Semantic Information– Profile data– Content metadata

Parameter ontology Service ontology

– Local vs. global metadata

DBGlobe Midterm Review, WP 1 5

Introduction DBGlobe is a data and service management system for

ubiquitous computing Service-oriented approach, data are wrapped as services PMOs

– “walking” miniature databases

– service providers and/or service requestors

– register services through content metadata

DBGlobe infrastructure has to provide the “glue” for the PMOs to act as a single data source

DBGlobe

iMac

DBGlobe Midterm Review, WP 1 6

Architecture Proposal

Infrastructure (essential functionality)– PMO components– PMOs are organized according to spatial proximity in cells– Cell Administration Servers (CAS), administrative grouping

manage sets of cells and the within located PMOs Middleware (common needed functionality)

– Community Admin. Server (CoAS), semantic grouping of PMOs according to communities

– User agents, supports PMOs that have limited resources and/or are offline

– Dynamic results database

DBGlobe Midterm Review, WP 1 7

PMO Components

“Small” computing devices Service Request Definition Tool

– specify the services, discover and invoke them

Service Definition Tool– create and publish services

Media Previewer– displaying, e.g., images, sound,

movies Service Engine

– to run services

DBGlobe Midterm Review, WP 1 8

Space Model

Geographical 2-D space is divided into administrative areas (grid), each managed by an Cell Administration Server (CAS)

– Similar topology to cellular systems

– Heterogeneous (cell size, technologies…)

Cell2

Access PointCell3

Access PointCell5

Access Point

Cell1

Access Point

Cell6

Access Point

Cell4

Access Point

Cell7

Access Point

AdministrationServerCAS

DBGlobe Midterm Review, WP 1 9

Cell Administration Server (CAS) CAS manages sets of PMO according to spatial

distribution Connect PMOs to the network CASes are interconnected through a network,

e.g., Internet– Aware of their CAS neighborhood– Cooperate, e.g., forwarding of service

descriptions, handling of requests

DBGlobe Midterm Review, WP 1 10

Cell Administration Server

CAS

Service ManagerTem poral Profile

Manager

ServiceTaxonom y

ServiceDescriptionRepos itory

Taxonom yDictionary

ServiceDirectory

PatternAnalyser

ServiceHis tory

Repos itory

Reques tHandler

Server-2-Server Com m . Controller

DeviceController

Service LogManager

ServicePublisher

DeviceRepos itory

CASDirectory

CAS

Distribution Network

CAS

CAS

Service Discovery,Execution

PMO connectivity handling

CAS network

Service profiling

DBGlobe cloud

DBGlobe Midterm Review, WP 1 11

Community Administration Server (CoAS) CAS groups PMOs according to network

topology (admin. grouping) CoAS, semantic grouping of PMOs in

communities (groups of PMOs having the same “interest”)

Contains constructs to facilitate– Service creation– Service discovery (to handle requests, browsing,

creation)– Ontologies

DBGlobe Midterm Review, WP 1 12

Outline

Introduction Architecture

– Infrastructure– Middleware

Semantic Information– Profile data– Content metadata

Parameter ontology Service ontology

– Local vs. global metadata

DBGlobe Midterm Review, WP 1 13

Profile Data - Device Profile

Data that characterizes the PMO

1. The characteristics of the device itself e.g., screen size, memory, keyboard, processor

power

2. The characteristics of the device with respect to the DBGlobe system e.g., credentials, after registering with the DB-

Globe system, a schedule for the availability of data

DBGlobe Midterm Review, WP 1 14

Profile Data - User Profile

Users have preferences with respect to what information they usually request, and

considering mobility, as to when and to where they do this

Creation of profile– Explicitly defined by the user – Implicitly by user behavior patters

Spatiotemporal behavior (mobile ontology based on trajectories)

Previous choices I.e., we (the PMO) records user behavior in terms of

movement and information access

DBGlobe Midterm Review, WP 1 15

Content Metadata

Service-oriented approach, data are wrapped as services

Support of service creation and discovery Parameter ontology

– covering all the parameters used in the various services

– supports service creation Service ontology

– structuring of the services– supports service discovery

DBGlobe Midterm Review, WP 1 16

Parameter Ontology

A service can be based on (i) only data, (ii) other services, or (iii) services and data

Services have an interface consisting of a set parameters

Support the construction of new services by describing the parameters of services in terms of a (global?) ontology

Example: we want to extend a weather service (A) to provide weather information along a route (A*)– (A) Weather: (location, time weather)– (A*)Weather_en_route: (route {weather}).

DBGlobe Midterm Review, WP 1 17

Growing Parameter Ontology

Parameter ontology can be seen as FUP (Frequently Used Parameters)

Services are defined evolutionary, and so is the parameter ontology

One could see services as an aid to gradually denote data semantics

DBGlobe Midterm Review, WP 1 18

Service Ontology

A service is semantically more than the sum of its parts (parameters)

Knowing the semantics of the parameters of the service is not sufficient to reason about the semantics of the service and to locate a service that fits user queries

Service discovery, a means to discover and/or relate services, a service ontology is needed

UDDI?

DBGlobe Midterm Review, WP 1 19

Service Ontology (cont’d)

Tree structure Classification of services into nodes that form a

specialization hierarchy Services are connected to nodes (n:m

relationship) Nodes characterize services, e.g., using

keywords

DBGlobe Midterm Review, WP 1 20

Service Ontology Example

Service ontology contains a large number of services service browsing unrealistic

Based on keywords Thesaurus is used to find entry points to structure Example: request for “travel, taxi, booking” service,

search for close-by appearance of keywords along a path

travel - cityguides - mass transp. info - taxi yellow pages

travel -reservation|booking - taxis

DBGlobe Midterm Review, WP 1 21

Local vs. Global Ontologies

Defining global ontologies is difficult Communities share a common interest, easier at

this local level

DBGlobe Midterm Review, WP 1 22

Conclusions and Future Work

Architecture (CAS - administrative aspect and CoAS - semantic aspect)

Metadata, profile data and ontologies to support service creation and discovery

Making local constructs go global, I.e, towards a global service ontology

Integration of ontologies in prototype implementation

Empirical evaluation, I.e., how difficult is authoring services, will they ever do it?

DBGlobe Midterm Review, WP 1 23

Publications

Karakasidis and E. Pitoura, “DBGlobe: A Data-Centric Approach to Global Computing”. IWSAWC 2002, Vienna, Austria, July 2002

S. Valavanis, M. Vazirgianis, and K. Norvag, “ MobiShare: Sharing Context-Dependent Data and Services from Mobile Sources”. Submitted for publication

C. Ververidis, S. Valavanis, M. Vazirgiannis, G.C. Polyzos, “An Architecture for Sharing, Discovering and Accessing Mobile Data and Services: Location and Mobility Issues”, Presented at: Lobster Workshop, Mykonos, Greece, 4-5 October, 2002

D. Pfoser, E. Pitoura, and N. Tryfona. “Metadata Modeling in a Global Computing Environment”. Proc. 10th ACM GIS, McLean, VA November 8-9, 2002.

G. Samaras, C. Panayiotou, “A Flexible Personalization Architecture for Wireless Internet Based on Mobile Agents”, Proc. ADBIS 2002, September 2002, Bratislava, Slovakia.

C. Panayiotou, G. Samaras, “Personalized Portals for the Wireless User Based on Mobile Agents: Demonstration“, Accepted for Publication, 19th ICDE, 2003 - Bangalore, India. To appear 2003.

DBGlobe Midterm Review, WP 1 24

Meeting the Objectives

The overall architecture of the DBGlobe system (deliverable D3 - Section 2, and three research publications)

The design of the metadata management system (deliverable D2, and one research publication) 

A detailed specification of DBGlobe's functional components (deliverable D3) 

Appropriate distribution, caching and replication protocols and location management (6 research publications).