Industrial Ontologies Group University of Jyväskylä PRIME Project Idea “Proactive Inter-Middleware for Self- Configurable Heterogeneous Cloud Ecosystems”

Slides:



Advertisements
Similar presentations
4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, th IEEE International Conference.
Advertisements

Industrial Ontologies Group University of Jyväskylä Industrial Ontologies Group.
USER-assisted SEMANTIC INTEROPERABILITY in INTERNET of THINGS
Mastering Intelligent Clouds Engineering Intelligent Data Processing Services in the Cloud Sergiy Nikitin, Industrial Ontologies Group, University of Jyväskylä,
Information Day on Embedded Systems - Call 5 Jens Schumacher The Product Avatar Concept as a Platform for Networked Embedded.
Ch. 7. Architecture Standardization for WoT
Zharko A., ”Industrial Ontologies” Group, February 2004 Community Formation Scenarios in Peer-to-Peer Web Service Environments Olena Kaykova, Oleksandr.
Adding Organizations and Roles as Primitives to the JADE Framework NORMAS’08 Normative Multi Agent Systems, Matteo Baldoni 1, Valerio Genovese 1, Roberto.
OntonutsOntonuts Reusable semantic components for multi-agent systems Sergiy Nikitin Industrial Ontologies Group, University of Jyväskylä, Finland.
Semantic Web Services for Smart Devices based on Mobile Agents Vagan Terziyan Industrial Ontologies Group University of Jyväskylä
University of Jyväskylä An Observation Framework for Multi-Agent Systems Joonas Kesäniemi, Artem Katasonov * and Vagan Terziyan University of Jyväskylä,
Date of presentation 1 PROJECT IDEA Topic: PRIME: “Proactive Inter-Middleware for Self- Configurable Heterogeneous Cloud EcoSystems” –Objective Cloud Computing,
Industrial Ontologies Group University of Jyväskylä International Master Program: “Mobile Technologies and Business”
Industrial Ontologies Group Oleksiy Khriyenko, Vagan Terziyan INDIN´04: 24th – 26th June, 2004, Berlin, Germany OntoSmartResource: An Industrial Resource.
Industrial Ontologies Group: our history and team Vagan Terziyan, Group Leader Industrial Ontologies Group Agora Center, University of Jyväskylä.
Industrial Ontologies Group University of Jyväskylä Future of the Web: Vagan Terziyan University of Jyväskylä, 20 May, 2009 Towards Global Understanding.
P2P as a Discovery Instrument for Multi-Agent Ubiquitous Middleware P2P as a Discovery Instrument for Multi-Agent Ubiquitous Middleware A work-package.
SmartResource: Proactive Self-Maintained Resources in Semantic Web TEKES Project proposal Vagan Terziyan, Project Leader Industrial Ontologies Group Agora.
AceMedia Personal content management in a mobile environment Jonathan Teh Motorola Labs.
AGENT-BASED APPROACH FOR ELECTRICITY DISTRIBUTION SYSTEMS University of Jyväskylä University of Vaasa Acknowledgements: Industrial Ontologies Group.
Industrial Ontologies Group Sergiy Nikitin Dynamic Aspects of Industrial Middleware Applications Public examination of the dissertation.
Industrial Ontologies Group University of Jyväskylä CONTEXT-POLICY-CONFIGURATION: Paradigm of Intelligent Autonomous System Creation Oleksiy Khriyenko.
Bridging Webs for Future Business: "Everything-as-a-User" Vagan Terziyan OPEN DISCUSSION: “Business through Technologies or Technologies through Business”
Industrial Ontologies Group University of Jyväskylä SmartResource Project: (industrial case for Semantic Web and Agent Technologies) “Device”“Expert”“Service”
Introduction to Agent Technology in Mobile Environment Course Introduction Vagan Terziyan Department of Mathematical Information Technology University.
23/03/2007 mail-to: site: A Security Framework for Smart Ubiquitous.
UbiRoad: “Semantic Middleware for Smart Traffic Management”
Industrial Ontologies Group University of Jyväskylä UbiRoad: “Semantic Middleware for Context- Aware Smart Road Environments” “Driver” “Road” “Car” Resource.
Industrial Ontologies Group Semantic and Agent Technologies in Developing Distributed Applications “Device” “Expert” “Service” Resource Agent Vagan Terziyan.
1 FM Overview of Adaptation. 2 FM RAPIDware: Component-Based Design of Adaptive and Dependable Middleware Project Investigators: Philip McKinley, Kurt.
ONTOLOGY-BASED INTERNATIONAL DEGREE RECOGNITION Vagan Terziyan, Olena Kaykova University of Jyväskylä, Finland Oleksandra Vitko, Lyudmila Titova (speaker)
Industrial Ontologies Group University of Jyväskylä Proactive Future Internet “Smart Semantic Middleware for Overlay Architecture” “Device” “Expert” “Service”
WISE: Web Intelligence and Service Engineering International Master Program Department of Mathematical Information Technology University of Jyväskylä (Finland)
Software engineering on semantic web and cloud computing platform Xiaolong Cui Computer Science.
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 18 Slide 1 Software Reuse 2.
©Ian Sommerville 2006Software Engineering, 8th edition. Chapter 18 Slide 1 Software Reuse.
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 18 Slide 1 Software Reuse.
A Research Agenda for Accelerating Adoption of Emerging Technologies in Complex Edge-to-Enterprise Systems Jay Ramanathan Rajiv Ramnath Co-Directors,
Ontology-derived Activity Components for Composing Travel Web Services Matthias Flügge Diana Tourtchaninova
Katanosh Morovat.   This concept is a formal approach for identifying the rules that encapsulate the structure, constraint, and control of the operation.
Industrial Ontologies Group ( ) (Fast Introduction) Industrial Ontologies Group.
Industrial Ontologies Group Industrial Ontologies Group brief introduction Vagan Terziyan “Device”
Agent-Driven Self-Management “Device” “Expert” “Service” Resource Agent.
Agent Model for Interaction with Semantic Web Services Ivo Mihailovic.
Margherita Forcolin (Insiel S.p.A.) Thessaloniki, 13 October 2011.
Linked-data and the Internet of Things Payam Barnaghi Centre for Communication Systems Research University of Surrey March 2012.
Digital Earth Communities GEOSS Interoperability for Weather Ocean and Water GEOSS Common Infrastructure Evolution Roberto Cossu ESA
The roots of innovation Future and Emerging Technologies (FET) Future and Emerging Technologies (FET) The roots of innovation Proactive initiative on:
Issues in (Financial) High Performance Computing John Darlington Director Imperial College Internet Centre Fast Financial Algorithms and Computing 4th.
© 2012 xtUML.org Bill Chown – Mentor Graphics Model Driven Engineering.
NA-MIC National Alliance for Medical Image Computing UCSD: Engineering Core 2 Portal and Grid Infrastructure.
ICCS WSES BOF Discussion. Possible Topics Scientific workflows and Grid infrastructure Utilization of computing resources in scientific workflows; Virtual.
Semantic Web: The Future Starts Today “Industrial Ontologies” Group InBCT Project, Agora Center, University of Jyväskylä, 29 April 2003.
NGCWE Expert Group EU-ESA Experts Group's vision Prof. Juan Quemada NGCWE Expert Group IST Call 5 Preparatory Workshop on CWEs 13th.
Riga Technical University Department of System Theory and Design Usage of Multi-Agent Paradigm in Multi-Robot Systems Integration Assistant professor Egons.
6. Protocol Standardization for IoT 1.  TCP/IP  HTML and HTTP  The difference between the Internet and the World Wide Web The Internet is the term.
16/11/ Semantic Web Services Language Requirements Presenter: Emilia Cimpian
Internet of Things (Ref: Slideshare)
Internet of Things. IoT Novel paradigm – Rapidly gaining ground in the wireless scenario Basic idea – Pervasive presence around us a variety of things.
Chapter 1: Computing with Services Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005.
Providing web services to mobile users: The architecture design of an m-service portal Minder Chen - Dongsong Zhang - Lina Zhou Presented by: Juan M. Cubillos.
NCP Info DAY, Brussels, 23 June 2010 NCP Information Day: ICT WP Call 7 - Objective 1.3 Internet-connected Objects Alain Jaume, Deputy Head of Unit.
Semantic Web in Context Broker Architecture Presented by Harry Chen, Tim Finin, Anupan Joshi At PerCom ‘04 Summarized by Sungchan Park
CIMA and Semantic Interoperability for Networked Instruments and Sensors Donald F. (Rick) McMullen Pervasive Technology Labs at Indiana University
IoT R&I on IoT integration and platforms INTERNET OF THINGS
Context-Aware Middleware for Resource Management in the Wireless Internet US Lab 신현정.
Industrial Ontologies Group: 10th Anniversary
Model-Driven Engineering for Mission-Critical IoT Systems
Collaborative Open Market to Place Objects at your Service
UPTIME & SEMANTIC WEB STANDARDS
Presentation transcript:

Industrial Ontologies Group University of Jyväskylä PRIME Project Idea “Proactive Inter-Middleware for Self- Configurable Heterogeneous Cloud Ecosystems” “Device” “Expert” “Service” Resource Agent

Inter-middleware concept Most of the resources are connected to some existing middleware. Most of the resources are connected to some existing middleware. We do not abandon those. Rather, we connect to the resources through their respective middleware. We do not abandon those. Rather, we connect to the resources through their respective middleware. In this sense, the PRIME platform is a inter-middleware. In this sense, the PRIME platform is a inter-middleware.

M3 M5 M1 M2 M6 M4 M7 M3 M5 M1 M2 M6 M4 M7 PRIME Inter-Middleware PRIME: Inter-Middleware concept

Challenges and Solutions Clouds are supposing to have very heterogeneous components Clouds are supposing to have very heterogeneous components Different nature (devices, Web services, humans). Different nature (devices, Web services, humans). Not always the exact same domain (e.g. more general Web services can be applicable to several industries). Not always the exact same domain (e.g. more general Web services can be applicable to several industries). Data-level heterogeneity Data-level heterogeneity Calls for the Semantic technology. Calls for the Semantic technology. Protocol-level heterogeneity Protocol-level heterogeneity PRIME approaches through the Agent technology. PRIME approaches through the Agent technology. Each resource has a representative – software agent (not necessarily intelligent or even fully autonomous, but at least able to act as a programmable proxy). Each resource has a representative – software agent (not necessarily intelligent or even fully autonomous, but at least able to act as a programmable proxy). Interactions among resources go through their agents. Interactions among resources go through their agents.

Challenges and Solutions (2) Coordination Coordination When considering physical devices, in contrast to purely digital world of Web services, coordination is critical. When considering physical devices, in contrast to purely digital world of Web services, coordination is critical. Coordination is about resources planning their activities while attempting to avoid negative interactions (e.g. collision over a non-shareable resource) as well as exploit positive interactions (re-using each other results). Coordination is about resources planning their activities while attempting to avoid negative interactions (e.g. collision over a non-shareable resource) as well as exploit positive interactions (re-using each other results). Enabling coordination among heterogeneous resources is even harder problem than data-level or protocol-level heterogeneity – communication about actions. Enabling coordination among heterogeneous resources is even harder problem than data-level or protocol-level heterogeneity – communication about actions. PRIME approaches through semantic programming PRIME approaches through semantic programming Agents are programmed in RDF-based Semantic Agent Programming Language (S-APL). Agents are programmed in RDF-based Semantic Agent Programming Language (S-APL). Agents communicate their action plans in S-APL as well. Agents communicate their action plans in S-APL as well.

PRIME for FP7: Preliminary glance Coordinator: Prof. Vagan Terziyan (University of Jyväskylä) Partners (6-8):  Academic (4) University of Jyväskylä, Finland – Architecture, SOA, Self- Management VTT (Technical Research Center), Finland – Agents, MAS, SE University of Coimbra, Portugal – Semantics, Business, Web 2.0 Kharkov National University of Radioelectronics, Ukraine – IoT, SE  Industrial (2-4 - open) End-User, Case provider Technology provider (SAP ?)

Related Work by Industrial Ontologies Group (University of Jyväskylä, Finland) just finished UBIWARE Project

Industrial Ontologies Group Activities of Industrial Ontologies Group towards Global Understanding Environment “Device” “Expert” “Service” Resource Agent PI GB SC Vagan Terziyan

GUN Concept (Industrial Ontologies Group) GUN – Global Understanding eNvironment GUN = Global Environment + Global Understanding = Proactive Self-Managed Semantic Web of Everything

Current UBIWARE Agent Architecture S-APL S-APL – Semantic Agent Programming Language (RDF-based) S-APL S-APL – is a hybrid of semantics (metadata / ontologies/ rules) specification languages, semantic reasoners, and agent programming languages. It integrates the semantic description of domain resources with the semantic prescription of the agents' behaviors S-APL

Latest Innovations Invented by Industrial Ontologies Group in UBIWARE OntoNuts 4i (“for eye”) technology Smart Comments OntoNuts – is the ontology-based instrument to reconfigure and enhance complex distributed systems by automated discovery and linking external sources of heterogeneous and dynamic data and capabilities during system runtime 4i – is smart ontology-based visualization technology able to automatically discover and utilize external visualization service providers and dynamically create and visualize mashups from external data sources in a context-driven way Smart Comments – is smart ontology-based technology for end-user-driven control and configuration management of the application in runtime based on smart mapping of appropriate tags from natural language comments provided by a SW engineer and the source code.

Key Components of UBIWARE Scientific Impact 3. Language 1. UBIWARE: Approach and Architecture 2. Engine 4. Ontonuts

Environment HardBody SoftBody SoftMind HardMind HardSoul SoftSoul UBIWARE Agent: Possible Future Architecture RAB RAB – Reusable Atomic Behavior RBE RBE – Reusable Behavior Engine RAB RABRABRAB RBE RBERBERBE Beliefs (facts, rules, policies, plans) Shared Beliefs Shared RABs Shared RBEs Shared Meta-Beliefs Meta-Beliefs (preferences) “Life” Behavior Configuration (GENOME) Shared Hardware “Visible” to other agents through observation Ontobility Ontobility is self- contained, self-described, semantically marked-up proactive agent capability (agent-driven ontonut), which can be “seen”, discovered, exchanged, composed and “executed” (internally or remotely) across the agent platform in a task-driven way and which can perform social utility-based behavior Genome Genome is part of semantically marked-up agent configuration settings, which can serve as a tool for agent evolution: inheritance crossover and mutation May be an agent

UBIWARE present status The UBIWARE project is a major step in a longer path that aims to build the so called global understanding environment. That is, a platform or middleware that supports flexible integration of all kinds of resources that have not been a priori designed to be interoperable into new processes that have not been specified when designing the platform. The basic approach in development has been that of agile development – creation of a succession of prototypes with improving functionalities on every release combined with concrete use cases with companies.

PRIME in the context of UBIWARE

PRIME Objectives Development of the generic inter-middleware architecture to enable interoperability and integration of heterogeneous cloud resources and components through orchestrating available middleware platforms as services (MaaS). Development of an ontological model for interoperability, covering real-world entities, software systems, and humans along with their user interfaces, from both the technical and the business perspectives. Development of a multi-agent architecture, in which the interaction scenarios of heterogeneous resources involved in end-user applications are defined and configured declaratively (semantically) rather than programmatically. Adoption and further elaboration and extension of the Semantic Agent Programming Language (S-APL) for representation of agent’s role behaviour models (behavioural semantics) and the integration scenarios. Enabling flexible yet predictable operation through incorporating commitments imposed by the organizational roles and policies. Design of the core semantic mechanisms for inter-agent coordination. Development of a set of solutions enabling homogeneous interfacing with resources of different nature. Linking to Real-world Entities (physical objects with embedded electronics or RFID). Linking to the Web of Services. Linking to Human Resources.

PRIME as 2-nd order middleware (UBIWARE-based)

Enhancement of Industrial Systems and Private Clouds with Public/Social Context and Services

Innovative concepts of PRIME Vision The “Inter-middleware" approach opens a new challenging concept of MaaS (Middleware-as-a-Service) in addition to SaaS (Software-as-a-Service) and DaaS (Device-as-a-Service). Through MaaS every resource will be able to automatically get service available in certain ecosystem and even integrate heterogeneous services from different ecosystems. Also a human is considered in various possible roles including HaaS (Human-as-a- Service). The Knowledge-as-a-service (KaaS) driven by proactive ontologies is also a new concept. Finally we invented IaaS (Intelligence-as-a-Service), meaning data- mining/knowledge discovery/OLAP/ algorithms (which produce new knowledge to the system), as services of the system. Summarising, the “inter-middleware” vision allows innovative self-managed cloud architecture that enhances traditional cloud architectures with the Internet of Things capabilities and also with the capabilities provided by the Web of Services, Web of Humans (Web.2.0), Web of Knowledge (Web 3.0) and Web of Intelligence (Web 4.0).

Some of PRIME research challenges Ontology of: Middleware; Software Platforms, OS, Environments, Ecosystems etc.; Semantic annotation of remote environments and automated access via smart semantic adapters (“ontonuts”); Cloud architecture of PRIME with SOA principles towards remote services; PRIME as a “meta-cloud” (InterCloudWare); User application as complex, autonomous, proactive agent- driven entity; End-users interfaces for systems’ design, (re)configuration and use; Devices and software applications as PRIME users (EaaU: “Everything-as-a-User”); Semantic blogging, PRIME knowledge creation and management; Assuring interoperability among applications designed with PRIME; “Linked Capabilities” vs. Linked Data