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

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Presentation on theme: "Industrial Ontologies Group University of Jyväskylä PRIME Project Idea “Proactive Inter-Middleware for Self- Configurable Heterogeneous Cloud Ecosystems”"— Presentation transcript:

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

2 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.

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

4 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.

5 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.

6 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 ?)

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

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

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

10 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

11 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.

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

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14 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

15 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.

16 PRIME in the context of UBIWARE

17 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.

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

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

20 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).

21 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


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