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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).