ServiceTechMag.com > Issue LXXI, March/April 2013

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Industrial SOA

Jürgen Kress, Berthold Maier, Hajo Normann, Danilo Schmiedel, Guido Schmutz, Bernd Trops, Clemens Utschig-Utschig, Torsten Winterberg

Jürgen Kress Berthold Maier Hajo Normann
Danilo Schmiedel Guido Schmutz Bernd Trops Clemens Utschig-Utschig Torsten Winterberg

SOA and service-orientation have laid the foundation for a variety of emergent service technology innovations, while the original building blocks of SOA and service-orientation continue to evolve by embracing fundamental service technologies, concepts and practices. These new technology innovations do not replace service-orientation; they use it as their basis. Service-orientation continues to evolve towards a factory approach, towards industrializing integrated platforms, such as BI, master data management (MDM), mobile front-ends, BPM, adaptive processes, Big Data and Cloud Computing - all of which add architectural layers upon SOA-based infrastructure. All of these technologies can interface via standardized data and functions, published as service contracts, in order to avoid redundancy - that's service-orientation. Let's take a closer look. The amount of data, which companies produce and store tends to grow on an on-going basis. This includes structured data (for example, from ERP systems or data warehouses), as well as unstructured data (for example, from e-mails). With the rise of social media services like twitter, Facebook, Pinterest and the emphasis on Customer Experience Management, the amount of data and data sources has increased dramatically. To integrate all of these data sources through an SOA-approach is essential. The models, principles and patterns behind SOA and service-orientation can be applied to formalize interoperability between...


SOA Blueprint: A Toolbox for Architects

Jürgen Kress, Berthold Maier, Hajo Normann, Danilo Schmiedel, Guido Schmutz, Bernd Trops, Clemens Utschig-Utschig, Torsten Winterberg

Jürgen Kress Berthold Maier Hajo Normann
Danilo Schmiedel Guido Schmutz Bernd Trops Clemens Utschig-Utschig Torsten Winterberg

This article introduces the foundations that need to be established in order to implement functional SOA processes. Rather than presenting specific tools, we will define a broadly applicable SOA blueprint whose individual modules can be topped up with commercial products or increasingly available open source offerings. Upon examination of Figure 1, the vision of adaptive enterprise computing is illustrated as a meta-blueprint for the overall company with three differentiated levels: Infrastructure Level - This level is formed by databases, storage systems, application servers, and all other IT resources that are required to run IT systems. Application System Level - This level houses entire applications, both individual applications and standard software, as well as services relating to SOA, workflow and BPM systems. Process Management Level - Functional requirements are manifested in the process design and then implemented at the lower levels. An advanced service-oriented architecture is the most effective option for implementing the functional requirements at the application-system level. The more superior the mapping of existing business services to the functional steps in process models is, the more the business-IT gap shrinks. Various back-coupling loops represent the actual added value of this meta-blueprint, meaning consistent usage of services and technical processes enables the measuring of KPIs. This in turn facilitates process control and...


On the Concept of Metadata Exchange in Cloud
Services - Part I

Enrique Castro-Leon, Robert Harmon, John Kennedy, and Mrigank Shekhar

Enrique Castro-Leon

Robert Harmon

John Kennedy

Mrigank Shekhar

The concept of metadata is essential in a number of disciplines, including Database Architecture and Library Science. In a cloud environment, service introspection is a must have requirement to establish meaningful relationships between cloud service consumers and providers. Metadata exchange refers to the automated exchange of information about a service offering during service setup and operations. Automated, standardized metadata exchange will become an essential ingredient in a functioning, scalable cloud service ecosystem. Under the current state of the art, when an application is implemented using outsourced cloud components there is inherently less transparency about the service components when services cross organizational boundaries as in private clouds, or even more so company boundaries. This circumstance makes it difficult to implement manageability policies for a composite application made of outsourced service components. This paper reports an initial exploration of geolocation and power management examples for service metadata elements. The notion of metadata is central to many disciplines such as the Dewey Decimal System for cataloguing books in library and information science, the EXIF data recorded with every frame by many digital cameras.[3] The notion of metadata is also essential to the business model of the leading social media companies like Facebook, Google, and Twitter. It can be said that the revenue from metadata is so valuable to these companies that it allows them to deliver the actual content to their user community essentially for free or at nominal cost. Reflecting this value, metadata is also at the core of intellectual property ownership and privacy controversies in the industry today. Cloud metadata constitutes an emerging field. The cloud metadata literature typically refers to metadata management for information stored in the cloud, about performance issues, replication policies and the optimal configurations for specific applications. In the context of databases, the notion of metadata is commonly associated with information about stored data to organize the data and make it easier to search and retrieve. Metadata access and replication policies are important factors in the information retrieval performance and, when improperly architected, can become a bottleneck. Metadata is...


Envisioning Cloud-Inspired Smarter Homes

Pethuru Raj Chelliah

Pethuru Raj Chelliah

The rapid rate of maturity of machine-to-machine (M2M) communication technologies has put their application processes in the spotlight. The initiative of this methodology aims to bring a range of real-time, adaptive applications and services to the forefront. A number of industry professionals has expressed interest in furthering advancements in this field for a range of business and use cases. People that reside in futurist smart homes, for example, will be able to use smartphones to remotely activate and control home-centric tools for enhanced convenience and comfort. The optimal usage of home appliances and other electronics to reduce energy consumption has become a viable option, while appliance safety and operation can be improved using various forms of higher-performance connectivity. Another trend of M2M is to enable service providers to collect real-time data from machines and appliances for analysis, before being applied for product design, engineering, and packaging improvement purposes. The key technical components of smart homes, their primary use cases, and the future of home networking, integration, and automation will be discussed and explored in this article. There are several drivers in M2M technology advancements that are relevant to smart homes, which include the mass production of smartphones, penetration of broadband communications, M2M integration, and adoption of the cloud. Business market research consistently praises M2M for the advantages provided to next-generation services by machines that can remotely and locally connect and collaborate with one another wirelessly. Managed home automation market revenue is predicted to have a compound annual growth rate of 60% until 2017...


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