Digital Enterprise Architecture - Transformation for the Internet of Things Alfred Zimmermann1, Rainer Schmidt2, Kurt Sandkuhl3, Matthias Wißotzki3, Dierk Jugel1,3, Michael Möhring4 1

Reutlingen University Reutlingen, Germany

2

Munich University Munich, Germany

[email protected]

rainer.schmidt @hm.edu

Abstract—Excellence in IT is both a driver and a key enabler of the digital transformation. The digital transformation changes the way we live, work, learn, communicate, and collaborate. The Internet of Things (IoT) fundamentally influences today’s digital strategies with disruptive business operating models and fast changing markets. New business information systems are integrating emerging Internet of Things infrastructures and components. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous Enterprise Architecture efforts to enable business value by integrating Internet of Things architectures. Both architecture engineering and management of current information systems and business models are complex and currently integrating beside the Internet of Things synergistic subjects, like Enterprise Architecture in context with services & cloud computing, semantic-based decision support through ontologies and knowledge-based systems, big data management, as well as mobility and collaboration networks. To provide adequate decision support for complex business/IT environments, we have to make transparent the impact of business and IT changes over the integral landscape of affected architectural capabilities, like directly and transitively impacted IoT-objects, business categories, processes, applications, services, platforms and infrastructures. The paper describes a new metamodel-based approach for integrating Internet of Things architectural objects, which are semi-automatically federated into a holistic Digital Enterprise Architecture environment. Keywords—Digital Transformation, Internet of Things, Digital Enterprise Architecture, Reference Architecture, Architecture Model Integration

I.

INTRODUCTION

Information, data and knowledge are fundamental concepts of our everyday activities. Social networks, smart portable devices, and intelligent cars, represent only a few instances of a pervasive, information-driven vision [1] for the next wave of the digital economy and well-aligned information systems. Enterprise Architecture Management has established as a governance instrument [2] to consistently align both business and IT with strategy and goals, and to ensure adaptability, consistency, compliance, and efficiency. Service-oriented enterprise architecture and engineering [3] applies engineering principles to the design of enterprise architectures. We are introducing the term Digital Enterprise Architecture to extend the subject of Enterprise Architecture Management for current

3

University of Rostock Rostock, Germany [email protected]

4

Aalen University Aalen, Germany

[email protected]

digital transformation efforts. One of the most challenging subjects for the current discussion about the digital transformation of our society is the Internet of Things (IoT) [4] and [5]. The Internet of Things enables a large number of physical devices to connect each other to perform wireless data communication and interaction using the Internet as a global communication environment. Information and data are central components of our everyday activities. Social networks, smart portable devices, and intelligent cars, represent a few instances of a pervasive, information-driven vision of current enterprise systems with IoT and service-oriented enterprise architectures. Social graph analysis and management, big data, and cloud data management, ontological modeling, smart devices, personal information systems, hard non-functional requirements, such as location-independent response times and privacy, are challenging aspects of the above software architecture [6]. Service-oriented systems close the business - IT gap by delivering appropriate business functionality efficiently and integrating new service types coming from the Internet of Things [7], [8] and from cloud services environments [9], [10], [11] and [12]. As the architecture of Internet of Things systems becomes more complex, and we are going rapidly into cloud computing settings, we need a new and improved set of methodological well-supported instruments of Enterprise Architecture Management, which are associated with tools for managing, decision support, diagnostics and for optimization of impacted business models and information systems. The current state of art research for the Internet of Things architecture [5] lacks an integral understanding of Enterprise Architecture and Management [13], [14], [15] and [16] and shows an abundant set of physical-related standards, methods and tools, and a fast growing magnitude of heterogeneous IoTdevices. The aim of our research is to close this gap and enhance analytical instruments for cyclic evaluations of business and system architectures of integrated Internet of Things environments. In this paper we introduce our extended service-oriented enterprise architecture reference model in the context of our new architecture metamodel integration approach and ontology for an integral Enterprise Architecture of the Internet of Things. We are revisiting and extending our first version of ESARC – the Enterprise Services Architecture Reference Cube [17], [18] to support digital transformations of

Enterprise Architecture Management

ESARC©

- Enterprise Software Architecture Reference Cube

Hochschule Reutlingen Reutlingen University

Monitoring,business and Optimization software-intensive products and services and to cover theArchitecture ESARCCapability abstractsDiagnostics, from a concrete scenario or !  ESARC defines an original holistic classification scheme forfor cyclic diagnostics andarchitectural optimization of eight architectural transformation for the Internet of Things. technologies, but is applicable concrete types (viewpoints) of service-oriented enterprise software architectures !  ESARC substantiates the TOGAF standard with other models to provide a useful mapping foundation of a instantiations. Our research aims to investigate a metamodel-based model reference architecture, defining main architecture artifacts and their relationships extraction and integration approach for enterprise architecture viewpoints, models, standards, frameworks and tools for the high fragmented Internet of Things. The integration of many dynamically growing distributed Internet of Things objects into an effective and consistent Enterprise Architecture Management is challenging. Currently we are working on the idea of integrating small EA descriptions for each relevant IoT object. These EA-IoT-Mini-Descriptions consists of partial EA-IoT data together with partial EA-IoT models and metamodels. Our goal is to be able to support an integral architecture development, assessments, architecture © Prof. Dr. Alfred Zimmermann diagnostics, monitoring with decision support, and25 Fig. 1. Enterprise Services Architecture Reference Cube optimization of the business, information systems, and Metamodels and their architectural data are the core part of technologies. We report about our work in progress research to the Enterprise Architecture. Enterprise architecture metamodels provide a unified ontology-based methodology for adaptable [16], [26] should support decision support [27] and the digital enterprise architecture models from relevant information strategic [28] and IT/Business [20] alignment. Three quality resources, especially for the Internet of Things. perspectives are important for an adequate IT/Business The main contribution of our current research paper alignment and are differentiated as: (i) IT system qualities: consists of a novel and high scalable approach for Digital performance, interoperability, availability, usability, accuracy, Enterprise Architecture composed of microarchitectures of maintainability, and suitability; (ii) business qualities: distributed devices and services, which are not covered yet by flexibility, efficiency, effectiveness, integration and classical enterprise architectures. The novelty of our approach coordination, decision support, control and follow up, and lies in the connection between IoT and other distributed organizational culture; and finally (iii) governance qualities: services and traditional most central EA approaches. plan and organize, acquire and implement deliver and support, monitor and evaluate. The following Section 2 presents our research platform with fundamental concepts for an evolving Digital Enterprise Architecture Governance, as in [29] sets the governance Architecture. In Section 3 we introduce the Internet of Things frame for well aligned management practices within the architecture. Section 4 covers our architectural integration enterprise by specifying management activities: plan, define, method to map the Internet of Thing architecture into the larger enable, measure, and control. The second aim of governance is context of Digital Enterprise Architecture. Finally Section 5 to set rules for architectural compliance respecting internal and concludes our main results and provides an outlook for our external standards. Architecture Governance has to set rules for current and next research. the empowerment of people, defining the structures and procedures of an Architecture Governance Board, and setting II. DIGITAL ENTERPRISE ARCHITECTURE rules for communication. Our principal new idea is an extended approach about the The Business and Information Reference Architecture systematic composition and integration of architectural BIRA provides, a single source and comprehensive repository metamodels, ontologies, views and viewpoints within of knowledge from which concrete corporate initiatives will adaptable service-oriented enterprise architecture frameworks evolve and link. The BIRA confers the basis for business-IT for services and cloud computing architectures, by means of alignment and therefore models the business and information different integrated service types and architecture capabilities. strategy, the organization, and main business demands as well ESARC - Enterprise Services Architecture Reference Cube in as requirements for information systems, such as key business Fig. 1 comprises an integral service-oriented enterprise processes, business rules, business products, services, and architecture categorization framework, which sets a related business control information. classification scheme for main enterprise architecture models, as a guiding instrument for decisions in architectural The Business & Information Reference Architecture of engineering viewpoints. We are currently integrating ESARC defines the link between the enterprise business metamodels for EAM and the Internet of Things. strategy and the results of supporting strategic initiatives through information systems. The Business & Information The ESARC – Enterprise Services Architecture Reference Reference Architecture provides a single source and Cube [17] and [18] complements existing architectural models, comprehensive repository of knowledge from which concrete standards and frameworks for EAM – Enterprise Architecture corporate initiatives will evolve and link. This knowledge is Management [15], [19] and [20], [16] and extends these model based and defines an integrated enterprise model of the architecture standards for services [21], [22] and [23] and cloud business, which includes organization and business processes computing [24], [25] in a holistic way. ESARC is an original models. architecture reference model, which provides a holistic classification model with eight integral architectural domains. © Alfred

Zimmermann and SOA Innovation Lab 2011

The Business & Information Reference Architecture opens a connection to IT infrastructures, IT systems, and software as well as security architectures. It provides integration capabilities for IT management, software engineering, service & operations management, and process improvement initiatives. The Business & Information Reference Architecture confer the basis for business IT alignment and therefore models the business and information strategy, the organization, and main business requirements for information systems like key business processes, business rules, business products, services, and related business control information. The OASIS Reference Model for Service Oriented Architecture [30] is an abstract framework, which guides our ESARC reference architecture. ESARC provides on his part the abstract model for specific applications architectures and concrete implementations. The ESARC – Information Systems Reference Architecture in Fig. 2 details the Reference Architectures [31] and [32] and provides a blueprint for individual customizable service-oriented architectures for application systems. The ESARC – Information Systems Reference Architecture contains the main application specific service types and defines their relationship by a layer model of building services. The core functionality of domain services is linked with application interaction capabilities and with the business processes of the customer’s organization.

state information directly, but work in cooperation with information services. The access to information services follows an acyclic graph according the common control of layer models - from top to down layers. Operations of task and entity services should not have any knowledge about their process context or interactive usage context. Task service operations should be independent from users and sessions and should only implement business functionality. Authorization checks should be done outside of the business operations. Task and information services should use a transactional context, but their operations shouldn’t implement by their own local transactions. Task service operations should be usable both in batch and in online system transactions. Task services are used in process services as multiple composites of services and should therefore be centrally managed high reusable assets. Rule services provide declarative capabilities for adaptable business product and business service structures. Rules provide additional flexible control elements for agile business processes. Process services are long running services, which compose task services and information services into workflows to implement the procedural logic of business processes. Process services can activate rule services to swap out a part of the potentially unstable gateway-related causal decision logic. Process services are frontend by interaction services or by specific diagnostic service and process monitoring services. Often process services manage distributed data and application state indirectly, by activating task and information services. Process services participate in atomic transactions only when they are activated from batch services. When processes services participate in human interaction workflows they have to support long-running transactions where compensation of possible errors or exceptions happens in the business logic. The ESARC – Technology Reference Architecture in and Fig. 3 describes the logical software and hardware capabilities that are required to support the deployment of business, data, and application services.

Fig. 2. ESARC - Information Systems Reference Architecture

We have differentiated a whole sequence of layered service types in [17], [18] ESARC – Information Systems Reference Architecture. The information services for enterprise data can be thought of as data centric components providing access to the persistent entities of the business process. The capabilities of information services combine both elementary access to CRUD (create, read, update, delete) operations and complex functionality for finding/searching of data or complex data like data composites or other complex-typed information. Close to the access of enterprise data are context management capabilities provided by the technology architecture: error compensation or exception handling, seeking for alternative information, transaction processing of both atomic and long running and prevalent distributed transactions. Information services and their related data architecture are core company assets and should be close and centrally managed for reuse. Task services implement business capabilities related to specific actions of the business process. Task services could be own or third party services. Usually task services don’t manage

Fig. 3. ESARC - Technology Reference Architecture

This includes IT infrastructure, middleware, networks, communications, processing, and standards. The layers of the ESARC – Technology Reference Architecture and the layers of the ESARC – Information Systems Reference Architecture correspond to each other.

The database system is the vendor supported database management system for handling enterprise data. Close associated with the database system we have included in our architecture stack the TP-monitor system and optionally a reference model of a messaging system. The application server is the container environment architecture for objects and enterprise components. The enterprise service bus uses a flexible and standard-based messaging mechanism to interconnect services on a process and service execution platform.

directly modern business architectures by BPaaS – Business Process as a Service and giving a direct link to Service-oriented Enterprise Architectures. The IBM Cloud Computing Reference Architecture provides in [10] additionally to the standardization of NIST best-of-industry knowledge and cloud product specifications by integrating the NIST standard with own technology stacks, middleware, as well as service-oriented programming and runtime platforms. The Service-Oriented Cloud Computing (SOCCI) Framework [11] is an enabling framework for an integrated set of cloud infrastructure components. Basically it is the synergy of service-oriented and cloud architectures by means of a consistent As-a-Service-Mechanism for all types of cloud services.

On top of the service bus we have placed the rule server, which is able to represent business rule and operate rule processing by assembling dynamic inference chains. The process orchestration server [18] executes process services by calling suitable services of earlier mentioned types. For running interaction and collaboration services additional infrastructures are positioned in our stack of the technology reference architecture like: interaction frameworks, portal servers, workflow engines, and nowadays more often collaboration frameworks. Security services are part of an integral framework-based security system of standards and components and are impacted by the mentioned services and by distributed service technologies.

III. INTERNET OF THINGS ARCHITECTURE The Internet of Things (IoT) fundamentally revolutionizes today’s digital strategies with disruptive business operating models [2], and holistic governance models for business and IT [29], in context of current fast changing markets. With the huge diversity of Internet of Things technologies and products organizations have to leverage and extend previous enterprise architecture efforts to enable business value by integrating the Internet of Things into their classic business and computational environments. Reasons for strategic changes by the Internet of Things [37] are:

Cloud architectures are evolving fast, but have not reached their full potential in integrating Enterprise Architecture with Services [21], [22], and [23] and Cloud Computing [24] and [25]. Today’s development of cloud computing technologies and standards are growing very fast and provide a growing standardized base for cloud products and service offerings. Fig. 3 shows our integration scenario for an extended Cloud Computing architecture model from [9], [10], [11], and [12]. The Cloud Services Reference Architecture [17], [18] provides a reference-model-based synthesis of current standards and reference architectures from [9], [10], and [11]. Furthermore, Cloud Computing based architectures can enable Big Data analytics [33], [34], [35] for small and medium-sized enterprises and organizations [36].

• Information of everything – enables information about what customers really demand, • Shift from the thing to the composition – the power of the IoT results form the unique composition of things in an always-on, • Always-connected information-rich environments, • Convergence – integrates people, things, places, and information, • Next-level business – the Internet of Things is changing existing business capabilities by providing a deeper way to interact, measure, operate and analyze business and IT.

Metamodell-basierte Integration von Service-orientierten EA-Referenzarchitekturen

Fig. 4 shows our integration scenario for an extended Cloud Integrating Cloud Computing Reference Architectures with Computing Reference Architecture Model. (SOCCI) The NIST Cloud Computing Service-Oriented Cloud Computing Infrastructure 19

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Information Technology Laboratory Cloud Computing Program

Figure 3: SOCCI High-Level View

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SOCCI Architecture Building Blocks (ABBs) consist of the SOCCI and SOCCI NIST CC-RA, IBM CC-RA, CSA CC-RA, Open Group SOCCI Framework Alfredelements Zimmermann Management Building Blocks. The former leverages the latter to interface with the users. The

Fig. 4. Integrating Cloud Computing Architectures

SOCCI Management Building Blocks are categorized as operation-centric and business-centric. The division between the two is dependent on the type of service provided. The Business ABBs relate to supporting the business functions needed to be able to create, support, and consume an IaaS offering; e.g. metering, billing, and location management. The Operational ABBs relate to operational functions supporting/leveraging the SOCCI elements to provide the operational management services; e.g., virtualization and provisioning management.

The NIST Cloud Computing Reference Architecture [9] defines the Conceptual Reference Model for Cloud Computing. Some standard extensions for Cloud Reference Architectures, like [10], [11] provide practical additions for supporting more SOCCI Management Building Blocks that enable SOCCI are described below. Business ABBs:

Metering Manager (measured service enabler) tracks consumer usage statistics for the usage of virtual networks and resources from aggregated data including usage statistics

Service-Oriented Cloud Computing Infrastructure (SOCCI) Framework

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The Internet of Things is the result of a convergence of visions [38]: Things-oriented vision, an Internet-oriented vision, and a Semantic-oriented vision. The Internet of Things enables a large number of physical devices to connect each other to perform wireless data communication and interaction, by using the Internet as a global communication environment. A cloud centric vision for architectural thinking of a ubiquitous sensing environment is provided by [7]. The typical configuration of the Internet of Things includes besides many communicating devices a cloud-based server architecture, which is required to interact and perform remote data management and calculations. Sensors, actuators, devices as well as humans and software agents interact and communicate data to implement specific tasks or more sophisticated business or technical processes. The Internet of Things maps and integrates real world objects into the virtual world, and extends the interaction with mobility systems, collaboration support systems, and systems and services for big data and cloud environments. Furthermore, the

Today, the Internet of Things includes a multitude of technologies and specific application scenarios of ubiquitous computing [38], [41] like wireless and Bluetooth sensors, Internet-connected wearable systems, low power embedded systems, RFID tracking, smartphones, which are connected with real world interaction devices, smart homes and cars, and other SmartLife scenarios. To integrate all aspects and requirements of the Internet of Things is difficult, because no single architecture can support today the dynamics of adding and extracting these capabilities. A first Reference Architecture (RA) for the Internet of Things is proposed by [41] and can be mapped to a set of open source products. This Reference Architecture covers aspects like: cloud server-side architecture, monitoring and management of Internet of Things devices and services, a specific lightweight RESTful communication system, and agent and code on often-small low power devices, having probably only intermittent connections. The Internet of Thing architecture has to support a set of generic as well as some specific requirements [41], and [5]. Generic requirements result from the inherent connection of a magnitude of devices via the Internet, often having to cross firewalls and other obstacles. Having to consider so many and a dynamic growing number of devices we need an architecture for scalability. Because these devices should be active in a 24x7 timeframe we need a high-availability approach [39], with deployment and auto-switching across cooperating datacenters in case of disasters and high scalable processing demands. Additionally an Internet of Thing architecture has to support automatic managed updates and remotely managed devices. Often connected devices collect and analyze personal or security relevant data. Therefore it is mandatory to support identity management, access control and security management on different levels: from the connected devices through the holistic controlled environment.

Desirable requirements of device management [41] include the ability to locate or disconnect a stolen device, update the software on a device, update security credentials or wiping security data from a stolen device. Internet of Things systems can collect data streams from many devices, store data, analyze data, and act. These actions may happen in near real time, which leads to real-time data analytics approaches. Server ! infrastructures and platforms should be high scalable to support elastic scaling up to millions of connected devices, supporting The!Architecture! alternatively as well smaller deployments. Security is a The!RA!consists!of!a!set!of!layers.!Each!layer!performs!a!clear!function.!Layers!can!be! challenging aspect of this high-distributed typical small instantiated!by!specific!technologies,!and!we!will!discuss!options!for!implementing!each!layer.! There!are!also!some!cross:cutting/vertical!layers!such!as!security/identity!management.! environment of Internet of Things. Sensors are able to collect ! personalized data and can bring these data to the Internet.

Internet of Things

Reference Architecture A layered Reference Architecture for the Internet of Things Internet of Things isReference proposedArchitecture in [41] and (Fig. 1). Layers can be instantiated by suitable technologies for the Internet of Things. Web / Portal

Dashboard

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A main question is, how the Internet of Things architecture fits in a context of a services-based enterprise-computing environment? A service-oriented integration approach for the Internet of Things was elaborated in [8]. The core idea for millions of cooperating devices is, how they can be flexibly connected to form useful advanced collaborations within the business processes of an enterprise. The research in [8] proposes the SOCRADES architecture for an effective integration of Internet of Things in enterprise services. The architecture from [8] abstracts the heterogeneity of embedded systems, their hardware devices, software, data formats and communication protocols. A layered architecture structures following bottom-up functionalities and prepares these layers for integration within an Internet of Things focused enterprise architecture: Devices Layer, Platform Abstraction Layer, Security Layer, Device Management Layer with Monitoring and Inventory Services, and Service Lifecycle Management, Service Management Layer, and the Application Interface Layer.

Specific architectural requirements [38] and [42] result from key categories, such as connectivity and communications, device management, data collection and analysis, computational scalability, and security. Connectivity and communications groups existing protocols like HTTP, which could be an issue on small devices, due to the limited memory sizes and because of power requirements. A simple, small and binary protocol can be combined with HTTP-APIs, and has the ability to cross firewalls. Typical devices of the Internet of Things are currently not or not well managed by device management functions of the current Enterprise Architecture Management.

Device Manager

Internet of Things fundamentally influences the Industry 4.0 [39] and adaptable digital enterprise architectures [40]. Therefore, smart products as well as their production is supported by the Internet of Things and can help enterprises to flexibly create customer-oriented products.

Fig. 5. A Internet of Things Reference Architecture [WS15] 14 WSO2: Reference Architecture for the Internet of Things. http://wso2.com 2014 13 WSO2: A Reference Architecture for the Internet of Things. http://wso2.com 2014 Figure!2!>!Reference!Architecture!for!IoT!

!

! The Devices layer is the bottom layer, on which all other layers are built on. Devices are of different types, like cell and The!layers!are:! • External!Communications!!:!Web/Portal,!Dashboard,!APIs! smart phones, cars, machines, house devices, and have to be • Event!Processing!and!Analytics!(including!data!storage)! connected directly or indirectly with the Internet. Each device • Aggregation!/!Bus!Layer!–!ESB!and!Message!Broker! need an ID, which may be an UUID – unique identifier • Device!Communications!! provided • Devices!by a device-chip, UUID provided by the radio The!cross:cutting!layers!are:! subsystem as a Bluetooth identifier or a Wi-Fi MAC address, • Device!Management! or an OAuth2 Token. • Identity!and!Access!Management!

! The Communications layer provides the devices’ ! connectivity [5], [41], having to support typically multiple protocols for communication, like HTTP/HTTPS also supporting REST architectural styles, and lightweight! ! protocols, such as MQTT [http://mqtt.org], a publish-subscribe messaging protocol based on a broker model, and the Constrained Application Protocol (CoAP). CoAP enables IP and HTTP-based communications in a constrained

9!

environment. Mobility requirements and solutions for servicecontinuity in the Internet of Things in a mobile IPv6 environment are elaborated in [38], [41]. MQTT enables lossy and intermittently connected networks on top of TCP. CoAP supports a RESTful application protocol over UDP with reduced footprint and is directly binary coded. In case of using the HTTP protocol for sending data to the device would cause an inefficient HTTP polling. A replacement with the WebSocket protocol upgrades the HTTP connection into a full two-way connection. Therefore MQTT combined with WebSocket results as the recommended efficient protocol for the Internet of Things. The Aggregation / Bus Layer aggregates and combines communications from different devices, and routes communications as a gateway to specific devices. Additionally the aggregation / bus layer is responsible for bridging and transformations between protocols, and supports a HTTP server and a MQTT broker. The Event Processing and Analytics Layer [41] are responsible for analyzing events, which are taken from the bus and stored with data into a database. There are different approaches to be used in the Event Processing and Analytics Layer: scalable column-based data storage, map-reduce for long-running batch-oriented data processing, complex event processing for fast in-memory processing, and traditional application server processing. The External Communication Layer [5], [41] enables communication outside of devices by supporting processing models like: Web-based frontends and portals, dashboards with analytics processing views, and system interaction outside the network via APIs. The Device Management Layer groups the Device Manager component and related device manager agents for different platform and device types. The device manager supports managing of the installed software, enabling and disabling features of devices, managing security controls and identifiers, monitoring the availability of devices, and locking the device remotely. A current holistic approach for the development for the Internet of Things environments is presented in [5]. This research has a close link to our work about leveraging the integration of the Internet of Things into a framework of digital enterprise architectures. The main contribution from [5] considers a role-specific development methodology, and a development framework for the Internet of Things. The development framework contains a set of modeling languages for a vocabulary language to describe domain-specific features of an IoT-application, an architecture language for describing application-specific functionality, and a deployment language for deployment features. Associated with this language set are suitable automation techniques for code generation, and linking to reduce the effort for developing and operating devicespecific code. The metamodel for Internet of Things applications from [5] defines elements of an Internet of Things architectural reference model like, IoT resources of type: sensor, actuator, storage, and user interface. Internet of Thing resources and their associated physical devices are differentiated in the context of locations and regions. A device provides the capability to interact with users or with other

devices. The base functionality of Internet of Things resources is provided by software components, which are handled in a service-oriented way by using computational services. IV. ARCHITECTURE INTEGRATION METHOD Current work revisits and extends our basic enterprise architecture reference model from ESARC (Section 3) and [43] and [44] by federating Internet of Things architectural models (Section 2) from related scientific work, as well as specifications from industrial partners. Our originally developed integration model ESAMI – Enterprise Services Architecture Metamodel Integration – [40] serves as a method for integrating base models from enterprise architecture standards, like [15], [16], architectural frameworks [45], [46], and [47] in the context of architectural viewpoint descriptions [48] and [49]. ESAMI is based on correlation analysis, having a systematic integration process. Typically this process of pair wise mappings is quadratic complex. We have linearized the complexity of these architectural mappings by introducing a neutral and dynamically extendable architectural reference model, which is supplied and dynamically extended from previous mapping iterations. The architectural model integration [43] and [44] works considering following steps: analyze concepts of each resource by using concept maps; extract viewpoints for each resource: Viewpoint, Model, Element, Example; initialize the architectural reference model from base viewpoints; analyze correlations between base viewpoints and architectural reference model; determine integration options for the resulting viewpoint integration model; develop the synthesis metamodel from base metamodels; consolidate the architectural reference model according the synthesis metamodel, and finally readjust correlations and integration options; develop the ontology of the architectural reference model; develop correspondence rules between model elements; and develop patterns for architecture diagnostics and optimization. First we have to analyze and transform given architecture resources with concept maps and extract their coarse-grained aspects in a standard way [43], [44] by delimiting architecture viewpoints, architecture models, their elements, and illustrating these models by a typical example. Architecture viewpoints are representing and grouping conceptual business and technology functions regardless of their implementation resources like people, processes, information, systems, or technologies. They extend these information by additional aspects like quality criteria, service levels, KPI, costs, risks, compliance criteria a. o. We are using modeling concepts from ISI/IEC 42010 [48], [49] like Architecture Description, Viewpoint, View, and Model. Architecture models are composed of their elements and relationships, and are represented using architectural diagrams. For each architecture resource we are extracting then a Base Viewpoint Model in a standardized way. Then we develop the model of the initial Architectural Reference Model from each Base Viewpoint Model. This first version of the Architectural Reference Model is the result of a simple union from Base Viewpoint Models and could enclose redundant model information. In the next step we extend the initial Architectural Reference Model by analyzing model

correlations as quantified mappings between analyzed architecture models and by deriving synthesis or integration options for an optimized Architectural Reference Model. A Synthesis Metamodel of the Base Metamodels following the specifications of the Integration Options supports this step. The Architecture Metamodel is the base for the synthesized Architectural Reference Model, which is based on consolidated correlation and synthesis indicators from (Fig. 6). Finally we Enterprise Architecture Management & Cloud Computing cluster the resulting Viewpoint Map as a base for the ESAMI – Enterprise Services Architecture Metamodel Integration Capability Map finalArchitecture: Models and Elements. Consolidated EAMwith Reference Analysis and Integration EAM Reference Model

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Fig. 6. Correlation Analysis and Model Integration Options© Prof. Dr. Alfred Zimmermann COMPUTATION 2013 Valencia, Informatik 2013 Koblenz 9 SERVICE

Ontologies, as in [50], [51], [52] and [53], provide both a fundamental base for a clear understanding of the integrated architectural concepts and for additional knowledge representation and inference mechanisms. We are currently researching about semantic-supported representations for service-oriented enterprise architectures to provide a base for easier navigation and simulation within the complex space of enterprise architectures. The semi-automated navigation between architectural concepts enables new functionalities for impact management as well as for cyclic architecture evaluations and for real-time architecture analytics, diagnostics and decision support. We have constructed architecture metamodels (Fig. 7) using [50], [54] to define elements and their relationships for the ESARC architectural ontology model [51]. We use Hochschule Reutlingen Enterprise Architecture Management University metamodels as an abstraction for architecturalReutlingen elements and ESAMI – Enterprise Services Architecture Metamodel Integration relate them to architecture ontologies. SOA Ontology Typed Metamodel of Business Reference Architecture Business Function (Element)

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Business Rule (Element) © Prof. Dr. Alfred Zimmermann

Architecture ontologies represent a common vocabulary for enterprise architects who need to share their information based on explicitly defined concepts. Ontologies include the ability to

automatically infer transitive knowledge. The Metamodel of the Business & Information Reference Architecture – BIRA consists of ESARC-specific concepts, which are derived as specializations from generic concepts such as Element and Composition from the Open Group’s SOA Ontology [50]. The technical standard of Service-oriented Architecture Ontology from [50] defines core concepts, terminology, and semantics of a service-oriented architecture in order to improve the alignment between the business and IT communities. In our understanding architecture ontologies represent a common vocabulary for enterprise architects who need to share their information based on explicitly defined concepts. Ontologies include the ability to infer automatically transitive knowledge. Our developed ontology for ESARC ([51] and Fig. 7) instantiates [50] has main practical characteristics: share the common understanding of the ESARC Architecture domains and their structures, reuse of the architectural knowledge, make architectural requirements, structures, building blocks explicit and promote reusability of architectural artifacts, separate the architectural knowledge according orthogonal architectural domains, classify, analyze, diagnose enterprise systems according to the service-oriented reference architecture od ESARC. The SOA ontology represents core concepts of a generic service-oriented architecture as classes and properties. The SOA ontology includes in addition natural language descriptions of main concepts and relationships UML diagrams, which show graphically the semantic concepts as classes and the properties as UML associations. The UML diagrams are intended for explanation only, but are helpful constructs for understanding the modeled domain of SOA architecture and more concise than the more spacious formal descriptions in OWL. The SOA ontology defines the relations between semantic concepts, without mentioning the exact usage of these architecture concepts. We have developed the ESARC Ontology, according [55], and [56], and defined ontology concepts for ESARC using the ontology editor Protégé [56]. We have merged our specialized ESARC Ontology with the generic SOA Ontology from [47]. The so-called Asserted View from Protégé shows the is-arelationship between specific concepts of the Business & Information Reference Architecture and the Open Group’s generic SOA Ontology Reference Architecture. The terminal concepts are specific concepts of ESARC. In Fig. 7 we point within parentheses to the linked generic concepts of the SOA Ontology. Additionally we have determined knowledge properties for the modeled ontology concepts of ESARC. Using the ESARC ontology we intend further to navigate easier within the complex space of enterprise architecture management structures and to enable semantic-supported decisions and more transparency for stakeholders. The integration of a huge amount of dynamically growing Internet of Things objects is a considerable challenge for the scalability, extension and dynamically evolution of EA models. Currently we are working on the idea of integrating small EA descriptions for each relevant IoT object. These EA-IoT-MiniDescriptions consists of partial EA-IoT-Data (Instances), partial EA-IoT-Models, and partial EA-IoT-Metamodels

associated with main IoT objects like IoT-Resource, IoTDevice, and IoT-Software-Component [Pa15], and [WS14]. Our research in progress main question asks, how we can dynamically federate these EA-IoT-Mini-Descriptions to a global high scalable EA model and information base by promoting a mixed automatic and collaborative decision process [57], [58], and [59]. For the automatic part we currently extend model federation and transformation approaches from [60], [61], and [62] by introducing sematicsupported architectural representations, e.g. by using partial and federated ontologies and ontology-supported model transformations [63] as well as associated mapping rules - as universal enterprise architectural knowledge representation, which are combined with special inference mechanisms. V. CONCLUSION AND OUTLOOK We have developed a metamodel-based model extraction and integration approach for enterprise architecture viewpoints, models, standards, frameworks and tools for EAM towards integrated Internet of Things. Our goal is to support a holistic Enterprise Architecture Management with architecture development, assessments, architecture diagnostics, monitoring with decision support, and optimization of the business, information systems, and technologies. We intend to provide a unified and consistent ontology-based EAM-methodology for the architecture management models of relevant Internet of Things resources, especially integrating service-oriented and cloud computing systems for digital transforming enterprises as well.

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By considering the context of service-oriented enterprise architecture, we have set the foundation for integrating metamodels and related ontologies for orthogonal architecture domains of our integrated Enterprise Architecture Management approach for the Internet of Things. Architectural decisions for Internet of Things objects, like IoT Resource, Device, and Software Component are closely linked with the code implementation. Therefore, researchers can use our approach for integrating and evaluating Internet of Things in the field of enterprise architecture management. Our results can help practical users to understand the integration of EAM with the Internet of Things and to support architectural decisions. Limitations can be found e.g. in the field of practical multilevel evaluation of our approach as well as domain-specific adoptions.

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Future work will include conceptual work to federate EAIoT-Mini-Descriptions to a global EA model and enterprise architecture repository by promoting a semi-automatic and collaborative decision process. We are currently extending our architectural model federation and transformation approaches with basic research for ontology-based model transformations and elements from related work. We are researching about semantic-supported architectural representations, as universal enterprise architectural knowledge representations, which are combined with special inference mechanisms. Additional improvement opportunities will focus on methods for visualization of architecture artifacts and control information to be operable in an architecture management cockpit.

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